Datasets:

J0nasW
/

paperswithcode

Dataset card Viewer Files Files and versions Community

Split (2)

train · 44.6k rows

paperID stringlengths 36 36	pwc_id stringlengths 8 47	arxiv_id stringlengths 6 16 ⌀	nips_id float64	url_abs stringlengths 18 329	url_pdf stringlengths 18 742	title stringlengths 8 325	abstract stringlengths 1 7.27k ⌀	authors stringlengths 2 7.06k	published stringlengths 10 10 ⌀	conference stringlengths 12 47 ⌀	conference_url_abs stringlengths 16 198 ⌀	conference_url_pdf stringlengths 27 199 ⌀	proceeding stringlengths 6 47 ⌀	taskID stringlengths 7 1.44k	areaID stringclasses 688 values	embedding stringlengths 9.26k 12.5k	umap_embedding stringlengths 29 44
d30b5a19-0f95-4c57-9733-dcd8d241d153	adversarial-background-aware-loss-for-weakly	2007.06643	null	https://arxiv.org/abs/2007.06643v1	https://arxiv.org/pdf/2007.06643v1.pdf	Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization	Temporally localizing activities within untrimmed videos has been extensively studied in recent years. Despite recent advances, existing methods for weakly-supervised temporal activity localization struggle to recognize when an activity is not occurring. To address this issue, we propose a novel method named A2CL-PT. Two triplets of the feature space are considered in our approach: one triplet is used to learn discriminative features for each activity class, and the other one is used to distinguish the features where no activity occurs (i.e. background features) from activity-related features for each video. To further improve the performance, we build our network using two parallel branches which operate in an adversarial way: the first branch localizes the most salient activities of a video and the second one finds other supplementary activities from non-localized parts of the video. Extensive experiments performed on THUMOS14 and ActivityNet datasets demonstrate that our proposed method is effective. Specifically, the average mAP of IoU thresholds from 0.1 to 0.9 on the THUMOS14 dataset is significantly improved from 27.9% to 30.0%.	['Kyle Min', 'Jason J. Corso']	2020-07-13	null	https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/2121_ECCV_2020_paper.php	https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590273.pdf	eccv-2020-8	['weakly-supervised-action-localization', 'weakly-supervised-temporal-action']	['computer-vision', 'computer-vision']	[ 4.04389679e-01 -2.78379798e-01 -4.92030412e-01 1.38230259e-02 -5.53314209e-01 -6.29174531e-01 5.20057619e-01 -2.65922807e-02 -4.13463056e-01 6.89744055e-01 3.23770344e-01 6.30357936e-02 1.98935136e-01 -4.81775761e-01 -7.62333930e-01 -1.08057916e+00 -3.63205105e-01 -3.66156697e-01 7.62846589e-01 2.29793772e-01 1.50679290e-01 4.75336879e-01 -1.14712238e+00 4.05196637e-01 6.00293875e-01 1.28093100e+00 1.05402553e-02 3.23936284e-01 1.57191291e-01 1.38672006e+00 -7.05896795e-01 3.09569240e-01 3.57228667e-01 -6.24926329e-01 -5.98935366e-01 1.70967862e-01 3.57855231e-01 -2.60827959e-01 -7.76447594e-01 1.00472748e+00 2.04885513e-01 2.85726935e-01 3.46555322e-01 -1.36999726e+00 -1.95143372e-01 4.79873925e-01 -8.03613424e-01 7.59711325e-01 3.72075081e-01 3.41881141e-02 8.18857551e-01 -8.20629776e-01 6.47702217e-01 7.80213475e-01 3.45226943e-01 3.92971605e-01 -9.49894369e-01 -8.15103173e-01 4.00073439e-01 4.27980006e-01 -1.53981960e+00 -4.72827643e-01 8.75172913e-01 -3.54987115e-01 6.26111805e-01 5.81444725e-02 7.30631769e-01 1.23868394e+00 2.14272022e-01 9.84085083e-01 9.38770890e-01 -2.18291357e-01 2.14136064e-01 -2.34356374e-01 -2.60273367e-01 7.36922741e-01 -3.97142880e-02 -8.01433176e-02 -7.82391071e-01 -2.73515992e-02 8.60113740e-01 1.99367851e-01 -4.36053753e-01 -3.79734308e-01 -1.50001192e+00 5.39704382e-01 3.98073643e-01 5.51541567e-01 -3.53925854e-01 2.39294261e-01 4.61657614e-01 1.54824704e-01 5.02776146e-01 8.32619369e-02 -3.13997537e-01 -4.19010192e-01 -1.00121439e+00 -5.41724116e-02 5.28903186e-01 7.55252659e-01 7.69919574e-01 -1.56203005e-02 -3.88187110e-01 6.88432455e-01 -9.31482837e-02 2.20565766e-01 5.19577563e-01 -8.58744323e-01 6.25037074e-01 6.64665997e-01 1.85532123e-01 -1.10787213e+00 -6.54874891e-02 -3.93016905e-01 -5.97990334e-01 -2.45501235e-01 4.70603675e-01 -3.10863227e-01 -8.48740101e-01 1.77116561e+00 2.83413529e-01 7.79523134e-01 -1.19260654e-01 9.11456645e-01 4.87297714e-01 8.97878945e-01 1.17862463e-01 -2.98042059e-01 9.86922741e-01 -1.29730797e+00 -6.07391357e-01 -3.39332610e-01 5.18085301e-01 -5.49277604e-01 7.54476607e-01 1.75567463e-01 -8.05780530e-01 -4.11978275e-01 -1.10882866e+00 3.54389578e-01 -1.90227970e-01 3.12737435e-01 4.43244427e-01 1.98970944e-01 -8.38792324e-01 4.13832307e-01 -1.04777741e+00 -2.94729203e-01 5.76508939e-01 1.84486866e-01 -4.76008296e-01 7.96494484e-02 -1.03226471e+00 4.30866122e-01 5.41519701e-01 3.76847982e-02 -1.30842257e+00 -2.62928277e-01 -8.12683642e-01 1.65743232e-01 8.98358166e-01 -6.16203398e-02 9.57518697e-01 -1.36941922e+00 -1.13767588e+00 5.33894360e-01 -2.98168063e-01 -5.25136530e-01 5.46594143e-01 -3.37020457e-01 -5.71421325e-01 6.93729401e-01 4.00661021e-01 5.16152918e-01 8.53749454e-01 -8.45778584e-01 -1.02867174e+00 -1.35144293e-01 9.35021117e-02 1.45557508e-01 -5.46903491e-01 2.37542018e-01 -9.23953295e-01 -9.80049729e-01 1.52687356e-01 -9.05733228e-01 -3.17672640e-02 1.53841496e-01 -2.62398720e-01 -1.68521792e-01 1.10908449e+00 -5.78793287e-01 1.38661921e+00 -2.27432919e+00 2.71046087e-02 2.37984583e-01 1.24061830e-01 1.55593708e-01 -1.43242568e-01 3.14080268e-01 -6.57262951e-02 -4.63935584e-02 -8.46051127e-02 8.60726461e-03 -4.53709841e-01 1.88925341e-01 -1.68214455e-01 5.87623298e-01 2.53383905e-01 7.33278155e-01 -1.00913835e+00 -6.03732526e-01 1.74511477e-01 2.67876774e-01 -4.02741373e-01 1.97645366e-01 6.84828088e-02 5.99351168e-01 -6.14930034e-01 8.38978410e-01 3.58117610e-01 -3.03030044e-01 2.22488895e-01 -9.39093977e-02 -2.51921147e-01 1.51938245e-01 -1.15656483e+00 1.72548473e+00 -1.94355518e-01 6.71163559e-01 -2.16994524e-01 -1.11882472e+00 5.92113018e-01 4.27887380e-01 1.02779007e+00 -7.04456866e-01 4.07742243e-03 -9.32567343e-02 1.69797018e-02 -5.17827868e-01 2.86653429e-01 2.31416717e-01 -1.24819875e-01 3.62511724e-01 2.76649505e-01 7.60258913e-01 5.30062735e-01 2.43379056e-01 1.57945383e+00 3.17976981e-01 4.54410076e-01 -1.00955166e-01 6.95831597e-01 -2.21786499e-01 9.78347123e-01 7.26294637e-01 -6.41447902e-01 3.86097968e-01 6.99364841e-01 -3.62071067e-01 -5.12985170e-01 -1.02550435e+00 2.93987542e-01 1.21289742e+00 4.70325887e-01 -5.49620748e-01 -8.43956172e-01 -1.20960319e+00 -3.09470296e-01 1.84352413e-01 -8.35830688e-01 -2.69899070e-01 -7.88209796e-01 -3.81877452e-01 4.66752380e-01 8.00745487e-01 8.76357675e-01 -1.17864859e+00 -6.98682725e-01 1.44247606e-01 -5.06739080e-01 -1.39606607e+00 -8.22293282e-01 2.21123010e-01 -7.71327972e-01 -1.12300622e+00 -7.17087150e-01 -8.24428499e-01 7.67136216e-01 5.44725597e-01 7.93484986e-01 -6.14003204e-02 2.11420991e-02 1.78399324e-01 -5.62059760e-01 2.70941090e-02 -1.95147749e-02 6.28235098e-03 6.19372912e-02 6.46264195e-01 3.84461969e-01 -5.62947333e-01 -7.61381686e-01 7.35974550e-01 -8.09033811e-01 -2.42620513e-01 6.55042171e-01 6.20149732e-01 6.37250423e-01 5.06028384e-02 4.08911109e-01 -4.71772671e-01 5.11079244e-02 -7.14735091e-01 -3.71793479e-01 2.20155492e-01 -9.22644734e-02 -1.72886416e-01 7.33437240e-01 -7.81560600e-01 -7.91368842e-01 3.55361402e-01 1.60803720e-01 -6.46574378e-01 -2.93746799e-01 3.93163055e-01 -2.59265751e-01 -1.94256350e-01 5.29680312e-01 5.34233868e-01 -4.18746531e-01 -2.40840659e-01 -5.04096150e-02 3.38996321e-01 6.78662360e-01 -4.48713720e-01 8.38087022e-01 7.40500450e-01 -2.31553435e-01 -7.87420988e-01 -9.54638124e-01 -7.45729685e-01 -4.83100325e-01 -5.25933206e-01 8.33697796e-01 -1.00293720e+00 -3.86350006e-01 3.92667860e-01 -8.18921864e-01 -2.42003828e-01 -2.03069046e-01 5.32178044e-01 -3.64687055e-01 4.70133692e-01 -4.45359588e-01 -5.58180392e-01 -1.11075677e-01 -9.91169512e-01 9.51420844e-01 3.41628700e-01 -8.95016715e-02 -8.09025586e-01 -3.33121629e-03 2.20970422e-01 -6.82159932e-03 4.33070809e-01 3.57908517e-01 -6.14464462e-01 -6.82624102e-01 -3.00039887e-01 -4.19407412e-02 3.80811155e-01 4.31403190e-01 -1.11891493e-01 -7.87684739e-01 -2.81378299e-01 5.46143129e-02 -2.32856512e-01 7.74698198e-01 3.04356754e-01 1.33844697e+00 -3.50226790e-01 -5.52695692e-01 4.92583483e-01 1.12208617e+00 6.36198401e-01 6.28517926e-01 3.72569650e-01 5.68071306e-01 1.12253815e-01 9.38462377e-01 4.08328176e-01 -1.10792406e-01 8.47421348e-01 4.53348458e-01 -7.25841969e-02 7.78188035e-02 -4.05962378e-01 7.86396563e-01 4.36573744e-01 -2.14503303e-01 -2.72668064e-01 -7.04873979e-01 5.92784822e-01 -2.01191783e+00 -1.19454861e+00 4.19999599e-01 2.06339669e+00 6.20082319e-01 3.49004120e-01 2.69739658e-01 1.13541447e-01 7.65263140e-01 6.14225209e-01 -5.88430703e-01 3.38211238e-01 -9.35659185e-02 2.73999255e-02 3.17527115e-01 -2.77435053e-02 -1.56578887e+00 8.83390367e-01 5.81525803e+00 8.56104076e-01 -1.11994922e+00 2.24438950e-01 4.13051695e-01 -3.40687424e-01 3.99171680e-01 2.58616656e-02 -4.84483451e-01 7.65852034e-01 5.83699822e-01 -8.01904500e-02 2.77373552e-01 9.27294135e-01 4.60157484e-01 -4.00247186e-01 -1.01009190e+00 9.46076095e-01 3.10175240e-01 -1.14349139e+00 -1.37403617e-02 -8.24826062e-02 8.39245737e-01 -5.85862659e-02 -2.17634141e-01 3.59360218e-01 -1.70937300e-01 -7.12913573e-01 9.40127254e-01 3.64757836e-01 6.23996198e-01 -8.60265076e-01 6.36367857e-01 4.85341966e-01 -1.60695446e+00 -2.04394534e-01 2.57235803e-02 2.00086627e-02 1.26017347e-01 2.78140575e-01 -5.07924736e-01 3.70186657e-01 8.78036320e-01 1.14916015e+00 -5.70299208e-01 1.05169940e+00 -4.60013777e-01 8.79536271e-01 -1.88486025e-01 9.83448550e-02 5.30742168e-01 -6.32331073e-02 5.33017874e-01 1.12865150e+00 2.34693497e-01 -1.50423571e-01 5.38045704e-01 4.77546871e-01 -2.55033106e-01 -2.55455095e-02 -6.44446075e-01 -1.12906657e-01 2.92939723e-01 1.22394979e+00 -9.08671439e-01 -2.81836390e-01 -6.07658088e-01 1.23316944e+00 2.43151277e-01 4.35666174e-01 -1.25932276e+00 -4.34743106e-01 5.59924364e-01 8.03108737e-02 5.07714868e-01 -2.01445207e-01 3.17786396e-01 -1.50542152e+00 2.83390462e-01 -7.17452407e-01 5.46623170e-01 -6.26999676e-01 -8.27941954e-01 3.51363242e-01 -1.18253820e-01 -1.55375838e+00 -1.78433329e-01 -2.84714967e-01 -6.40798450e-01 3.97205144e-01 -1.22482288e+00 -9.33070362e-01 -5.82933187e-01 7.66744375e-01 7.11632729e-01 -1.74600184e-01 3.58471215e-01 4.86237079e-01 -7.12741911e-01 5.53061128e-01 9.84805403e-04 5.57320178e-01 6.24298394e-01 -9.51399267e-01 1.05990589e-01 1.42755580e+00 4.93555218e-01 5.74097037e-01 3.66546392e-01 -5.92035711e-01 -1.12503552e+00 -1.23057616e+00 6.32784545e-01 -2.16686368e-01 8.08246076e-01 -4.02338535e-01 -7.57200718e-01 7.58913159e-01 3.07273865e-02 4.79328424e-01 6.01986110e-01 -3.27351332e-01 -3.37569267e-01 -2.62865514e-01 -9.23787951e-01 6.94575608e-01 1.24365389e+00 -4.76212204e-01 -5.11532366e-01 1.59973040e-01 4.15848196e-01 -3.10079038e-01 -6.97031617e-01 3.58967632e-01 5.29120088e-01 -9.28238928e-01 8.09107661e-01 -4.56217170e-01 4.22143847e-01 -5.93664229e-01 -1.43525794e-01 -9.91994619e-01 -2.13462994e-01 -7.62008607e-01 -5.55847168e-01 9.76355910e-01 4.14367318e-02 -4.48336422e-01 8.93498123e-01 -1.62040979e-01 -1.16398416e-01 -7.55767405e-01 -1.02998638e+00 -9.93772388e-01 -4.55739260e-01 -1.62441775e-01 1.06152885e-01 1.01164997e+00 3.67608294e-02 1.49200857e-01 -6.15311027e-01 1.34333193e-01 3.34454268e-01 1.55629575e-01 6.60444856e-01 -7.16476083e-01 -1.95885956e-01 -2.12316304e-01 -6.24203920e-01 -1.47458565e+00 1.54046297e-01 -6.96764708e-01 1.32646233e-01 -1.17138743e+00 4.95789886e-01 -8.14440474e-03 -7.94542253e-01 7.31174469e-01 -4.76317666e-02 3.74201864e-01 4.49834876e-02 3.04217815e-01 -9.53236520e-01 3.93861145e-01 9.81706619e-01 -1.58710256e-01 -9.75579321e-02 -4.86301724e-03 -4.25960064e-01 7.83289552e-01 8.77294242e-01 -5.53826928e-01 -4.36435521e-01 -8.93480107e-02 -3.62269938e-01 6.90833479e-02 4.68962342e-01 -1.36907411e+00 1.92000359e-01 -2.64901996e-01 4.79062706e-01 -6.34703934e-01 1.84298351e-01 -9.36247289e-01 -1.33300185e-01 4.21933085e-01 -2.28023991e-01 -1.60973996e-01 1.23836629e-01 8.73466790e-01 -5.04618704e-01 -1.27367144e-02 7.87962914e-01 3.91876213e-02 -1.01758289e+00 3.92531753e-01 -5.25758028e-01 7.40021914e-02 1.41818249e+00 -2.59215087e-01 -2.37825528e-01 -3.44881803e-01 -7.57108450e-01 1.30958319e-01 4.11408722e-01 5.38936615e-01 5.43075860e-01 -1.40424454e+00 -3.31313938e-01 8.35080445e-02 2.51886874e-01 -3.78601611e-01 2.05876291e-01 1.00520456e+00 -4.03994381e-01 3.82018209e-01 -2.33771384e-01 -6.79195762e-01 -1.30058753e+00 4.12135899e-01 3.67535114e-01 -2.90142596e-01 -5.67289591e-01 5.91502726e-01 3.01346779e-01 3.47581625e-01 3.99476886e-01 -2.63310194e-01 -2.82383025e-01 8.01760703e-02 5.89892685e-01 3.52170140e-01 -1.67034969e-01 -8.45767140e-01 -5.93114138e-01 4.47870493e-01 -7.56099448e-02 4.39309049e-03 1.14738142e+00 1.25051916e-01 8.36528614e-02 4.36742246e-01 1.23339140e+00 1.28699169e-01 -1.73735785e+00 -3.23110610e-01 6.61528707e-02 -4.98265237e-01 -1.02901049e-01 -6.70333028e-01 -1.35685682e+00 6.61258161e-01 5.17391622e-01 1.26381978e-01 1.50277865e+00 1.99393854e-02 7.44011641e-01 2.49455750e-01 4.27712888e-01 -1.07903326e+00 5.46491563e-01 4.24269259e-01 7.13133991e-01 -9.93883491e-01 -1.75836489e-01 -3.15550745e-01 -6.12133205e-01 9.14029479e-01 7.54704475e-01 -2.49913149e-02 3.14397812e-01 2.25400701e-01 -1.57480836e-01 -7.63448700e-02 -5.82485020e-01 -1.16875671e-01 2.83960134e-01 2.63976961e-01 1.42415673e-01 -2.89265484e-01 -2.30298176e-01 3.48930329e-01 5.07760704e-01 9.71324518e-02 3.01886588e-01 1.32747912e+00 -4.09503311e-01 -6.73371434e-01 -2.39390463e-01 3.57975155e-01 -7.28219867e-01 1.35390729e-01 -4.68787551e-01 7.13654399e-01 2.47739479e-01 1.04622376e+00 8.79060850e-02 -5.27806818e-01 2.20323429e-01 -9.46574584e-02 2.00852126e-01 -4.98753607e-01 -4.96950954e-01 4.21161741e-01 1.42992316e-02 -1.00134540e+00 -7.73333073e-01 -8.69054556e-01 -1.16837943e+00 1.13651380e-01 -1.57458276e-01 3.12388033e-01 7.92830288e-02 7.39590645e-01 2.77567655e-01 5.01291037e-01 8.78827989e-01 -7.79647171e-01 -9.22788307e-02 -8.66680503e-01 -5.58283985e-01 4.09588575e-01 2.65274227e-01 -9.14377034e-01 -5.39931595e-01 3.05260003e-01]	[8.415910720825195, 0.6566603183746338]
b12bba26-7d89-470c-b5ae-5ff6363d7aee	molecular-graph-convolutions-moving-beyond	1603.00856	null	http://arxiv.org/abs/1603.00856v3	http://arxiv.org/pdf/1603.00856v3.pdf	Molecular Graph Convolutions: Moving Beyond Fingerprints	Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular "graph convolutions", a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph---atoms, bonds, distances, etc.---which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.	['Vijay Pande', 'Kevin McCloskey', 'Steven Kearnes', 'Marc Berndl', 'Patrick Riley']	2016-03-02	null	null	null	null	['graph-regression']	['graphs']	[ 4.82508749e-01 3.11219972e-02 -6.93815291e-01 -4.88606453e-01 -5.05816936e-02 -6.80829942e-01 3.16764891e-01 7.84880519e-01 -1.80452064e-01 1.09567904e+00 2.21277267e-01 -8.95242274e-01 -1.61583349e-01 -1.13446414e+00 -8.35596383e-01 -7.59679794e-01 -6.16749108e-01 4.05058801e-01 -1.73757270e-01 -2.54445612e-01 5.53190887e-01 1.01415825e+00 -7.07780778e-01 4.99048233e-01 5.61123669e-01 5.35707712e-01 -5.87884150e-02 5.05104661e-01 -3.44535232e-01 8.12530637e-01 -4.21708554e-01 -2.61601776e-01 -2.37655535e-01 -3.24484318e-01 -7.36709476e-01 -5.65863848e-01 6.72050595e-01 3.29378457e-03 -7.49804735e-01 1.05858195e+00 5.67868054e-01 1.73177287e-01 7.88778305e-01 -5.78679621e-01 -9.59064841e-01 4.57236767e-01 -3.09066296e-01 1.79555967e-01 6.97857976e-01 1.63960770e-01 1.08649421e+00 -7.89045036e-01 9.12333310e-01 1.20673287e+00 8.85291040e-01 3.95291299e-01 -1.49001837e+00 -6.47437513e-01 1.66188747e-01 5.53205460e-02 -1.12174761e+00 -1.10270642e-01 5.83868921e-01 -5.94528496e-01 1.42274678e+00 3.97558779e-01 5.76606870e-01 1.00211096e+00 7.42059231e-01 2.10935310e-01 7.90101469e-01 -1.44723415e-01 3.18865627e-01 -2.70901769e-01 2.84696966e-01 1.10771358e+00 5.59714854e-01 3.86817098e-01 -6.13507330e-01 -7.12282181e-01 7.93264449e-01 5.03556490e-01 -4.70985413e-01 -4.77147102e-01 -1.11018765e+00 1.00024176e+00 8.38610113e-01 -3.49847712e-02 -3.33503127e-01 6.55898392e-01 2.77585983e-01 3.11220229e-01 1.37864441e-01 8.70613933e-01 -4.73194063e-01 3.20616901e-01 -7.72104263e-01 3.76576245e-01 8.39585423e-01 8.07167411e-01 1.03337121e+00 -8.93111713e-03 -1.99881077e-01 2.80557901e-01 2.06519738e-01 4.96368064e-03 1.51530327e-02 -2.04814151e-01 1.83776125e-01 5.92521012e-01 -2.99614258e-02 -9.82771456e-01 -6.89653158e-01 -4.18616652e-01 -5.66258967e-01 3.71950567e-01 4.10718590e-01 -1.82543248e-01 -1.18872476e+00 1.47897100e+00 1.14935577e-01 -5.16114570e-02 -2.48221576e-01 4.87595677e-01 1.04018092e+00 4.36360657e-01 4.87667292e-01 -2.25986000e-02 9.96909559e-01 -3.64448726e-01 -4.21268344e-01 2.40525067e-01 8.50772917e-01 -5.27388334e-01 5.18822134e-01 3.67502838e-01 -5.26963711e-01 -2.53292590e-01 -1.23325086e+00 7.76763856e-02 -9.24873888e-01 -4.30860281e-01 1.48135543e+00 8.04773033e-01 -8.33839297e-01 1.48143256e+00 -4.36243057e-01 -1.23321608e-01 6.89546943e-01 9.91714895e-01 -6.77545190e-01 -1.85114548e-01 -1.01475012e+00 7.87789822e-01 4.45172608e-01 -1.74622566e-01 -7.27947116e-01 -8.81113231e-01 -8.73403728e-01 1.15030982e-01 1.33278981e-01 -6.04010999e-01 8.68019223e-01 -5.44488728e-01 -1.11856663e+00 4.38050538e-01 -2.77419478e-01 -4.21446890e-01 5.82026653e-02 3.26855302e-01 -4.30913538e-01 -6.31254762e-02 -1.25146225e-01 5.00257432e-01 2.71116316e-01 -8.46053958e-01 -2.48531234e-02 -3.64546210e-01 2.00318187e-01 -1.35621354e-01 1.04401924e-01 -1.83076367e-01 1.58024251e-01 -4.76946205e-01 -3.24283391e-02 -7.38652408e-01 -7.68730104e-01 4.71318066e-02 -7.42654622e-01 -5.29273925e-03 5.50693512e-01 -2.14930639e-01 1.10109830e+00 -1.53974926e+00 -1.40775234e-01 6.51370406e-01 7.48093963e-01 2.44361952e-01 -2.73277730e-01 1.07665896e+00 -6.76042020e-01 3.35503429e-01 2.31229886e-02 4.27224815e-01 -4.15042430e-01 4.15815674e-02 -9.49868113e-02 6.06955767e-01 3.26569498e-01 9.89518881e-01 -1.29056561e+00 -3.57813016e-02 2.62905836e-01 6.64438844e-01 -5.78594506e-01 -2.72348046e-01 -6.71180189e-01 4.33177769e-01 -9.48662817e-01 8.62035275e-01 7.89050281e-01 -5.43827057e-01 7.36210287e-01 -2.47886315e-01 -1.34485543e-01 4.62184787e-01 -6.02194667e-01 1.62731886e+00 2.45722383e-01 4.52944219e-01 -5.97691834e-01 -8.30929101e-01 8.12103152e-01 1.79917797e-01 7.30027139e-01 -6.10393822e-01 -1.95398897e-01 7.28095770e-02 4.34786260e-01 -9.65065733e-02 1.51934460e-01 -1.21354908e-01 4.33550417e-01 2.19523042e-01 1.79450035e-01 3.32500458e-01 2.06670195e-01 1.36216938e-01 1.38275659e+00 1.82231069e-01 4.17684942e-01 -3.51315856e-01 1.79797739e-01 2.36419186e-01 2.59720325e-01 7.21361041e-01 2.56053805e-01 3.01553071e-01 6.32375181e-01 -1.11512268e+00 -7.41838753e-01 -8.97378922e-01 -1.88128382e-01 9.84941840e-01 -1.27869666e-01 -8.68021011e-01 -4.17513430e-01 -8.25086772e-01 5.86622298e-01 2.67126590e-01 -1.04218173e+00 -2.65891254e-01 -3.25690895e-01 -9.75703061e-01 3.73112321e-01 3.38093758e-01 -2.86974132e-01 -1.00192809e+00 1.62269160e-01 6.52163148e-01 6.34331763e-01 -4.22023267e-01 -6.60224378e-01 9.13640201e-01 -9.92465377e-01 -1.65775836e+00 -4.72201496e-01 -6.63031101e-01 7.85146415e-01 3.37108284e-01 1.20398223e+00 1.37087271e-01 -5.54046273e-01 -1.72001317e-01 2.85923714e-03 -6.19817257e-01 -2.61951208e-01 -9.39091966e-02 -9.36068967e-02 -2.62110084e-01 5.92080653e-01 -8.85769486e-01 -9.19178486e-01 6.35341406e-02 -4.47578520e-01 -3.16597819e-01 5.63179374e-01 9.37430024e-01 9.87760305e-01 -2.29842216e-01 4.02993470e-01 -1.72337997e+00 8.82572830e-01 -4.33371514e-01 -5.08587301e-01 2.65814960e-01 -7.16148794e-01 4.86503541e-01 8.11570048e-01 -3.15277427e-01 -4.29561436e-01 3.21844399e-01 -8.91395584e-02 -1.90561131e-01 1.66909665e-01 8.95948589e-01 -1.98659003e-01 -9.57158566e-01 1.04485524e+00 1.41001821e-01 -8.65753293e-02 -6.45427346e-01 2.37652525e-01 1.35055840e-01 2.37343103e-01 -7.97069192e-01 1.67096332e-01 1.77069485e-01 6.28132343e-01 -6.93772495e-01 -2.97293901e-01 -4.19338435e-01 -4.86651272e-01 3.25657785e-01 5.90916514e-01 -6.15013242e-01 -1.19037843e+00 -3.00242841e-01 -1.24487543e+00 -6.24300465e-02 -8.75287801e-02 4.35620844e-01 -3.15776616e-01 4.74161625e-01 -5.35857737e-01 -4.37040091e-01 -2.52226710e-01 -1.23161268e+00 6.92326367e-01 1.71180338e-01 -2.65754461e-01 -1.10487878e+00 4.22024637e-01 -2.76843637e-01 1.97402686e-01 8.53854060e-01 1.32418489e+00 -9.96019125e-01 -7.06950843e-01 -4.08720225e-01 -2.71970481e-01 -1.35101944e-01 3.95654291e-01 5.73546216e-02 -1.06341398e+00 -1.46454751e-01 -8.41108561e-01 3.80519927e-02 9.52038825e-01 6.56393290e-01 1.55259204e+00 -4.30066496e-01 -8.07870388e-01 9.25113559e-01 1.40871561e+00 6.48452461e-01 6.24783218e-01 -7.12142065e-02 8.88910949e-01 2.89922208e-01 3.17581072e-02 5.25609314e-01 -1.14487424e-01 4.10341501e-01 6.19243085e-01 -4.84330475e-01 -6.34778738e-02 -6.29607737e-01 -1.16227955e-01 -4.28340808e-02 -3.91464919e-01 -4.02906537e-01 -6.88173354e-01 -2.19660595e-01 -1.58977616e+00 -1.09499848e+00 -3.66710931e-01 2.41669011e+00 7.92890370e-01 1.03549279e-01 1.50641188e-01 -2.91723132e-01 5.45543969e-01 1.29460022e-01 -9.34393048e-01 -7.81361163e-01 -3.29159573e-02 9.42704976e-01 1.01216745e+00 4.73052353e-01 -9.39508438e-01 8.46093714e-01 8.23525620e+00 5.85666001e-01 -1.39712274e+00 -6.37408495e-01 6.50096834e-01 3.20461392e-01 -6.41540349e-01 1.68552205e-01 -5.44956744e-01 4.12546098e-01 1.08861935e+00 -6.52858242e-02 5.31135559e-01 7.74869263e-01 1.68993652e-01 1.58298850e-01 -1.53773236e+00 8.02109182e-01 -5.58922708e-01 -2.36255980e+00 6.32502377e-01 6.28719866e-01 3.90302002e-01 1.97061941e-01 8.26462880e-02 -2.32982069e-01 5.56863189e-01 -1.79772866e+00 1.49622396e-01 5.69516420e-01 1.13390064e+00 -8.40227664e-01 3.34916085e-01 -2.38977224e-01 -9.85171556e-01 3.07833105e-01 -6.31717920e-01 -3.53477374e-02 -4.49033409e-01 4.77085531e-01 -1.00127864e+00 5.13530612e-01 1.26206130e-01 8.57284963e-01 -5.52275658e-01 1.16780376e+00 2.27046870e-02 2.96666831e-01 1.14327401e-01 -3.68704975e-01 3.96745086e-01 -2.85141855e-01 1.39085487e-01 1.50120926e+00 -4.29015085e-02 -5.33261858e-02 2.68739432e-01 7.93461502e-01 -3.49311382e-01 1.18678488e-01 -1.00307059e+00 -8.70859444e-01 3.77414823e-01 9.55779254e-01 -5.23911297e-01 -1.80398881e-01 -4.76798773e-01 6.55247271e-01 2.58696198e-01 5.89437902e-01 -3.94435078e-01 -8.29289734e-01 1.04137611e+00 3.13769042e-01 9.38182399e-02 -2.91400939e-01 8.48913006e-03 -6.71880424e-01 -6.07789338e-01 -1.01494074e+00 2.86313593e-01 -5.08137703e-01 -1.04481399e+00 3.24601948e-01 -4.52151060e-01 -8.15815151e-01 -1.25507519e-01 -1.43761873e+00 -6.24145925e-01 1.26069617e+00 -1.30984068e+00 -8.43250513e-01 2.15877175e-01 4.97783393e-01 -1.69739276e-01 -2.17324078e-01 1.28224015e+00 7.60575756e-02 -2.32864574e-01 5.03440499e-01 5.29908895e-01 8.67503360e-02 6.27074540e-01 -1.40740681e+00 7.33642161e-01 -2.79174056e-02 4.50360626e-01 1.22215235e+00 7.24892020e-01 -7.56958902e-01 -1.71170664e+00 -9.35483575e-01 6.84087753e-01 -4.25301284e-01 5.60279906e-01 -2.09158853e-01 -8.12008679e-01 4.72852439e-01 -4.71656360e-02 2.07873642e-01 1.42642820e+00 5.20886242e-01 -8.65632534e-01 2.59633482e-01 -1.15028203e+00 5.10673821e-01 1.27734351e+00 -7.61743605e-01 6.40305206e-02 7.94780552e-01 6.56449258e-01 -2.29717880e-01 -1.06505585e+00 1.82257384e-01 7.52507031e-01 -7.96827674e-01 1.24546182e+00 -1.51506937e+00 1.53442264e-01 -2.43089765e-01 -9.44167003e-02 -1.31878948e+00 -7.66934216e-01 -9.03492749e-01 -1.82334095e-01 2.15649545e-01 7.72475004e-01 -7.56860495e-01 1.24330950e+00 3.45968783e-01 -2.59844899e-01 -8.39757085e-01 -5.99010468e-01 -4.97664809e-01 1.19149581e-01 1.73398387e-02 9.33070064e-01 1.00244761e+00 4.07125622e-01 4.54335988e-01 -1.71732143e-01 9.32517461e-03 4.11715597e-01 1.37985170e-01 4.45944041e-01 -1.30371547e+00 -5.36723495e-01 -6.23760998e-01 -7.80784726e-01 -7.01830745e-01 -2.31524140e-01 -1.18207407e+00 -6.68932199e-01 -1.48300207e+00 1.76294804e-01 -1.54820830e-01 -7.99641907e-01 5.83306074e-01 4.41438407e-02 -1.31582618e-01 -2.76009649e-01 -1.70813620e-01 -3.69564027e-01 6.43951399e-03 1.57939649e+00 -6.61602736e-01 -1.80662736e-01 -1.72842406e-02 -1.01802850e+00 2.33277053e-01 6.17724001e-01 -4.84507650e-01 -4.93163973e-01 1.23707075e-02 2.83638835e-01 1.48404256e-01 1.42870292e-01 -7.77370691e-01 7.93964937e-02 -5.79904318e-01 9.58700776e-01 -3.37895960e-01 2.24062636e-01 -3.99449766e-01 5.07818103e-01 7.60015309e-01 -3.14482629e-01 6.27346244e-03 2.32670754e-01 8.85853648e-01 4.57622148e-02 6.70021102e-02 4.47380900e-01 -4.82679814e-01 -3.39706689e-01 9.74665165e-01 -2.74355054e-01 -4.24853474e-01 3.93667430e-01 -6.36342227e-01 -3.90692443e-01 -1.60437882e-01 -9.40341234e-01 -2.08953470e-01 5.93649209e-01 -1.04529269e-01 6.54561996e-01 -1.06122994e+00 -2.55847543e-01 1.44170851e-01 3.40616345e-01 -4.72827196e-01 -1.84399799e-01 2.59848952e-01 -8.21580052e-01 7.53016591e-01 -2.98940420e-01 -1.15481362e-01 -1.05765438e+00 8.24883223e-01 5.19127667e-01 -8.68243948e-02 -3.98307025e-01 8.24444830e-01 4.91891861e-01 -2.55419105e-01 2.20495716e-01 -3.42821598e-01 2.86821928e-02 -1.96645737e-01 6.00868881e-01 -1.14774741e-01 2.29249895e-01 -1.39961392e-01 -5.35828054e-01 1.75326809e-01 -3.64003092e-01 6.66286409e-01 1.50946510e+00 8.10729861e-01 -4.61438186e-02 -8.06966126e-02 1.21134722e+00 5.41002788e-02 -1.06993020e+00 -1.27913907e-01 3.08950007e-01 -4.60893750e-01 -3.29470858e-02 -1.01044655e+00 -6.67950809e-01 1.05916929e+00 4.09328103e-01 -2.99637932e-02 3.65659416e-01 -3.99936080e-01 3.61332446e-01 8.77263188e-01 4.44375247e-01 -6.98612988e-01 8.50842148e-03 2.67786503e-01 6.60117686e-01 -9.89741623e-01 4.12322700e-01 -3.73272121e-01 -1.08538732e-01 1.59104156e+00 1.52314514e-01 -1.44860834e-01 7.20165372e-01 8.65684077e-02 -5.01032710e-01 -7.40297377e-01 -5.89859068e-01 -2.74594128e-01 4.79016542e-01 1.01507080e+00 1.15815914e+00 2.38562316e-01 -1.87731802e-01 9.78533775e-02 2.37648934e-01 3.91226076e-02 6.43442497e-02 9.45839643e-01 -6.65474951e-01 -1.70934665e+00 -1.31730184e-01 7.49371111e-01 -4.99438822e-01 -5.69336653e-01 -1.06915951e+00 6.92081511e-01 3.97886299e-02 6.25764132e-01 -4.28444892e-01 -6.88732564e-01 2.86910534e-01 -1.07047111e-02 8.87821257e-01 -8.54381025e-01 -6.08422160e-01 -1.31412536e-01 3.52939099e-01 -7.06608891e-01 -1.76467840e-02 -1.43641993e-01 -1.28229809e+00 -7.96100199e-01 -2.61588514e-01 4.09492970e-01 6.97852969e-01 4.28863198e-01 6.25849605e-01 5.33327043e-01 4.21650290e-01 -7.65480459e-01 -2.01651618e-01 -5.20065308e-01 -7.63610363e-01 1.13144495e-01 3.89772803e-01 -5.88498950e-01 1.54364258e-01 -2.66913295e-01]	[5.105561256408691, 5.782642364501953]
ea1fec54-cfc2-44a0-9e27-17943c2f64ea	no-reference-image-quality-assessment-based	null	null	https://www.mdpi.com/2313-433X/6/8/75	https://www.mdpi.com/2313-433X/6/8/75/htm	No-Reference Image Quality Assessment Based on the Fusion of Statistical and Perceptual Features	The goal of no-reference image quality assessment (NR-IQA) is to predict the quality of an image as perceived by human observers without using any pristine, reference images. In this study, an NR-IQA algorithm is proposed which is driven by a novel feature vector containing statistical and perceptual features. Different from other methods, normalized local fractal dimension distribution and normalized first digit distributions in the wavelet and spatial domains are incorporated into the statistical features. Moreover, powerful perceptual features, such as colorfulness, dark channel feature, entropy, and mean of phase congruency image, are also incorporated to the proposed model. Experimental results on five large publicly available databases (KADID-10k, ESPL-LIVE HDR, CSIQ, TID2013, and TID2008) show that the proposed method is able to outperform other state-of-the-art methods.	['Domonkos Varga']	2020-07-30	null	null	null	null	['no-reference-image-quality-assessment']	['computer-vision']	[ 9.97546315e-02 -6.08953357e-01 -4.52758884e-03 -1.67011335e-01 -5.72920084e-01 -2.18535006e-01 5.50716996e-01 4.36801091e-02 -3.37597907e-01 5.98331630e-01 2.73861706e-01 2.10047975e-01 -2.04152554e-01 -6.56603694e-01 -7.14692995e-02 -7.87535667e-01 -2.20504448e-01 -5.99644244e-01 3.80466491e-01 -3.37301642e-01 7.17582762e-01 3.78596127e-01 -1.73340833e+00 1.47606820e-01 1.01040292e+00 1.54381621e+00 2.13553935e-01 5.08323908e-01 3.62716347e-01 7.83162713e-01 -3.93241704e-01 -3.25424492e-01 3.64596307e-01 -6.74459457e-01 -4.78458524e-01 2.43253872e-01 1.69602469e-01 -2.69158602e-01 -3.32441330e-01 1.26638699e+00 7.40622401e-01 1.60673454e-01 7.03602672e-01 -1.08496499e+00 -1.13447261e+00 -1.97583720e-01 -7.34778225e-01 6.10567808e-01 5.56304276e-01 3.28288376e-01 7.32359052e-01 -8.66915762e-01 6.34112358e-01 1.20547616e+00 5.00186503e-01 -1.63963079e-01 -1.23516250e+00 -4.95749563e-01 -3.76526803e-01 8.37708056e-01 -1.52512980e+00 -3.60867977e-01 9.96346653e-01 -3.63089591e-01 4.04964179e-01 2.78915912e-01 7.20614195e-01 6.76543653e-01 8.05761158e-01 2.55384982e-01 1.93799508e+00 -5.43282866e-01 3.70128274e-01 -4.76776846e-02 -1.36771470e-01 6.73718274e-01 5.16888797e-02 3.85238558e-01 -6.53277338e-01 7.69282728e-02 7.29768693e-01 -2.92343497e-01 -4.59741354e-01 -3.09349120e-01 -1.31239307e+00 6.16644502e-01 4.02641892e-01 4.98326480e-01 -5.78343153e-01 -3.66718411e-01 2.36533523e-01 3.71032447e-01 4.03052002e-01 1.62075773e-01 -1.45487815e-01 -1.88139930e-01 -7.92596757e-01 -1.42359823e-01 2.84408867e-01 5.16571045e-01 6.69909298e-01 2.15359643e-01 -2.94196457e-01 7.52429485e-01 2.05944642e-01 8.81093860e-01 8.68669391e-01 -1.25808167e+00 -2.01468229e-01 4.13388461e-01 2.87995756e-01 -1.81142724e+00 -3.64224225e-01 -2.72067100e-01 -1.18363142e+00 5.16689718e-01 3.38880122e-02 6.00185990e-01 -6.70634568e-01 1.41026974e+00 6.48228750e-02 8.52309838e-02 2.71339893e-01 1.05937898e+00 9.37207758e-01 7.19502628e-01 -1.22336797e-01 -6.98749900e-01 1.27648115e+00 -6.31925642e-01 -1.06129825e+00 1.34568259e-01 -1.09783687e-01 -9.58286405e-01 1.28752160e+00 6.67263329e-01 -1.09897900e+00 -1.32495463e+00 -1.31098211e+00 1.80242956e-01 -3.65211874e-01 1.05639346e-01 1.67745039e-01 7.27466583e-01 -1.15961838e+00 6.04028463e-01 -1.87814087e-01 -3.85872483e-01 1.03411481e-01 -1.65571317e-01 -5.25265515e-01 -2.58402497e-01 -1.24107420e+00 1.01894236e+00 4.40838337e-01 -6.57931045e-02 -4.75997031e-01 -1.87884375e-01 -7.40419030e-01 -1.07675321e-01 -1.30791545e-01 -3.67990941e-01 4.57850635e-01 -9.48269963e-01 -1.72939634e+00 7.51625299e-01 -3.68487230e-03 -2.99564987e-01 1.79024637e-01 2.03958690e-01 -1.03646743e+00 6.37893319e-01 -6.00000378e-03 5.72463036e-01 1.05025852e+00 -1.34537578e+00 -3.75047237e-01 -4.49340433e-01 -3.34888756e-01 3.27948511e-01 -2.84117341e-01 -1.04030333e-01 -3.40595067e-01 -7.72961497e-01 2.46281758e-01 -5.89997411e-01 1.20429449e-01 2.19340637e-01 -1.75099403e-01 1.43253595e-01 7.19432294e-01 -9.97099638e-01 1.30781031e+00 -2.50729084e+00 -2.04257026e-01 2.22959548e-01 6.26176670e-02 2.30501637e-01 -4.39969122e-01 1.61071047e-01 3.20241675e-02 -3.07314284e-02 -1.24297671e-01 4.66484547e-01 -5.20846955e-02 -3.30568254e-02 1.76159859e-01 7.93958187e-01 5.27847745e-02 7.02033937e-01 -8.32589746e-01 -7.76016295e-01 7.89763391e-01 4.72899705e-01 -7.70242661e-02 -1.37599977e-02 5.33932865e-01 5.41049957e-01 -8.34841728e-02 6.29016042e-01 1.14901042e+00 -1.68304950e-01 -2.50047773e-01 -6.17171288e-01 -1.46720588e-01 -3.79250675e-01 -1.25083315e+00 1.49861574e+00 -2.29145959e-01 6.33258820e-01 -3.40147853e-01 -7.30801642e-01 1.09074485e+00 1.03971303e-01 4.37254339e-01 -1.63716745e+00 1.11509271e-01 1.66107789e-01 4.29029241e-02 -6.08866632e-01 5.25248289e-01 1.30290926e-01 4.56799120e-02 -5.21969572e-02 1.19622096e-01 -1.55934706e-01 3.51973265e-01 -1.83252752e-01 8.69360387e-01 -1.60283059e-01 7.10899949e-01 -2.71227449e-01 9.21789050e-01 -4.20744359e-01 7.25720823e-01 5.18796384e-01 -7.95764923e-01 7.36391127e-01 1.60809457e-01 -2.57357776e-01 -1.21833324e+00 -1.44589424e+00 -3.89841080e-01 5.88372111e-01 7.73007691e-01 -2.82588840e-01 -4.34829623e-01 -1.63542852e-01 -3.93565089e-01 4.41078275e-01 -6.59988344e-01 -2.25943714e-01 -1.32096291e-01 -6.31262004e-01 1.69419408e-01 1.04731619e-01 1.11399150e+00 -1.14996147e+00 -7.73576260e-01 1.28301904e-01 -4.30386424e-01 -1.22767985e+00 -4.00068313e-01 -3.75590503e-01 -7.39640832e-01 -9.86831248e-01 -8.55944157e-01 -5.38559794e-01 2.85380304e-01 3.80218327e-01 1.07392800e+00 -1.33525237e-01 -5.24487019e-01 2.15322137e-01 -5.93448639e-01 1.74063846e-01 -3.35977405e-01 -7.11838484e-01 -6.88240537e-03 1.59115791e-01 3.82467583e-02 -4.92575705e-01 -1.02028441e+00 5.00687778e-01 -9.98254895e-01 1.51363192e-02 8.90550137e-01 8.71111989e-01 8.95631611e-01 4.83216345e-01 5.06178081e-01 -1.62231728e-01 7.26903975e-01 -6.94470182e-02 -3.58522117e-01 2.17995882e-01 -9.67033148e-01 -1.64661244e-01 5.60375273e-01 -3.96968663e-01 -1.07700229e+00 -2.13033900e-01 8.79985094e-03 -1.90872833e-01 -1.44189522e-01 2.80836314e-01 -3.15749258e-01 -3.98299962e-01 6.36587799e-01 7.63613880e-01 4.37099263e-02 -2.07355812e-01 4.77250636e-01 6.37192428e-01 9.70890641e-01 1.50679452e-02 8.41449440e-01 4.92320567e-01 1.68609396e-01 -8.73754740e-01 -3.02658767e-01 -5.37645280e-01 -6.23838902e-01 -4.60101008e-01 8.07224572e-01 -8.63236308e-01 -6.64239585e-01 8.51862907e-01 -8.22898388e-01 2.02291816e-01 -3.13522220e-01 5.99807858e-01 -7.94803619e-01 7.06012130e-01 -4.71817940e-01 -7.27776289e-01 -3.83071214e-01 -1.10504353e+00 7.26605475e-01 6.49444163e-01 1.83669835e-01 -7.61176825e-01 5.82860000e-02 1.56932384e-01 6.61634624e-01 4.50356692e-01 7.79865801e-01 -1.08640492e-01 -2.25964203e-01 4.06877473e-02 -5.00737011e-01 6.65106177e-01 3.59713435e-01 -7.90311918e-02 -6.74058795e-01 -2.42890343e-01 1.17715664e-01 -2.40783945e-01 5.44723809e-01 5.42134881e-01 1.00936735e+00 -4.07905787e-01 2.93719709e-01 6.31585121e-01 1.74725819e+00 4.46712971e-01 1.19537270e+00 5.17157018e-01 2.20199022e-02 1.58808187e-01 9.00424719e-01 5.72844923e-01 3.07425052e-01 6.69852912e-01 2.31466278e-01 -3.17583263e-01 -4.37376350e-01 4.29754481e-02 3.42340648e-01 1.05611348e+00 -1.30213857e-01 -1.18136995e-01 -5.21085918e-01 3.15144509e-01 -1.28329515e+00 -1.13989675e+00 -2.85978504e-02 2.06043887e+00 6.11676097e-01 8.12371448e-03 -1.45201892e-01 6.56795263e-01 6.85302973e-01 3.97757024e-01 -5.33119023e-01 -2.30191752e-01 -6.74122155e-01 7.63760954e-02 3.39590907e-01 9.90442112e-02 -1.13243711e+00 4.54826564e-01 6.35982800e+00 1.10404849e+00 -1.19029117e+00 7.68247843e-02 9.48540688e-01 5.02582729e-01 1.34582534e-01 -3.18739474e-01 8.00835267e-02 7.28405297e-01 1.01250577e+00 -3.15118194e-01 5.56220531e-01 5.96947551e-01 3.66414189e-01 -5.26069343e-01 -3.78370672e-01 1.41479182e+00 3.92621607e-01 -8.79892707e-01 -2.11068094e-01 2.14243941e-02 7.16221750e-01 -3.21176827e-01 6.02326214e-01 -8.58352408e-02 -1.68698743e-01 -9.45319772e-01 6.13788426e-01 8.73889446e-01 9.99866843e-01 -8.42246652e-01 9.05590713e-01 -9.32873338e-02 -1.16917372e+00 -2.26165764e-02 -4.86506581e-01 2.41410837e-01 -7.87937045e-02 5.77441156e-01 5.39475344e-02 8.83060396e-01 1.02287018e+00 8.58808458e-01 -1.11360109e+00 1.26536536e+00 4.29320894e-02 3.01839232e-01 1.47974506e-01 3.61134529e-01 -1.78550765e-01 -2.25622863e-01 3.69049937e-01 1.00739408e+00 5.78258753e-01 3.61932665e-01 -1.91109136e-01 5.43156445e-01 1.54931441e-01 4.93321031e-01 -4.20143843e-01 1.31589338e-01 2.69831955e-01 1.30645132e+00 -8.21146250e-01 -1.73774689e-01 -4.20425415e-01 1.23617911e+00 -4.94138151e-01 3.00620228e-01 -6.83027744e-01 -4.92646933e-01 2.78223991e-01 -1.21254653e-01 2.59646267e-01 -1.34572923e-01 -9.58985910e-02 -1.06338370e+00 4.28043976e-02 -1.01864588e+00 1.46036163e-01 -1.40668523e+00 -1.47207594e+00 7.36439645e-01 -1.92448542e-01 -1.84903681e+00 -2.94887237e-02 -4.20877904e-01 -4.27352637e-01 8.90606403e-01 -1.83501923e+00 -8.80881011e-01 -6.50087476e-01 8.60844970e-01 2.71460980e-01 -3.04634333e-01 6.80823624e-01 2.20496818e-01 -1.10032387e-01 4.09182578e-01 4.84837323e-01 6.51000589e-02 7.99053073e-01 -9.82578814e-01 1.35807842e-01 9.22229290e-01 2.45042518e-02 5.07560596e-02 8.02617610e-01 -3.87074679e-01 -1.24417937e+00 -8.26002598e-01 4.12550777e-01 2.86132932e-01 4.61470932e-01 3.09135526e-01 -8.36399555e-01 -3.67666572e-01 4.79196310e-01 5.56159616e-01 5.86419284e-01 -6.01649702e-01 -2.64171749e-01 -3.92897189e-01 -1.45611346e+00 2.25473717e-01 6.19135678e-01 -4.95263159e-01 -3.39157462e-01 -2.25353524e-01 4.19443488e-01 -4.71268706e-02 -1.34801519e+00 4.86765981e-01 6.44404471e-01 -1.47962964e+00 1.27805066e+00 3.18307281e-01 3.19135517e-01 -5.53436935e-01 -5.09752393e-01 -1.44661438e+00 -5.97787082e-01 -2.36497939e-01 -5.03631569e-02 1.09337103e+00 -2.15936631e-01 -4.82384294e-01 1.79565683e-01 -9.45597515e-02 2.32492715e-01 -4.08354789e-01 -1.02232420e+00 -9.67100918e-01 -2.33251393e-01 -7.92201161e-02 4.25422460e-01 7.45870948e-01 -1.77031353e-01 2.68833227e-02 -5.65569460e-01 3.38503495e-02 9.08992231e-01 8.12736303e-02 3.70987356e-01 -1.36230671e+00 -1.09672152e-01 -3.92942965e-01 -1.08925521e+00 -5.41465580e-01 -2.40331367e-01 -4.45991307e-01 -5.89627735e-02 -1.42902684e+00 3.63609195e-01 -1.01503044e-01 -8.30150306e-01 -8.30692425e-02 -2.40853399e-01 7.64829397e-01 4.00106847e-01 3.44807386e-01 -7.53072202e-01 8.80865693e-01 1.62424684e+00 -2.66467810e-01 7.73396045e-02 -3.97190571e-01 -5.23583472e-01 6.03215039e-01 6.99287772e-01 -1.44604683e-01 -3.08934420e-01 1.97154298e-01 -1.52030781e-01 3.44779730e-01 4.88166302e-01 -1.52900147e+00 -1.07089104e-02 -1.86839864e-01 8.81649911e-01 -6.31633341e-01 3.69579256e-01 -6.59440875e-01 1.43883109e-01 6.09297156e-01 -1.90640673e-01 3.12643826e-01 -2.58168932e-02 6.06454015e-01 -6.20281637e-01 2.18744546e-01 1.36672759e+00 1.01357304e-01 -1.17506576e+00 5.73060811e-02 -2.75236517e-01 7.81240836e-02 1.01791513e+00 -4.44327921e-01 -6.10597253e-01 -3.53753418e-01 -4.60485309e-01 -4.37504858e-01 6.76522255e-01 3.46752316e-01 1.05125701e+00 -1.60328031e+00 -8.58024895e-01 2.60084778e-01 3.64736259e-01 -9.31975782e-01 6.91243112e-01 8.45179558e-01 -5.32303512e-01 2.74330825e-01 -9.97659326e-01 -5.34559548e-01 -1.15645933e+00 7.46168256e-01 9.04857591e-02 -2.55768806e-01 -5.71350098e-01 4.32644598e-02 -3.66364010e-02 8.69287327e-02 -9.93060097e-02 -5.53358160e-02 -5.15781403e-01 -1.17500968e-01 7.58570850e-01 4.79766130e-01 7.52697811e-02 -1.28100932e+00 -3.18515658e-01 8.20167840e-01 4.16270673e-01 -2.03695282e-01 1.12392163e+00 -7.40499139e-01 -2.65118796e-02 4.57546353e-01 1.36809027e+00 -1.53334081e-01 -1.04819608e+00 -3.28735918e-01 -1.09378390e-01 -9.98002529e-01 3.12105924e-01 -9.95623052e-01 -1.16691458e+00 8.39628518e-01 1.71418023e+00 2.76049435e-01 1.90268171e+00 -3.14448535e-01 6.77347422e-01 2.45514829e-02 4.13220882e-01 -1.12014413e+00 5.87867439e-01 7.37736225e-02 9.34526503e-01 -1.37123024e+00 1.07858144e-01 -1.30534738e-01 -6.75799012e-01 1.03324664e+00 4.30707186e-01 4.50731767e-03 6.03706539e-01 -9.22355875e-02 7.63955340e-02 2.77057469e-01 -4.25965130e-01 -3.37458521e-01 5.61297536e-01 9.23728883e-01 1.49290502e-01 -1.16276547e-01 -4.85119700e-01 3.70905191e-01 -8.63718390e-02 1.89916044e-01 6.32544816e-01 6.07165933e-01 -5.58386922e-01 -6.22408986e-01 -6.04848087e-01 3.24791163e-01 -5.05367875e-01 -8.17816928e-02 2.18094215e-01 6.30897284e-01 2.44866058e-01 1.28994679e+00 -4.59549539e-02 -7.35291779e-01 1.70295417e-01 -3.72866243e-01 4.57929134e-01 3.17467034e-01 -1.36967227e-01 5.10321371e-02 -3.55314374e-01 -7.78394222e-01 -7.72337496e-01 -4.01453674e-01 -9.03320730e-01 -3.39050621e-01 -1.02590293e-01 -7.72911385e-02 7.08515406e-01 5.16612649e-01 2.32692868e-01 4.86263245e-01 9.89945233e-01 -7.48484254e-01 -2.39561382e-03 -1.01624286e+00 -9.86173928e-01 6.58176601e-01 2.19044626e-01 -7.21791804e-01 -3.63805592e-01 4.76013392e-01]	[11.72169303894043, -1.9646824598312378]
aea21f14-5c89-45bd-b4d2-91cb7343796c	end-to-end-face-swapping-via-adaptive-latent	2303.04186	null	https://arxiv.org/abs/2303.04186v1	https://arxiv.org/pdf/2303.04186v1.pdf	End-to-end Face-swapping via Adaptive Latent Representation Learning	Taking full advantage of the excellent performance of StyleGAN, style transfer-based face swapping methods have been extensively investigated recently. However, these studies require separate face segmentation and blending modules for successful face swapping, and the fixed selection of the manipulated latent code in these works is reckless, thus degrading face swapping quality, generalizability, and practicability. This paper proposes a novel and end-to-end integrated framework for high resolution and attribute preservation face swapping via Adaptive Latent Representation Learning. Specifically, we first design a multi-task dual-space face encoder by sharing the underlying feature extraction network to simultaneously complete the facial region perception and face encoding. This encoder enables us to control the face pose and attribute individually, thus enhancing the face swapping quality. Next, we propose an adaptive latent codes swapping module to adaptively learn the mapping between the facial attributes and the latent codes and select effective latent codes for improved retention of facial attributes. Finally, the initial face swapping image generated by StyleGAN2 is blended with the facial region mask generated by our encoder to address the background blur problem. Our framework integrating facial perceiving and blending into the end-to-end training and testing process can achieve high realistic face-swapping on wild faces without segmentation masks. Experimental results demonstrate the superior performance of our approach over state-of-the-art methods.	['Qian Li', 'Chao Shen', 'Pengbin Hu', 'Chenhao Lin']	2023-03-07	null	null	null	null	['face-swapping']	['computer-vision']	[ 5.02206028e-01 -8.48869141e-03 -1.39281359e-02 -5.47992349e-01 -5.40769279e-01 -5.94284177e-01 2.08099797e-01 -1.02068913e+00 -3.86203304e-02 4.78558451e-01 -4.78136130e-02 9.27841440e-02 1.17510721e-01 -6.69995904e-01 -7.15477288e-01 -9.72360253e-01 2.70248502e-01 1.69577569e-01 -1.08192548e-01 -2.81941444e-02 -3.37130949e-02 5.29712200e-01 -1.79811037e+00 4.11002547e-01 1.15041780e+00 1.06366706e+00 2.79214293e-01 4.38357621e-01 -1.32807910e-01 2.20959336e-01 -4.31273580e-01 -4.74047929e-01 6.27577066e-01 -7.56734073e-01 -4.76127386e-01 4.02877748e-01 8.08789015e-01 -6.16407096e-01 -2.24793062e-01 1.15951204e+00 6.89784348e-01 -4.25597169e-02 3.01413924e-01 -1.41349769e+00 -8.84239495e-01 1.02268815e-01 -8.07227910e-01 -3.25431585e-01 3.37937415e-01 5.31247616e-01 5.83924294e-01 -9.79214907e-01 4.39406842e-01 1.62780893e+00 4.97474194e-01 1.03036904e+00 -1.27451873e+00 -1.50117159e+00 8.65443349e-02 -1.88409239e-02 -1.47165668e+00 -9.24737215e-01 9.57832813e-01 -2.48077497e-01 1.51728526e-01 3.05700332e-01 6.63959086e-01 1.07299232e+00 -6.88080564e-02 6.06947362e-01 1.25666475e+00 -1.92061007e-01 -5.12780510e-02 5.77503741e-02 -7.44194090e-01 1.08944166e+00 -1.40269458e-01 1.21277556e-01 -5.42731643e-01 -1.86420336e-01 1.20876777e+00 1.47957176e-01 -5.67195415e-01 -4.15059119e-01 -8.27993333e-01 5.84841073e-01 3.78094107e-01 -1.11964196e-01 -2.14749068e-01 2.01518759e-01 1.14620849e-01 3.55021775e-01 4.30908412e-01 -8.68732631e-02 -5.40057778e-01 2.68385112e-01 -1.12555349e+00 1.01544984e-01 3.75789046e-01 1.02760851e+00 7.76263952e-01 2.22455356e-02 -4.69930887e-01 1.10312355e+00 5.35297036e-01 5.54286301e-01 2.62784988e-01 -1.21182656e+00 2.63287127e-01 3.73639882e-01 -9.42947119e-02 -8.34467292e-01 1.56470343e-01 -2.70712823e-01 -7.37474799e-01 4.01418686e-01 1.69649407e-01 -1.84955031e-01 -1.20372355e+00 1.96817577e+00 4.92237598e-01 5.01904130e-01 -2.01486707e-01 8.22453678e-01 5.75281560e-01 5.86174309e-01 1.01743326e-01 -4.77174759e-01 1.48607504e+00 -1.07551706e+00 -9.15874004e-01 -1.54541552e-01 1.55167609e-01 -8.81382823e-01 1.10428262e+00 7.43316486e-02 -1.08838248e+00 -7.66661704e-01 -8.36688161e-01 -8.05567503e-02 7.37197623e-02 3.14143509e-01 5.00213385e-01 8.22589517e-01 -1.09025311e+00 3.60183209e-01 -5.91806650e-01 -1.48056503e-02 1.01841462e+00 8.10387552e-01 -5.51938713e-01 -8.44821706e-02 -9.76111293e-01 2.82882273e-01 1.96675569e-01 3.10785651e-01 -9.42430258e-01 -7.41856098e-01 -8.49336445e-01 1.02535084e-01 4.48229223e-01 -9.06854689e-01 9.05513525e-01 -1.43762743e+00 -1.94994247e+00 9.58532512e-01 -1.84391707e-01 8.70248154e-02 5.80374360e-01 -2.08621070e-01 -2.63510793e-01 1.47042617e-01 1.35937989e-01 1.13163948e+00 1.44708729e+00 -1.37046015e+00 -3.98746490e-01 -4.09503579e-01 -2.97381431e-01 2.62368202e-01 -4.94325876e-01 1.36452928e-01 -8.34892154e-01 -8.51350248e-01 -1.22341299e-02 -1.03203642e+00 1.74289271e-01 5.63314617e-01 7.91828427e-03 2.84743123e-02 1.18414223e+00 -9.01261628e-01 8.70645523e-01 -2.50250149e+00 2.71945536e-01 9.07823518e-02 9.42437425e-02 4.64350998e-01 -4.76830095e-01 -2.50445336e-01 -3.41985852e-01 -5.99897392e-02 -5.12182653e-01 -5.88119805e-01 -2.65822977e-01 2.17208803e-01 -2.58676618e-01 5.82140505e-01 3.96911114e-01 9.70329821e-01 -7.26522565e-01 -6.57872379e-01 9.35765430e-02 8.34314227e-01 -8.95624995e-01 5.31512916e-01 -1.74287304e-01 7.81703949e-01 -2.90786684e-01 8.77091408e-01 1.22816205e+00 2.00112425e-02 1.75992414e-01 -3.67321640e-01 1.56317592e-01 -2.73918957e-01 -9.80197251e-01 1.82555652e+00 -4.26455706e-01 3.87158364e-01 4.03605580e-01 -3.72807890e-01 1.00245273e+00 2.22467422e-01 3.53905678e-01 -5.75211287e-01 1.19937472e-01 2.17425510e-01 -1.67403996e-01 -4.68048275e-01 9.38414708e-02 -1.90955862e-01 2.51615852e-01 2.84526616e-01 1.78861588e-01 4.58379388e-02 -4.17162746e-01 -1.88875839e-01 4.97429073e-01 5.78977823e-01 -1.03408799e-01 -1.15194201e-01 7.18482137e-01 -8.29760790e-01 8.26460302e-01 7.09967641e-03 -2.13773921e-01 8.95171106e-01 5.32211959e-01 -1.95797980e-01 -8.57166231e-01 -8.65901053e-01 -6.39046803e-02 1.25928557e+00 9.17415544e-02 -1.37293816e-01 -1.27108037e+00 -9.22300577e-01 -1.03590794e-01 3.83937716e-01 -7.35068738e-01 -2.49416366e-01 -7.30237186e-01 -5.02494693e-01 5.95730066e-01 3.71854335e-01 9.63009655e-01 -1.10392737e+00 -3.66521865e-01 -1.58963487e-01 -2.61295319e-01 -9.26101327e-01 -1.03264809e+00 -2.86528409e-01 -6.83205426e-01 -9.13810909e-01 -7.27118790e-01 -1.00993121e+00 9.17353928e-01 3.07002097e-01 5.86082995e-01 3.18737507e-01 -2.02387959e-01 1.31071165e-01 -1.22942686e-01 1.38611093e-01 -3.35185558e-01 -5.12723066e-02 1.75105352e-02 5.45026779e-01 -8.20896626e-02 -7.32668221e-01 -9.18153822e-01 5.35305798e-01 -1.04168427e+00 2.16432840e-01 7.38223851e-01 1.01162910e+00 4.64239031e-01 -1.15194723e-01 3.98779333e-01 -9.57693458e-01 1.64370492e-01 -2.24103138e-01 -6.59343898e-01 4.13114548e-01 -4.68301922e-01 1.43546918e-02 5.03660023e-01 -4.85044241e-01 -1.33109653e+00 2.95837969e-01 -1.91104963e-01 -8.95896077e-01 -6.54559359e-02 -3.40919733e-01 -8.66227329e-01 -4.41554725e-01 1.84154272e-01 3.09220552e-01 4.44429070e-01 -3.78775388e-01 5.73970020e-01 7.10480630e-01 6.17019355e-01 -6.05510116e-01 9.37254429e-01 4.37977821e-01 -2.58856356e-01 -4.33287591e-01 -5.83186448e-01 5.73275536e-02 -6.97105050e-01 -1.31264105e-01 8.87605906e-01 -1.04239714e+00 -8.60818863e-01 7.00498641e-01 -1.19579101e+00 -2.37105891e-01 -1.47806868e-01 -8.85387212e-02 -5.86558461e-01 3.44891667e-01 -3.65061224e-01 -6.91866219e-01 -2.74048895e-01 -1.37851918e+00 1.41921890e+00 3.72019351e-01 1.15330003e-01 -6.00784540e-01 -3.13374341e-01 6.04775131e-01 4.02370811e-01 2.44591996e-01 7.09213138e-01 4.58074249e-02 -7.76229680e-01 2.84111977e-01 -4.37074274e-01 3.21258932e-01 4.71351981e-01 -1.85486987e-01 -1.23819244e+00 -6.42471492e-01 9.19375643e-02 -1.71158925e-01 9.06294763e-01 9.17794704e-02 1.51612329e+00 -4.36527640e-01 -4.18016881e-01 1.17255557e+00 1.09819031e+00 2.34429687e-01 8.34496498e-01 -7.65331089e-02 1.02309918e+00 8.46679449e-01 5.90626478e-01 2.33614907e-01 1.49517218e-02 7.85827279e-01 3.96675557e-01 -2.12452829e-01 -4.33124453e-01 -3.99015516e-01 5.87241352e-01 3.37759584e-01 6.63234442e-02 -2.01517809e-02 -4.32639390e-01 2.63233751e-01 -1.59128654e+00 -8.83229017e-01 5.17584264e-01 2.05418134e+00 1.14830148e+00 -3.23253721e-01 -3.17045599e-02 -2.17715889e-01 1.00045872e+00 1.57154575e-01 -7.15599418e-01 2.34442521e-02 -3.05292606e-02 3.94271553e-01 3.72816026e-01 4.55539882e-01 -9.53515589e-01 1.15125871e+00 5.81082344e+00 1.07920933e+00 -1.17245054e+00 3.14754307e-01 9.94051039e-01 -1.56530023e-01 -5.26064634e-01 -7.90545493e-02 -7.81175613e-01 6.89345360e-01 4.97292131e-01 3.78928632e-01 7.34896958e-01 5.59003472e-01 -6.11876398e-02 2.47467965e-01 -9.67783511e-01 1.28149188e+00 2.92212367e-01 -9.77175891e-01 2.20410943e-01 2.01333925e-01 7.72930503e-01 -6.35342360e-01 5.69011748e-01 -1.63811515e-03 -1.15401946e-01 -1.16334033e+00 7.68285632e-01 4.12213027e-01 1.61766553e+00 -8.43935430e-01 4.22050267e-01 -2.67806023e-01 -1.23198688e+00 -2.92769730e-01 -8.34969580e-02 4.36291128e-01 -1.00992300e-01 1.33715957e-01 -4.87948835e-01 3.10952574e-01 5.76138854e-01 5.00903249e-01 -5.71290672e-01 4.94251311e-01 -2.55344301e-01 4.31118220e-01 -9.22253206e-02 6.27784550e-01 -1.40004888e-01 -3.44671190e-01 5.32565296e-01 8.71431172e-01 4.04888898e-01 1.42462149e-01 1.02922227e-02 1.08261693e+00 -4.03048366e-01 -7.80892298e-02 -4.75363553e-01 1.62591368e-01 5.95841050e-01 1.31716061e+00 -6.60763085e-01 3.10576037e-02 -2.61048555e-01 1.52116156e+00 1.96704328e-01 4.29281175e-01 -1.10548782e+00 -1.58834681e-01 9.26015794e-01 1.99398518e-01 5.52634716e-01 3.25203910e-02 -1.81358084e-01 -1.02742445e+00 8.18800628e-02 -1.00760877e+00 1.93687052e-01 -5.63758671e-01 -1.17825067e+00 6.77963555e-01 -4.03361488e-03 -1.08656752e+00 1.14839040e-01 -4.38751072e-01 -4.96724844e-01 1.03539181e+00 -1.51337838e+00 -1.54033029e+00 -4.69416797e-01 6.64885819e-01 7.01945603e-01 -4.75870878e-01 6.35975897e-01 3.25162292e-01 -6.98354542e-01 1.10510564e+00 -2.29844123e-01 1.58307031e-01 9.63421583e-01 -7.55272686e-01 3.13960850e-01 7.32617438e-01 -2.18461588e-01 7.23704159e-01 4.00306195e-01 -7.75758147e-01 -1.30857468e+00 -1.32909036e+00 2.24619210e-01 -2.42058977e-01 -1.33349905e-02 -6.13489687e-01 -9.95506346e-01 5.46034753e-01 3.38221312e-01 3.28381449e-01 7.15496957e-01 -3.11492920e-01 -4.18971717e-01 -3.98453802e-01 -1.41034722e+00 7.03673244e-01 1.36686528e+00 -6.67884827e-01 -1.37666658e-01 6.87215775e-02 7.82200038e-01 -3.42286736e-01 -4.13419664e-01 5.19242525e-01 7.45723724e-01 -8.79049540e-01 9.50822055e-01 -1.48296610e-01 3.89584601e-01 -5.82534194e-01 5.81714734e-02 -1.01237261e+00 -3.73787016e-01 -1.07959270e+00 2.46945582e-03 1.67790627e+00 -7.24439323e-02 -6.98040843e-01 8.62652600e-01 5.29877126e-01 4.08055149e-02 -7.95787394e-01 -9.87639368e-01 -3.46782148e-01 -1.58310831e-01 2.09777921e-01 9.82886553e-01 9.08076763e-01 -7.99605846e-01 1.20847777e-01 -5.95091760e-01 2.18545184e-01 7.33837843e-01 2.47145236e-01 7.16305315e-01 -9.15845335e-01 -3.20549309e-01 -2.82990694e-01 -1.68677375e-01 -1.08840048e+00 4.68107164e-01 -7.92119741e-01 5.78365326e-02 -7.57566392e-01 1.73852310e-01 -6.43362641e-01 -1.28759101e-01 7.90498137e-01 -3.50009590e-01 6.47988141e-01 2.16932341e-01 2.38975421e-01 -3.05953711e-01 9.11471784e-01 1.58359015e+00 -5.72224036e-02 -1.91935271e-01 -3.57864887e-01 -8.21491659e-01 5.69855511e-01 5.23516774e-01 -4.05100644e-01 -5.64662039e-01 -4.72787231e-01 -1.73032492e-01 1.47916108e-01 4.78189170e-01 -8.17023516e-01 1.07107088e-01 -3.11518401e-01 7.55650699e-01 -1.58532098e-01 4.24195260e-01 -9.55640554e-01 3.57767940e-01 4.06961143e-01 -1.51904538e-01 -1.38493225e-01 3.20330054e-01 6.44536018e-01 -4.45294939e-02 1.44111216e-01 1.17271721e+00 6.93474337e-02 -5.57554841e-01 7.22616792e-01 2.69340992e-01 -2.75457889e-01 1.23200595e+00 -4.34130043e-01 8.16544443e-02 -1.29696697e-01 -4.54446316e-01 1.39362708e-01 7.58234262e-01 5.76285362e-01 8.66390228e-01 -1.51419997e+00 -7.88864732e-01 9.76796567e-01 -7.56117329e-02 5.66072352e-02 4.03756708e-01 5.80816627e-01 -5.93958020e-01 -1.97781384e-01 -6.98449790e-01 -5.74503601e-01 -1.50432527e+00 5.17253458e-01 4.10016418e-01 2.57802010e-01 -3.73632014e-01 1.14703083e+00 6.53642237e-01 -3.15888703e-01 -6.30280003e-02 2.67771333e-01 -3.82545330e-02 2.50085723e-02 5.26246488e-01 1.20977275e-01 -3.05244684e-01 -7.47862279e-01 -2.87822872e-01 8.82147074e-01 -2.17059270e-01 -2.70473547e-02 1.22129393e+00 -3.83735299e-01 -3.93250018e-01 -4.81709540e-02 1.29148793e+00 1.99434593e-01 -1.83652818e+00 -3.01708039e-02 -7.02432156e-01 -1.06037331e+00 -1.05599977e-01 -6.28426194e-01 -1.52596486e+00 7.65101075e-01 1.06209004e+00 -5.10326743e-01 1.57849240e+00 -1.64551362e-01 1.03915846e+00 -3.23276669e-01 3.49944621e-01 -7.47112215e-01 1.48853928e-01 -4.17181570e-03 9.37208414e-01 -1.15842521e+00 -1.83308244e-01 -8.58638883e-01 -6.01538002e-01 1.01100802e+00 8.92169595e-01 8.48651677e-02 4.37388033e-01 2.43754402e-01 -5.16635692e-03 -3.56559418e-02 -4.45653468e-01 1.71135515e-01 2.90118515e-01 5.76877475e-01 2.17838123e-01 -1.62539240e-02 1.20405860e-01 3.21605444e-01 -7.96318203e-02 2.12389138e-02 -5.65038025e-02 5.78586996e-01 -1.35411531e-01 -1.36656177e+00 -5.38901269e-01 1.30155668e-01 -3.59470993e-01 -4.70741168e-02 -1.36515826e-01 2.34328300e-01 7.23649681e-01 5.21188140e-01 1.17334902e-01 -3.47090244e-01 6.17882982e-02 2.04590634e-01 7.71744788e-01 -5.93140662e-01 -4.21450585e-01 1.79737791e-01 -4.43242520e-01 -5.62520146e-01 -3.28412205e-01 -6.50314867e-01 -9.90604937e-01 -3.40089709e-01 -4.27528799e-01 -6.53954819e-02 2.70999253e-01 7.34308243e-01 6.17786467e-01 5.09002149e-01 9.76504505e-01 -8.33308399e-01 -2.78741837e-01 -7.06630230e-01 -4.25000221e-01 3.74887228e-01 4.99988526e-01 -8.23388457e-01 -7.23545924e-02 3.87803108e-01]	[12.687067031860352, -0.018864108249545097]
58dfbd3d-a926-4fb4-9666-3e5d8af72a42	reactive-and-safe-road-user-simulations-using	2109.06689	null	https://arxiv.org/abs/2109.06689v1	https://arxiv.org/pdf/2109.06689v1.pdf	Reactive and Safe Road User Simulations using Neural Barrier Certificates	Reactive and safe agent modelings are important for nowadays traffic simulator designs and safe planning applications. In this work, we proposed a reactive agent model which can ensure safety without comprising the original purposes, by learning only high-level decisions from expert data and a low-level decentralized controller guided by the jointly learned decentralized barrier certificates. Empirical results show that our learned road user simulation models can achieve a significant improvement in safety comparing to state-of-the-art imitation learning and pure control-based methods, while being similar to human agents by having smaller errors to the expert data. Moreover, our learned reactive agents are shown to generalize better to unseen traffic conditions, and react better to other road users and therefore can help understand challenging planning problems pragmatically.	['Chuchu Fan', 'Zengyi Qin', 'Yue Meng']	2021-09-14	null	null	null	null	['user-simulation']	['natural-language-processing']	[-4.12243545e-01 9.23994839e-01 -3.26367468e-01 5.21614328e-02 -9.20969367e-01 -3.15230459e-01 7.37582505e-01 -1.08688250e-01 -5.65681100e-01 1.40145552e+00 -4.54583913e-02 -5.12851238e-01 -2.50608474e-01 -1.00845635e+00 -7.12075531e-01 -8.04457664e-01 -4.58531052e-01 1.04695725e+00 9.29295242e-01 -8.58745337e-01 -5.13639078e-02 6.58586502e-01 -1.56837857e+00 -3.56731385e-01 1.13567615e+00 4.19414133e-01 -1.19588889e-01 8.16038251e-01 6.69248164e-01 1.22806776e+00 -3.44275981e-01 3.66244242e-02 3.77323061e-01 4.23084572e-02 -4.90805626e-01 -1.14962749e-01 -3.60065997e-02 -6.84079349e-01 -6.59696460e-01 7.83088148e-01 4.26058322e-01 5.61878860e-01 5.77302277e-01 -1.62099457e+00 5.41784465e-02 4.85492945e-01 -7.10244989e-03 -1.87783808e-01 2.92596221e-01 1.08436763e+00 5.47117829e-01 1.44397497e-01 5.78836381e-01 1.47925103e+00 4.14718568e-01 1.12398601e+00 -1.21504712e+00 -5.14986157e-01 5.84048569e-01 3.73612136e-01 -1.18886054e+00 -3.61953288e-01 3.28903705e-01 -3.71819943e-01 1.01852500e+00 1.61791220e-01 6.04582310e-01 1.27971566e+00 3.90118778e-01 6.22012973e-01 1.04698730e+00 6.05604164e-02 5.76563299e-01 2.45196685e-01 -1.63343757e-01 8.23842645e-01 1.10434413e-01 9.56856728e-01 1.26707077e-01 -1.31623745e-01 4.18965369e-01 -5.18323362e-01 9.97200422e-03 -5.45104146e-01 -9.82378244e-01 8.61684203e-01 3.37202907e-01 -2.37116456e-01 -7.65502512e-01 4.91415113e-01 3.91125411e-01 4.03023988e-01 8.09781477e-02 2.62260318e-01 -3.95406723e-01 -2.74975747e-01 -2.09640682e-01 8.16222370e-01 1.15779734e+00 1.01334453e+00 6.47353709e-01 4.90821600e-01 -1.97265089e-01 1.83443755e-01 3.41020495e-01 9.61578190e-01 -1.99080542e-01 -1.70826411e+00 4.04874831e-01 3.30284476e-01 6.94983602e-01 -6.41851068e-01 -8.10801089e-01 3.01250219e-02 -4.94700462e-01 9.88878489e-01 2.99396485e-01 -6.40385151e-01 -5.49444795e-01 1.71673810e+00 4.80450213e-01 5.10048687e-01 3.92521799e-01 8.00545514e-01 1.23652043e-02 7.20257223e-01 2.45821416e-01 -2.40276158e-01 8.22254360e-01 -8.79925549e-01 -5.16945720e-01 -2.14483455e-01 7.96290338e-01 9.49777439e-02 7.28075266e-01 5.12871265e-01 -1.20367670e+00 -4.19136018e-01 -8.52597952e-01 5.35115600e-01 -3.90798748e-01 -4.98520195e-01 2.33582810e-01 8.18843365e-01 -1.27158606e+00 5.60370624e-01 -8.42183590e-01 -3.48028719e-01 3.08811575e-01 4.92038846e-01 6.50938600e-02 2.62699336e-01 -1.39655900e+00 1.52432656e+00 2.27420107e-01 -5.71328662e-02 -1.72460008e+00 -8.51459742e-01 -8.72198462e-01 -1.95416883e-01 1.08835649e+00 -7.01160431e-01 1.62617481e+00 -2.85446584e-01 -2.25714564e+00 1.74484134e-01 2.60795593e-01 -1.04280186e+00 1.00156856e+00 -1.60800532e-01 -2.97830075e-01 1.30254447e-01 -5.24889724e-03 7.01898813e-01 5.32962143e-01 -1.49953210e+00 -9.83355999e-01 2.09947243e-01 5.04742324e-01 2.28415236e-01 3.17409664e-01 -3.80546063e-01 1.48736551e-01 1.51908219e-01 -9.97880161e-01 -1.22459197e+00 -9.45992768e-01 1.55169234e-01 -1.12714730e-01 -3.69030923e-01 8.26340854e-01 -1.98418081e-01 8.18713844e-01 -1.58205652e+00 1.74162954e-01 4.69286472e-01 2.74385124e-01 6.40450001e-01 -2.88278520e-01 7.36797154e-01 5.09797692e-01 -1.35043696e-01 1.91219434e-01 1.21474989e-01 3.44560325e-01 4.87381905e-01 -4.58960533e-01 5.37412941e-01 -6.75906688e-02 7.74505973e-01 -1.34902489e+00 -4.46596205e-01 7.12302983e-01 2.24251851e-01 -5.26383936e-01 2.63704270e-01 -5.57903051e-01 7.94047832e-01 -9.45191443e-01 -8.00689831e-02 3.03997993e-01 4.20040160e-01 1.44230053e-01 5.61002135e-01 -4.36572254e-01 1.03280254e-01 -1.06966078e+00 8.69971693e-01 -7.45394826e-01 5.61113179e-01 5.11726201e-01 -8.09414804e-01 6.28603697e-01 5.92249990e-01 5.43784142e-01 -9.84704196e-01 4.16190863e-01 1.51240462e-02 5.64369112e-02 -6.04081392e-01 2.25005895e-01 -1.09092575e-02 -2.24148169e-01 3.68707865e-01 -6.47520125e-01 -5.34387052e-01 1.18956380e-01 2.10691944e-01 1.16199541e+00 3.93709727e-02 1.06378771e-01 -2.51335263e-01 1.01918471e+00 3.18615288e-01 6.14089966e-01 1.00782871e+00 -6.98931992e-01 -4.02733803e-01 5.73828101e-01 -4.09248233e-01 -8.49942029e-01 -9.75640297e-01 5.66944778e-01 8.98320675e-01 4.70862597e-01 -1.51218073e-02 -8.73497367e-01 -7.48601556e-01 1.89962044e-01 1.29689765e+00 -5.55223763e-01 -4.61622417e-01 -1.03133464e+00 1.14105880e-01 5.70040524e-01 4.41050351e-01 4.52634037e-01 -8.60265791e-01 -7.61561036e-01 5.10261834e-01 1.42562941e-01 -1.25555742e+00 -2.71643579e-01 -4.27483469e-01 -2.76022702e-01 -1.30908382e+00 -2.15713173e-01 -2.89955407e-01 3.16144884e-01 1.70965642e-01 6.75466478e-01 2.66283333e-01 2.66660601e-01 7.49618351e-01 -1.59089103e-01 -6.44997299e-01 -1.07528126e+00 6.30716607e-02 4.63240921e-01 -1.80643827e-01 -2.12608799e-01 -4.31111574e-01 -4.41293567e-01 6.61679804e-01 -4.27863479e-01 -4.91884947e-02 1.91406026e-01 5.26664197e-01 7.97544792e-02 8.94379467e-02 7.53165960e-01 -5.88756084e-01 9.55505550e-01 -3.31823796e-01 -1.22365868e+00 -3.81374992e-02 -7.50989616e-01 1.02563493e-01 1.06748581e+00 -4.13352609e-01 -1.05325544e+00 -1.38198063e-01 -2.00934872e-01 3.46185863e-02 -5.18842876e-01 -1.86192095e-01 -6.02455158e-03 -3.34770024e-01 7.41501749e-01 -5.67071289e-02 4.84813720e-01 1.06950119e-01 5.50630510e-01 5.70930004e-01 7.86246583e-02 -9.03159320e-01 1.18252969e+00 6.33748829e-01 3.18617910e-01 -8.60176325e-01 -2.78680921e-01 -7.59331286e-02 -4.86667156e-01 -6.52352095e-01 8.37134302e-01 -7.76091099e-01 -1.69770336e+00 4.07107532e-01 -9.38567936e-01 -1.10513735e+00 -5.40420711e-01 3.52237284e-01 -1.25457668e+00 2.01243147e-01 -4.27091032e-01 -1.28850091e+00 1.85132265e-01 -1.35127783e+00 9.11498010e-01 3.25104564e-01 -5.71557879e-03 -1.19822550e+00 4.56867635e-01 8.84827524e-02 6.54817522e-01 3.43359381e-01 5.78901291e-01 -5.14194250e-01 -8.84398580e-01 -1.21084072e-01 2.32346594e-01 6.48778155e-02 -4.13961589e-01 -9.07000005e-02 -7.24232852e-01 -3.81046981e-01 -4.33422565e-01 -3.26028675e-01 2.98533142e-01 2.79440016e-01 5.16469002e-01 -6.55575156e-01 -7.12790608e-01 3.19356434e-02 1.05546057e+00 4.36191082e-01 7.03945637e-01 5.72169900e-01 2.94854790e-01 8.64819467e-01 9.91907299e-01 3.96980792e-01 8.81402850e-01 8.42898130e-01 7.48257935e-01 1.19813196e-01 1.71696559e-01 -2.83541888e-01 6.04116559e-01 5.84863313e-02 -1.95858404e-01 -5.37538901e-02 -1.02586150e+00 5.27954161e-01 -2.47008276e+00 -1.17154980e+00 -1.73809692e-01 2.09003544e+00 5.49352944e-01 4.55469996e-01 6.39715612e-01 -1.80078551e-01 4.34820354e-01 -1.51352137e-01 -6.15299881e-01 -5.03009439e-01 2.91717887e-01 -1.40087232e-01 8.74834955e-01 1.03691733e+00 -6.76264942e-01 1.25186086e+00 7.07391644e+00 8.18761170e-01 -7.87932754e-01 5.53264618e-02 -2.09682509e-02 9.50583294e-02 -5.22415433e-03 7.45671019e-02 -6.77437603e-01 2.45018467e-01 1.45916724e+00 -5.15438735e-01 7.79524326e-01 8.28194976e-01 1.11778951e+00 -2.03786403e-01 -1.00910985e+00 2.28271589e-01 -5.09323657e-01 -1.24925995e+00 -3.41234535e-01 1.76257670e-01 6.84446394e-01 7.23789558e-02 -1.86169013e-01 9.34013546e-01 1.14405835e+00 -8.71879816e-01 7.39855707e-01 7.19199181e-01 1.96667444e-02 -1.03539479e+00 5.89339375e-01 9.12101805e-01 -1.19314516e+00 -4.65082586e-01 -1.29342258e-01 -3.36495340e-01 5.58519900e-01 -2.62652963e-01 -8.00177276e-01 4.37312394e-01 2.23299012e-01 4.83471185e-01 -1.82925478e-01 1.02171254e+00 -3.27492565e-01 5.08812606e-01 -3.76261115e-01 -4.86258209e-01 6.15153074e-01 -1.57103062e-01 9.99731004e-01 6.47831559e-01 -3.89812887e-01 1.12850696e-01 7.19620943e-01 6.82530522e-01 6.35946214e-01 -4.09816504e-01 -1.01775777e+00 4.54971224e-01 3.93203914e-01 9.08547938e-01 -1.40398443e-01 -3.32733393e-01 -3.82300280e-02 2.88702518e-01 2.37139449e-01 6.54734671e-01 -1.27839041e+00 -2.30662599e-01 1.27019477e+00 1.42921656e-01 8.92980993e-02 -5.07422268e-01 9.40431729e-02 -5.80051064e-01 -4.23501521e-01 -9.03064072e-01 4.46015671e-02 -5.45522511e-01 -8.18732381e-01 4.33932066e-01 3.08675200e-01 -1.36234200e+00 -6.93284512e-01 -5.32633603e-01 -7.13114023e-01 4.17755872e-01 -1.73707807e+00 -1.06210363e+00 1.51432995e-02 5.54368854e-01 5.36553919e-01 -3.44993502e-01 5.12501121e-01 -1.49834552e-03 -5.57437241e-01 3.33840996e-01 1.59116127e-02 -1.92657933e-01 3.05251658e-01 -1.05633104e+00 3.64250243e-01 5.83636761e-01 -7.84149766e-01 1.91717044e-01 1.08815086e+00 -6.11406744e-01 -1.51012850e+00 -1.22169316e+00 2.71497250e-01 -6.15832269e-01 9.66579020e-01 -7.45956600e-02 -5.52528918e-01 5.79374552e-01 2.47029543e-01 -3.84601563e-01 -3.05025280e-01 -2.70411968e-01 1.30809978e-01 -3.29056948e-01 -1.33343887e+00 1.25799179e+00 9.91584957e-01 -2.23141223e-01 -2.42738456e-01 3.64736915e-01 7.82527387e-01 -4.52158600e-01 -5.63723266e-01 1.10255614e-01 3.56500059e-01 -6.74113870e-01 8.54190171e-01 -8.84496748e-01 -5.35809577e-01 -4.06926453e-01 2.11631313e-01 -1.59446824e+00 -2.75170445e-01 -1.23156023e+00 -2.16439173e-01 6.98095441e-01 4.41097498e-01 -1.17804575e+00 7.72616982e-01 9.49213684e-01 -2.08031654e-01 -5.26108742e-01 -1.40733433e+00 -1.23702836e+00 4.12945271e-01 -6.67587101e-01 4.93871123e-01 1.45134777e-01 1.31162733e-01 1.68170244e-01 -5.73845088e-01 6.86665416e-01 9.16064143e-01 -5.67699552e-01 1.15379226e+00 -9.90681052e-01 7.19022304e-02 -6.32531285e-01 -4.32852238e-01 -9.10081863e-01 8.74380469e-01 -3.79220486e-01 5.20224214e-01 -1.47444654e+00 -3.93509656e-01 -5.53356528e-01 3.22429240e-01 3.74424011e-01 1.87361941e-01 -4.10198122e-01 2.04987377e-01 -3.33611101e-01 -8.53852630e-01 8.07167828e-01 1.30284882e+00 -2.73804277e-01 -3.72383684e-01 3.28649700e-01 -4.60096031e-01 6.80919290e-01 9.69445348e-01 -4.83147115e-01 -5.98142684e-01 -1.29107639e-01 1.08960196e-02 4.14314687e-01 5.98028958e-01 -1.12951529e+00 5.69499969e-01 -9.80856299e-01 -8.24579597e-01 -2.07255527e-01 3.07446718e-01 -1.17606390e+00 -6.66805804e-02 1.05376470e+00 -3.79509330e-01 -3.25624943e-01 3.10013682e-01 9.39643919e-01 4.15358573e-01 1.63851008e-01 8.83067131e-01 1.22061245e-01 -7.53464341e-01 2.81163752e-01 -1.20086622e+00 1.92827418e-01 1.72389269e+00 -9.21243355e-02 -6.25514328e-01 -8.56351018e-01 -6.49679840e-01 1.12170494e+00 3.97928059e-01 4.75861818e-01 4.88152355e-01 -1.01024747e+00 -7.47569382e-01 -1.56890839e-01 -1.59200907e-01 -2.52808303e-01 1.76518932e-01 9.19487178e-01 -4.15207833e-01 6.13586485e-01 -1.98063686e-01 -4.83476847e-01 -8.71888638e-01 6.47436917e-01 8.01048100e-01 -2.80363470e-01 -7.42192030e-01 9.29184556e-02 -4.77813631e-02 -7.46706903e-01 4.35008466e-01 -2.65917212e-01 -1.07523747e-01 -4.22849178e-01 5.24466991e-01 1.02435684e+00 -2.98061192e-01 -6.11650348e-01 -3.05253685e-01 5.83161533e-01 1.36812016e-01 -4.03294116e-01 1.01927817e+00 -2.52391994e-01 5.41527927e-01 -4.24965099e-03 4.70949739e-01 -2.85876095e-01 -1.73352087e+00 7.60914907e-02 -1.10883554e-02 -1.98280692e-01 -9.41556022e-02 -6.16733015e-01 -7.85184443e-01 4.34178144e-01 5.37566185e-01 3.24352235e-01 4.45450932e-01 -2.63556629e-01 8.31166327e-01 8.30391765e-01 9.70374882e-01 -1.43385363e+00 -4.78050672e-02 7.60037005e-01 7.56621480e-01 -1.16386259e+00 -2.91433305e-01 -3.55884373e-01 -1.02482235e+00 7.76604176e-01 9.34558570e-01 -4.58321184e-01 6.66050136e-01 4.91773784e-01 1.75750583e-01 6.61851987e-02 -1.22709322e+00 -7.41001666e-01 -1.62263155e-01 1.42832065e+00 -6.49130702e-01 5.91119230e-02 -9.11853835e-02 7.65859708e-02 1.85820073e-01 6.96095526e-02 8.51593316e-01 8.69092107e-01 -8.82918477e-01 -1.10039783e+00 -2.46254221e-01 -1.00307077e-01 3.53510767e-01 6.67572558e-01 -1.79744259e-01 1.23447013e+00 -2.88086295e-01 1.33087802e+00 -2.66138047e-01 -2.38761678e-01 9.08461213e-01 -3.62415105e-01 3.26423585e-01 -4.23059940e-01 -5.68778992e-01 -5.30447066e-01 5.64418018e-01 -1.04363954e+00 -9.86698344e-02 -4.99918848e-01 -1.64654827e+00 -7.00110912e-01 -6.51665870e-03 2.75016546e-01 2.62109578e-01 1.07577217e+00 3.03973645e-01 6.25555754e-01 9.93431866e-01 -1.22058690e+00 -1.03722632e+00 -4.03889149e-01 -1.74746603e-01 -1.46020398e-01 7.13851750e-01 -8.17609847e-01 -4.17233765e-01 -4.45614427e-01]	[5.099752426147461, 1.4272388219833374]
3012205c-f329-481d-aaef-e7b604f4000c	revisiting-event-argument-extraction-can-eae	2306.00502	null	https://arxiv.org/abs/2306.00502v1	https://arxiv.org/pdf/2306.00502v1.pdf	Revisiting Event Argument Extraction: Can EAE Models Learn Better When Being Aware of Event Co-occurrences?	Event co-occurrences have been proved effective for event extraction (EE) in previous studies, but have not been considered for event argument extraction (EAE) recently. In this paper, we try to fill this gap between EE research and EAE research, by highlighting the question that ``Can EAE models learn better when being aware of event co-occurrences?''. To answer this question, we reformulate EAE as a problem of table generation and extend a SOTA prompt-based EAE model into a non-autoregressive generation framework, called TabEAE, which is able to extract the arguments of multiple events in parallel. Under this framework, we experiment with 3 different training-inference schemes on 4 datasets (ACE05, RAMS, WikiEvents and MLEE) and discover that via training the model to extract all events in parallel, it can better distinguish the semantic boundary of each event and its ability to extract single event gets substantially improved. Experimental results show that our method achieves new state-of-the-art performance on the 4 datasets. Our code is avilable at https://github.com/Stardust-hyx/TabEAE.	['Buzhou Tang', 'Jingyue Hu', 'Yuxin He']	2023-06-01	null	null	null	null	['event-extraction']	['natural-language-processing']	[ 1.22469805e-01 4.22627449e-01 -7.81578645e-02 -2.40272641e-01 -1.10703766e+00 -6.01718783e-01 7.32595503e-01 3.25040728e-01 -4.85408276e-01 8.72444212e-01 3.26338887e-01 -6.43022656e-01 -1.45908743e-01 -1.12744951e+00 -9.35918748e-01 -3.00562471e-01 -1.62846938e-01 5.95732391e-01 4.25998688e-01 -1.27110347e-01 -7.34937340e-02 1.33590028e-01 -1.57108581e+00 8.52923393e-01 5.59150279e-01 8.32557678e-01 -2.13131145e-01 7.55452931e-01 -5.91693670e-02 1.33016706e+00 -5.86222231e-01 -6.42704487e-01 -1.54803649e-01 -4.29658622e-01 -1.30871189e+00 -4.76335645e-01 -2.32685894e-01 -7.08300993e-02 -2.36697257e-01 6.27757967e-01 4.37583625e-01 -1.25922441e-01 6.45317495e-01 -1.40866339e+00 -1.29609630e-01 1.23043752e+00 -2.72389293e-01 5.59040904e-01 3.37840885e-01 -3.92766386e-01 1.25567603e+00 -9.02855873e-01 8.61818373e-01 1.09873021e+00 6.44809306e-01 2.01401427e-01 -9.71972048e-01 -6.71740472e-01 2.27415681e-01 7.04370260e-01 -1.14256942e+00 -4.41243291e-01 6.47099018e-01 -2.03888699e-01 1.26146019e+00 6.09383345e-01 3.32948714e-01 1.55725253e+00 1.93276778e-02 1.27467573e+00 1.03433645e+00 -5.29689670e-01 2.54515886e-01 -8.50790530e-04 3.29096407e-01 4.18379039e-01 2.37364814e-01 1.22711390e-01 -6.97902322e-01 -2.68442333e-01 4.68207479e-01 -2.36586288e-01 -1.31156400e-01 9.72746387e-02 -1.15170324e+00 9.31710362e-01 7.74333579e-03 3.29266876e-01 -6.32614791e-01 -4.78772186e-02 5.88790298e-01 2.45690212e-01 4.70785737e-01 2.45851308e-01 -9.22909379e-01 -3.32441270e-01 -6.34626806e-01 6.39293432e-01 1.14842296e+00 7.65421212e-01 2.58947283e-01 -2.46381685e-01 -2.40710333e-01 5.44160426e-01 4.07173224e-02 1.81183651e-01 2.31131330e-01 -6.51597023e-01 5.27841032e-01 5.12007654e-01 -1.81422848e-02 -7.76019275e-01 -5.57166040e-01 -3.31736654e-01 -5.92210174e-01 -1.63259208e-01 5.47432125e-01 -4.73366648e-01 -3.82479578e-01 1.66435921e+00 4.42328453e-01 5.30700088e-01 1.99500725e-01 4.59771484e-01 1.01199353e+00 7.97539711e-01 2.99311131e-01 -2.53603220e-01 1.69893253e+00 -7.39261389e-01 -8.02293003e-01 -3.38664144e-01 7.09855020e-01 -5.82618415e-01 6.94953263e-01 4.89914149e-01 -1.22537816e+00 -1.85517177e-01 -8.96433294e-01 5.06010577e-02 -6.68373048e-01 1.01441666e-01 8.74416888e-01 2.58720189e-01 -4.21229899e-01 5.34706473e-01 -9.99053717e-01 -2.00859904e-01 3.95599335e-01 -1.39385909e-02 -1.48510441e-01 3.65327895e-01 -1.76701617e+00 8.81917000e-01 8.17371070e-01 -4.41953614e-02 -5.78569531e-01 -6.82896495e-01 -8.43982220e-01 1.52878359e-01 1.10745430e+00 -6.03183866e-01 1.49352825e+00 -3.81154776e-01 -1.13078284e+00 7.82961607e-01 -2.44575724e-01 -8.53046656e-01 3.68575037e-01 -5.15285373e-01 -7.39618123e-01 1.11057237e-01 1.87041298e-01 1.70402870e-01 4.81251925e-01 -1.03225863e+00 -9.64502275e-01 -2.60009289e-01 1.05973668e-01 -2.26770014e-01 7.08242506e-02 6.25024736e-01 -2.43305877e-01 -8.13565612e-01 -3.15846026e-01 -8.20141733e-01 -6.71355873e-02 -6.86531901e-01 -6.55905366e-01 -6.22109652e-01 4.88834411e-01 -7.46050775e-01 1.63107955e+00 -2.05319738e+00 -1.72835216e-02 2.43106205e-02 3.07625271e-02 2.74451494e-01 2.30458885e-01 6.87584221e-01 -4.25852150e-01 1.82203650e-01 -2.89250314e-01 -2.04055592e-01 1.22754090e-01 3.27523828e-01 -6.50397182e-01 -2.87341066e-02 6.04057729e-01 9.85639334e-01 -9.26518977e-01 -7.05356359e-01 1.14045650e-01 3.71098161e-01 -5.02429247e-01 2.07256496e-01 -3.89514834e-01 1.15827642e-01 -5.64159453e-01 5.36005616e-01 3.67481411e-01 -5.15187442e-01 4.36186731e-01 -1.65680915e-01 -6.95876628e-02 8.00894976e-01 -1.55031765e+00 1.32686102e+00 -1.99400023e-01 4.09732044e-01 -3.66946191e-01 -1.15161586e+00 5.25121450e-01 4.81434286e-01 3.49483281e-01 -5.63534379e-01 2.58259505e-01 2.32863322e-01 -1.87003031e-01 -3.59396130e-01 3.69719952e-01 1.54120550e-01 -4.07642871e-01 3.49063158e-01 6.81735128e-02 4.28532183e-01 6.15423262e-01 3.39978009e-01 1.24639547e+00 2.56538481e-01 6.84994280e-01 6.58518896e-02 5.14584243e-01 1.42169639e-01 6.10121310e-01 9.07917798e-01 2.73133159e-01 3.59371841e-01 7.97721088e-01 -4.31458086e-01 -6.57591403e-01 -1.06933808e+00 -3.30117106e-01 1.04119909e+00 -2.60776818e-01 -9.91367042e-01 -6.46735311e-01 -1.15112722e+00 -2.52634794e-01 1.09929931e+00 -6.33970201e-01 1.27734959e-01 -8.74753594e-01 -1.27414954e+00 8.11781287e-01 8.39472353e-01 3.60038131e-01 -1.33337140e+00 -1.02467477e+00 6.17921293e-01 -6.98251843e-01 -1.12559545e+00 1.50970012e-01 5.32924771e-01 -4.75518912e-01 -1.35607493e+00 -6.07399121e-02 -4.69548702e-01 -7.29728118e-03 -4.51862127e-01 1.51403677e+00 -2.22678572e-01 -2.68502295e-01 3.49416845e-02 -6.37093723e-01 -9.29367542e-01 -4.27002370e-01 2.00591952e-01 -5.37576020e-01 -2.00932488e-01 5.81836820e-01 -6.61233425e-01 -3.82078260e-01 2.11642772e-01 -9.98184502e-01 1.25979796e-01 6.07007384e-01 7.13643253e-01 6.26544833e-01 1.89862415e-01 7.23828971e-01 -1.34312880e+00 4.30588603e-01 -8.61680567e-01 -4.16694134e-01 1.89566091e-01 -6.27233565e-01 2.14334249e-01 4.67604846e-01 -2.87665963e-01 -1.21073925e+00 -2.74162859e-01 -3.91263187e-01 5.95983900e-02 -3.71000677e-01 8.03287089e-01 -3.89720872e-02 8.80189002e-01 5.69894314e-01 3.25242467e-02 -5.71695447e-01 -5.48422575e-01 3.07991713e-01 5.24324000e-01 7.59282053e-01 -7.93556333e-01 5.60067296e-01 5.50658524e-01 -1.10262103e-01 -2.28174120e-01 -1.14124715e+00 -3.44939739e-01 -2.88763434e-01 2.56026872e-02 8.03383470e-01 -9.33590174e-01 -7.63594568e-01 3.00169617e-01 -1.32014751e+00 -3.41263294e-01 -3.24222267e-01 3.50664198e-01 -3.60130250e-01 1.15344353e-01 -8.87026787e-01 -7.17915714e-01 -3.38726640e-01 -6.69929802e-01 1.08405316e+00 1.25008300e-01 -5.69262743e-01 -8.52410376e-01 1.72567979e-01 2.67895386e-02 -4.35684212e-02 5.48447013e-01 9.69759881e-01 -1.27924883e+00 -3.92899960e-01 -7.85048455e-02 -8.54223296e-02 -5.88960610e-02 -2.72929490e-01 -8.51605088e-02 -9.35242176e-01 2.22720727e-01 7.78152887e-03 -5.72566725e-02 8.01300287e-01 2.57744402e-01 1.20774031e+00 -3.82548183e-01 -5.30894995e-01 3.21385920e-01 1.23286748e+00 3.11355591e-01 9.02133405e-01 7.37433016e-01 2.85051823e-01 5.70094109e-01 7.07268715e-01 6.53115630e-01 6.48205459e-01 6.41616046e-01 2.87344784e-01 4.19816412e-02 -2.92936694e-02 -3.12017590e-01 3.63731831e-01 5.30267596e-01 -1.72077090e-01 -5.41973293e-01 -8.93028319e-01 6.79614365e-01 -2.07372046e+00 -9.73971784e-01 -5.51506639e-01 1.81626177e+00 1.05680537e+00 3.94252986e-01 2.07739800e-01 4.29670751e-01 4.20457959e-01 1.54438198e-01 -6.82019144e-02 -2.94895709e-01 -2.47961536e-01 5.54479063e-01 2.45966703e-01 2.45914400e-01 -1.31936586e+00 7.13055551e-01 5.57087755e+00 8.34391057e-01 -6.60069466e-01 5.21373115e-02 6.37436032e-01 4.07374986e-02 -1.89973280e-01 2.40457684e-01 -1.00818229e+00 5.31415582e-01 1.39331901e+00 -1.72821462e-01 1.16897076e-01 6.68234468e-01 -1.69117898e-01 -1.14320181e-01 -1.30800962e+00 7.29442835e-01 -7.37082139e-02 -1.42129946e+00 -5.10157198e-02 -1.12816520e-01 2.19355151e-01 -2.14615405e-01 -2.92341620e-01 7.68332601e-01 5.03211319e-01 -8.54678154e-01 8.07572782e-01 3.74552101e-01 2.29888409e-01 -7.74343431e-01 8.86363447e-01 2.77721435e-01 -1.19639051e+00 -6.46802858e-02 9.33807492e-02 -6.16621152e-02 4.44044322e-01 7.22212851e-01 -1.05844069e+00 1.17975199e+00 8.85788441e-01 5.86331427e-01 -6.63176894e-01 7.56335974e-01 -4.93700087e-01 9.89674091e-01 -3.70467097e-01 1.74698040e-01 -1.95953138e-02 2.10778803e-01 7.85579562e-01 1.33869791e+00 2.28785843e-01 2.85231531e-01 -8.95813853e-02 8.93350244e-01 -6.17807098e-02 3.03348787e-02 -2.63182819e-01 3.28334942e-02 5.10966599e-01 1.12532938e+00 -7.93050170e-01 -6.17125809e-01 -4.26868975e-01 7.17211306e-01 2.76845813e-01 8.35065097e-02 -1.25414968e+00 -4.28278208e-01 1.58809334e-01 4.81582858e-04 5.10824382e-01 3.13942045e-01 -1.10094592e-01 -1.18541121e+00 7.14430735e-02 -9.92644906e-01 1.15127730e+00 -8.64357889e-01 -1.15560961e+00 7.18153894e-01 4.25742418e-01 -8.18230629e-01 -7.44090915e-01 -5.98493695e-01 -5.48689425e-01 4.36275572e-01 -1.40019441e+00 -9.76743817e-01 3.86073887e-02 5.56058645e-01 5.88428795e-01 3.03381443e-01 8.81748140e-01 5.40008366e-01 -7.00047135e-01 4.29661989e-01 -3.81678462e-01 5.47541440e-01 7.52247572e-01 -1.41242850e+00 4.79398161e-01 9.77788627e-01 4.75088865e-01 3.31376374e-01 8.17910492e-01 -7.57653058e-01 -1.23331678e+00 -1.11612320e+00 1.42825937e+00 -9.34756696e-01 8.00414264e-01 -2.70599306e-01 -1.01162207e+00 1.14609480e+00 2.98175514e-01 -2.14906991e-01 5.68420827e-01 4.40025210e-01 -4.74258482e-01 1.70373812e-01 -6.77705348e-01 5.79235733e-01 1.08271587e+00 -3.52416307e-01 -1.06561637e+00 2.61505038e-01 7.11606562e-01 -5.36580265e-01 -1.02421200e+00 7.27533817e-01 2.42869899e-01 -8.99994254e-01 1.19153535e+00 -8.25387478e-01 6.35464132e-01 -1.29270926e-01 1.16133410e-02 -9.78341699e-01 8.93342569e-02 -5.48681319e-01 -5.45101821e-01 1.59988272e+00 7.53212750e-01 -6.79412603e-01 4.02976036e-01 4.06881601e-01 -9.17550102e-02 -7.65899777e-01 -7.41217017e-01 -6.17431402e-01 -3.27694491e-02 -7.96488523e-01 7.61963546e-01 9.07540798e-01 9.96546447e-02 5.70437968e-01 -2.42988497e-01 3.60370666e-01 3.34278703e-01 3.23852867e-01 4.86456126e-01 -1.35036325e+00 -5.16779959e-01 -3.17392796e-01 1.77048177e-01 -5.19326925e-01 2.27392748e-01 -9.81323242e-01 -8.36149305e-02 -1.45089972e+00 2.57410228e-01 -1.27024144e-01 -3.22494298e-01 7.43645430e-01 -4.15371239e-01 -2.06213921e-01 -3.05036269e-02 -1.06655337e-01 -7.98208058e-01 1.93952933e-01 5.38123786e-01 2.56618440e-01 -6.75307810e-02 9.27885100e-02 -6.45567358e-01 8.73300493e-01 7.24417388e-01 -8.04509580e-01 -9.76765752e-02 -5.93917221e-02 6.97019100e-01 3.09813619e-01 6.45380080e-01 -7.27304876e-01 1.76687673e-01 1.31653145e-01 2.45198667e-01 -8.12285006e-01 -8.50803405e-02 -6.02820396e-01 3.81011963e-01 1.30756810e-01 -3.47577691e-01 2.16250017e-01 4.33163404e-01 6.40075862e-01 -3.77257049e-01 -1.69905797e-01 1.53817102e-01 -9.06775296e-02 -7.13107049e-01 -6.47229403e-02 -3.79426777e-01 4.59601402e-01 7.57447779e-01 3.68906081e-01 -3.93181324e-01 -8.08110535e-02 -9.05207098e-01 1.37905404e-01 -1.31726637e-01 3.60777050e-01 2.90587872e-01 -1.13878131e+00 -1.15706182e+00 -7.59449154e-02 3.85171808e-02 1.16596408e-01 2.96437651e-01 8.78636837e-01 3.96729149e-02 3.76199454e-01 2.79863954e-01 -3.18040729e-01 -1.20083153e+00 5.91678262e-01 -7.62920156e-02 -9.94175076e-01 -6.40766323e-01 7.10791111e-01 -8.07049945e-02 -2.80042887e-01 9.47945490e-02 -4.87629056e-01 -4.09352690e-01 3.07637721e-01 5.38348973e-01 4.48021561e-01 2.88721889e-01 -1.35432899e-01 -5.20642877e-01 -9.81618017e-02 -2.40160421e-01 -1.22854143e-01 1.50407696e+00 1.95130840e-01 -7.08544925e-02 4.06236529e-01 8.41696560e-01 2.10970223e-01 -8.59907269e-01 -1.49276108e-01 5.45746088e-01 4.30099331e-02 -2.17050940e-01 -9.46776390e-01 -7.16560960e-01 4.53510433e-01 1.61349595e-01 5.47823846e-01 1.10667551e+00 3.86515170e-01 7.81045198e-01 1.70999169e-01 1.61013618e-01 -8.53002608e-01 -2.24130392e-01 5.23850977e-01 7.76659727e-01 -9.97749150e-01 -3.14529598e-01 -7.26774633e-01 -6.45317495e-01 8.83852601e-01 2.75899768e-01 -1.35592297e-01 6.16055965e-01 5.72331965e-01 -5.04333913e-01 -4.41716969e-01 -1.11686611e+00 -3.34057719e-01 2.85632968e-01 7.56622925e-02 3.64798903e-01 5.72116934e-02 -3.17655742e-01 1.25446916e+00 -2.95583844e-01 1.93507642e-01 3.25849354e-01 1.12030077e+00 -5.16670085e-02 -1.35970891e+00 -2.36866370e-01 4.43204641e-01 -9.85211849e-01 -4.00353611e-01 -2.75834054e-01 1.16913617e+00 8.77408758e-02 1.06033230e+00 -8.31901561e-03 -8.13458636e-02 6.93774879e-01 5.84507704e-01 2.84236968e-01 -4.02236223e-01 -7.34978676e-01 1.84792522e-02 8.30793917e-01 -6.60174310e-01 -4.88352150e-01 -9.72999871e-01 -1.33897567e+00 -3.96493971e-02 -1.10438645e-01 4.38550472e-01 2.51591384e-01 1.00444233e+00 4.64396656e-01 9.65099633e-01 2.13376954e-01 -1.67168543e-01 -3.61806929e-01 -8.10616612e-01 -1.80768043e-01 4.80055749e-01 -7.43348002e-02 -7.04122186e-01 -4.51011419e-01 2.41390109e-01]	[9.125330924987793, 9.144476890563965]
869879dc-287b-4a47-9c83-af1138351c1d	sequential-diagnosis-prediction-with	2109.03069	null	https://arxiv.org/abs/2109.03069v1	https://arxiv.org/pdf/2109.03069v1.pdf	Sequential Diagnosis Prediction with Transformer and Ontological Representation	Sequential diagnosis prediction on the Electronic Health Record (EHR) has been proven crucial for predictive analytics in the medical domain. EHR data, sequential records of a patient's interactions with healthcare systems, has numerous inherent characteristics of temporality, irregularity and data insufficiency. Some recent works train healthcare predictive models by making use of sequential information in EHR data, but they are vulnerable to irregular, temporal EHR data with the states of admission/discharge from hospital, and insufficient data. To mitigate this, we propose an end-to-end robust transformer-based model called SETOR, which exploits neural ordinary differential equation to handle both irregular intervals between a patient's visits with admitted timestamps and length of stay in each visit, to alleviate the limitation of insufficient data by integrating medical ontology, and to capture the dependencies between the patient's visits by employing multi-layer transformer blocks. Experiments conducted on two real-world healthcare datasets show that, our sequential diagnoses prediction model SETOR not only achieves better predictive results than previous state-of-the-art approaches, irrespective of sufficient or insufficient training data, but also derives more interpretable embeddings of medical codes. The experimental codes are available at the GitHub repository (https://github.com/Xueping/SETOR).	['Jing Jiang', 'Sen Wang', 'Tao Shen', 'Guodong Long', 'Xueping Peng']	2021-09-07	null	null	null	null	['sequential-diagnosis']	['medical']	[ 2.27821153e-03 -2.91016921e-02 -3.21347147e-01 -5.03302991e-01 -5.01669526e-01 1.17810667e-02 4.72508669e-02 7.82001436e-01 -1.88776493e-01 4.07973230e-01 5.93384743e-01 -4.52200681e-01 -6.93384230e-01 -7.47030973e-01 -4.25315380e-01 -5.49533725e-01 -5.74281991e-01 7.61825919e-01 -2.05096647e-01 -1.65237486e-02 -2.71691650e-01 5.39268740e-02 -1.22233391e+00 5.48601925e-01 9.53551412e-01 1.23168409e+00 -2.59869592e-03 3.17083746e-01 1.04097620e-01 1.20609295e+00 1.72310807e-02 -2.46991441e-01 8.97726626e-04 -2.41434574e-01 -6.29709840e-01 -2.87804365e-01 -4.88691956e-01 -3.80921155e-01 -7.91455746e-01 7.91246057e-01 6.26188517e-01 -2.87472367e-01 4.64601964e-01 -1.10659409e+00 -1.00232351e+00 6.28479958e-01 -1.75805185e-02 3.60208005e-01 5.08563161e-01 1.46925315e-01 6.62030518e-01 -5.13430178e-01 3.56026530e-01 8.52175415e-01 1.16955245e+00 6.99142694e-01 -8.53190958e-01 -6.12376809e-01 -4.23723236e-02 4.06252205e-01 -1.38685787e+00 -2.54346013e-01 5.03854752e-01 -4.80490565e-01 9.41798747e-01 4.02445883e-01 8.15141141e-01 1.34162080e+00 6.22736216e-01 7.73404717e-01 5.29353321e-01 1.15808591e-01 2.02316679e-02 -7.00305030e-02 2.93200731e-01 7.16628909e-01 2.27780715e-02 3.79933864e-01 -1.78676426e-01 -7.08821476e-01 4.99548912e-01 1.14604640e+00 -4.37679112e-01 4.26203348e-02 -1.50014639e+00 5.26893795e-01 5.28338969e-01 3.40519786e-01 -7.92014480e-01 -2.84482330e-01 7.47397721e-01 4.19964433e-01 3.87426496e-01 -1.39822572e-01 -9.18138981e-01 -1.24819182e-01 -5.92470586e-01 1.61475316e-01 8.32816243e-01 9.45928574e-01 -9.38696787e-02 -3.01092178e-01 -4.43813115e-01 5.02958417e-01 2.66383469e-01 3.50917995e-01 9.69650626e-01 -3.04937422e-01 5.94839990e-01 1.06751668e+00 2.03991935e-01 -9.21723723e-01 -6.99459851e-01 -3.40895027e-01 -1.51502800e+00 -7.91566193e-01 2.34016906e-02 -1.33185983e-01 -9.20971215e-01 1.52348590e+00 4.44560736e-01 5.81155062e-01 1.87167525e-01 6.25624776e-01 9.44859385e-01 4.46892321e-01 2.39654511e-01 -4.76200461e-01 1.68976021e+00 -4.49823350e-01 -1.08612621e+00 3.27349722e-01 1.11799788e+00 -3.13655317e-01 7.95178235e-01 3.20678055e-01 -9.05766726e-01 -2.96438724e-01 -3.79446179e-01 -8.35528821e-02 -4.23285931e-01 1.57156810e-01 5.12593448e-01 2.97649708e-02 -6.41465783e-01 7.64212549e-01 -1.24927068e+00 -3.34955692e-01 5.80557108e-01 4.03269470e-01 -3.07237059e-01 -3.34844440e-01 -1.56737626e+00 7.17173696e-01 3.34805191e-01 1.78105608e-01 -5.26896656e-01 -1.16020715e+00 -1.02737904e+00 2.30730653e-01 8.65496695e-02 -1.01137412e+00 1.19895661e+00 -2.99455792e-01 -8.09040010e-01 5.38768470e-01 -2.27696732e-01 -5.22229135e-01 4.72426414e-01 -3.11253130e-01 -9.10425305e-01 -2.89825112e-01 -1.85111940e-01 -1.95856467e-01 1.74279943e-01 -4.39602256e-01 -5.89100659e-01 -7.02830493e-01 -5.36039829e-01 -5.38724028e-02 -5.83149672e-01 -1.28743216e-01 -1.38471246e-01 -5.62388301e-01 -2.09649131e-02 -6.49273992e-01 -5.04983127e-01 -1.72060534e-01 -3.17855179e-01 -4.06480283e-01 7.02275693e-01 -1.07534456e+00 1.92078316e+00 -2.19226766e+00 -4.70931306e-02 -5.16190305e-02 3.98882329e-01 2.94518739e-01 2.97992527e-01 7.17971921e-01 -2.69902557e-01 -1.40991062e-01 -3.18046957e-01 -2.56769449e-01 -2.42680863e-01 3.75849187e-01 -1.54727787e-01 4.74906445e-01 6.59774616e-02 1.11326790e+00 -9.50439930e-01 -5.40219069e-01 2.86407292e-01 7.92368472e-01 -5.52128673e-01 4.31590945e-01 1.41560957e-01 6.39407218e-01 -7.36813366e-01 8.76697302e-01 4.06266242e-01 -7.09482312e-01 1.37233734e-01 -2.46729165e-01 2.15253811e-02 4.20093089e-01 -8.62325013e-01 1.58918822e+00 -2.96049803e-01 -1.08727664e-01 -4.35876936e-01 -1.08245850e+00 5.35116255e-01 9.90617394e-01 1.12188220e+00 -8.40998232e-01 2.56493270e-01 1.38101995e-01 -2.76411641e-02 -1.15307260e+00 -2.02181071e-01 8.48038867e-03 -1.14022180e-01 9.96223018e-02 -3.10593337e-01 6.80909872e-01 -1.59762368e-01 -9.99678746e-02 1.48613989e+00 -1.97165713e-01 5.83327234e-01 7.27922618e-02 3.15606803e-01 -1.34384558e-01 1.01592171e+00 2.87425041e-01 -3.25995237e-01 4.76846188e-01 2.91998237e-01 -1.00764143e+00 -1.00006616e+00 -9.50815856e-01 -6.23612642e-01 4.09479350e-01 -1.15275823e-01 -4.01577532e-01 -1.59764603e-01 -5.38556874e-01 2.52048999e-01 4.17644054e-01 -8.70617867e-01 -4.62904364e-01 -5.25427222e-01 -1.24182463e+00 4.88015771e-01 7.13819444e-01 1.13327436e-01 -1.06329536e+00 -7.09769130e-01 6.22995138e-01 -5.29197097e-01 -8.81147981e-01 -5.60764849e-01 1.77819833e-01 -1.14151251e+00 -1.32990623e+00 -5.26227057e-01 -7.47410238e-01 7.25831151e-01 -4.25259322e-01 1.11562943e+00 1.32873133e-01 -5.10439813e-01 1.97664902e-01 -2.96779990e-01 -4.15498883e-01 -1.76344097e-01 -1.54353872e-01 2.27079511e-01 6.62603080e-02 7.04706192e-01 -5.40835738e-01 -9.59771872e-01 8.20169300e-02 -1.10187256e+00 3.73119377e-02 4.59823072e-01 1.11721539e+00 7.99954355e-01 1.07378297e-01 5.76918244e-01 -1.04727411e+00 6.05633676e-01 -1.17510569e+00 -1.92374945e-01 2.78144777e-01 -9.54238772e-01 3.82158123e-02 9.28378642e-01 -3.64750236e-01 -7.40394115e-01 -8.87952396e-04 -3.62318903e-01 -6.61895037e-01 -2.44306013e-01 7.00530231e-01 2.11151704e-01 7.02690661e-01 2.68707931e-01 5.29660285e-01 -8.61088708e-02 -6.24624848e-01 -3.33788782e-01 1.00916445e+00 3.19879204e-01 -1.08746663e-01 2.27652460e-01 3.30507129e-01 -2.02728495e-01 -1.18068710e-01 -8.24413478e-01 -7.43960857e-01 -4.45864469e-01 3.12289774e-01 8.82495463e-01 -1.07358456e+00 -9.95931566e-01 3.41351092e-01 -8.94824326e-01 -2.63387952e-02 -3.35712194e-01 6.95277035e-01 -2.69176394e-01 1.66221708e-01 -1.04764688e+00 -7.29957759e-01 -7.67334223e-01 -8.41430366e-01 8.79565537e-01 -3.70555557e-02 -3.93833399e-01 -1.20929801e+00 8.73307437e-02 1.42609134e-01 2.81236380e-01 6.18171096e-01 1.22397840e+00 -9.24966574e-01 -1.81784973e-01 -5.06674230e-01 -1.16903372e-01 7.32984394e-02 6.57387614e-01 -2.51397938e-01 -4.51316893e-01 -4.16966587e-01 3.74477625e-01 7.04798773e-02 5.04054129e-01 4.73865330e-01 1.52425718e+00 -7.52588093e-01 -6.80106759e-01 9.30987418e-01 1.43547451e+00 6.02297843e-01 5.27441919e-01 3.34405154e-02 7.62944460e-01 2.85180956e-01 5.09940386e-01 9.18443561e-01 9.86661732e-01 2.62620121e-01 4.65992957e-01 -1.20047688e-01 3.88376564e-01 -2.61024594e-01 -4.59613651e-02 1.25424612e+00 -1.21321501e-02 -1.00537091e-01 -1.13250864e+00 8.63721430e-01 -2.16992354e+00 -8.06842804e-01 -2.84264833e-01 2.23389864e+00 9.31985140e-01 -2.05205247e-01 -9.72476527e-02 2.90630162e-01 4.02176499e-01 -2.95547724e-01 -8.01856577e-01 -1.30932912e-01 2.63426125e-01 2.25091632e-02 5.39551616e-01 7.91974440e-02 -9.71325457e-01 1.82069600e-01 5.64553690e+00 2.30607688e-01 -1.04032683e+00 3.03193033e-01 6.60126805e-01 -2.59883761e-01 -2.16303319e-01 -4.77865577e-01 -5.02115071e-01 1.02576566e+00 1.12490892e+00 -5.19890897e-02 2.63074875e-01 6.34910643e-01 4.57959384e-01 5.66386580e-01 -1.39448595e+00 1.15233743e+00 -3.20708185e-01 -1.09618866e+00 -1.30556554e-01 3.14081199e-02 4.46516722e-01 1.85727552e-01 1.58053488e-01 3.21656525e-01 3.10952991e-01 -1.09450376e+00 2.41228077e-03 9.15196121e-01 9.41890836e-01 -6.22724593e-01 1.12459230e+00 4.53683227e-01 -1.22298086e+00 -5.46411872e-01 9.67860408e-03 -1.37263209e-01 1.82365686e-01 7.89831460e-01 -6.95664644e-01 8.25225174e-01 1.04467463e+00 1.23204625e+00 -1.95855096e-01 9.37961280e-01 2.61514574e-01 6.18217349e-01 -2.32161418e-01 4.16104585e-01 -7.56965652e-02 -1.06496900e-01 1.50381178e-01 1.03691125e+00 7.31645763e-01 4.99940723e-01 2.45685592e-01 5.48721731e-01 1.34622723e-01 1.04114912e-01 -7.95991421e-01 -3.55721116e-02 4.08493340e-01 7.97530890e-01 -4.76102494e-02 -4.91696060e-01 -5.01050115e-01 9.64494109e-01 1.66730583e-01 2.66981632e-01 -9.96355474e-01 -1.36537328e-01 7.08285272e-01 3.44555885e-01 3.15732434e-02 2.60052145e-01 -3.09968561e-01 -1.32932460e+00 2.55550593e-01 -8.64114285e-01 9.23665941e-01 -2.89299965e-01 -1.43667936e+00 5.61012864e-01 -3.60706955e-01 -1.55257738e+00 -2.24460602e-01 -2.60065287e-01 -4.42240894e-01 5.85533679e-01 -1.50013077e+00 -1.01942682e+00 -2.65530229e-01 9.79471266e-01 1.68606952e-01 -6.70303851e-02 1.27119410e+00 9.95495617e-01 -8.14164400e-01 6.37194574e-01 3.10505867e-01 2.71846116e-01 5.40563822e-01 -9.94769514e-01 2.10573837e-01 3.74804676e-01 -5.15714943e-01 6.70211315e-01 4.36273903e-01 -6.15926743e-01 -1.47531176e+00 -1.43561518e+00 1.44574320e+00 -7.07603633e-01 4.32402045e-01 5.88879660e-02 -1.12553740e+00 1.04382634e+00 -2.26496413e-01 3.46729070e-01 1.06297088e+00 2.97619328e-02 -6.91573098e-02 -2.23794878e-01 -1.33976746e+00 3.74842584e-01 1.11533403e+00 -3.74107540e-01 -6.72407150e-01 4.27195549e-01 8.12366366e-01 -5.94465017e-01 -1.53205442e+00 8.01989734e-01 5.32363713e-01 -6.34354949e-01 1.00701809e+00 -9.14743841e-01 6.28028035e-01 -1.87787369e-01 1.24077871e-01 -1.21356201e+00 -6.61560655e-01 -2.44756609e-01 -6.06053889e-01 7.07804263e-01 7.24980608e-02 -9.42256749e-01 3.58354062e-01 7.17430055e-01 -1.69759691e-01 -1.42044449e+00 -9.18367028e-01 -3.48140061e-01 -3.68770897e-01 -1.25987276e-01 1.08777273e+00 1.31630862e+00 2.92466909e-01 -1.21772386e-01 -6.02550924e-01 3.77329022e-01 3.25083226e-01 9.78221186e-03 9.83829647e-02 -1.47019541e+00 -9.08656940e-02 -1.09137230e-01 -4.18963879e-01 -6.45186424e-01 -4.54072446e-01 -8.23903561e-01 -3.21078897e-01 -1.83265710e+00 2.42576614e-01 -6.19134903e-01 -1.09680068e+00 7.74228632e-01 -2.81102926e-01 -3.02365929e-01 -3.55433911e-01 3.85440230e-01 -5.11634588e-01 6.00815177e-01 1.23414612e+00 -1.68664843e-01 -3.70347291e-01 1.00850895e-01 -5.37527919e-01 6.02809429e-01 6.04310393e-01 -7.15214014e-01 -4.07259077e-01 -5.20797551e-01 2.55486548e-01 6.02747142e-01 2.11082160e-01 -9.49503660e-01 2.95270264e-01 -1.34904981e-01 4.11174178e-01 -4.69892830e-01 9.74487960e-02 -1.26378977e+00 5.53084075e-01 1.05671227e+00 -2.82340795e-01 4.32514995e-01 1.00303248e-01 5.53481102e-01 -4.27944839e-01 3.92925262e-01 3.42729867e-01 -9.78694186e-02 -2.74544984e-01 1.02459335e+00 -1.15610905e-01 -7.43554384e-02 1.09482276e+00 6.54047802e-02 6.98200762e-02 1.18858367e-01 -8.94188702e-01 5.80463350e-01 5.90015277e-02 4.97940540e-01 7.81460583e-01 -1.49985325e+00 -7.57596731e-01 3.72027963e-01 3.54688346e-01 3.34947497e-01 7.44786203e-01 1.32944393e+00 -3.54435861e-01 4.78446633e-01 6.05124533e-02 -4.53963965e-01 -1.21041238e+00 1.03511846e+00 2.71596223e-01 -7.19748497e-01 -1.02812815e+00 4.26806957e-01 6.69950694e-02 -5.78249812e-01 4.13253427e-01 -9.07553375e-01 -3.18237543e-01 5.21404259e-02 6.43564522e-01 1.42363906e-01 1.04892805e-01 -3.42319787e-01 -4.64191914e-01 2.99327731e-01 -2.33751252e-01 7.99973726e-01 1.51475990e+00 -1.10681579e-01 1.99010540e-02 5.92094064e-01 1.18692911e+00 -6.43511236e-01 -7.16844618e-01 -4.81832772e-01 -1.36322007e-01 -1.10804237e-01 -2.02798262e-01 -6.90800309e-01 -1.09975934e+00 5.97278476e-01 8.90165985e-01 3.12005132e-01 1.30628657e+00 -2.54935116e-01 1.50700867e+00 1.79248810e-01 1.02735676e-01 -6.43260062e-01 -4.57076639e-01 3.62071484e-01 5.23562908e-01 -1.40291727e+00 -3.80671054e-01 -3.86004262e-02 -6.43902242e-01 7.51724839e-01 2.31086195e-01 7.05981106e-02 1.21056950e+00 3.25543970e-01 1.94777653e-01 -2.60799050e-01 -1.12345159e+00 2.37233654e-01 -3.50262597e-02 4.82542515e-01 5.21136522e-01 3.76770347e-01 -3.29742670e-01 1.18475699e+00 1.91625673e-02 7.44887710e-01 3.27428393e-02 8.92506897e-01 2.11481079e-01 -9.12412941e-01 -2.15753376e-01 9.21573937e-01 -8.77231538e-01 -3.45362157e-01 3.47723573e-01 2.90596724e-01 4.46962923e-01 6.01681948e-01 7.33199790e-02 -4.96374279e-01 6.07400537e-01 3.57263267e-01 4.44886126e-02 -3.78541559e-01 -6.66205049e-01 -3.62118185e-01 -3.30612540e-01 -6.62271380e-01 -6.14484921e-02 -6.74310088e-01 -1.43617153e+00 -2.30093062e-01 1.53537348e-01 9.42357033e-02 2.32916057e-01 9.83331859e-01 8.08737636e-01 1.03946185e+00 5.00049055e-01 -1.54240891e-01 -7.34714091e-01 -9.38677549e-01 -4.99786913e-01 8.50939691e-01 8.59173119e-01 -3.68366539e-01 -2.38638654e-01 2.22921953e-01]	[7.914104461669922, 6.2550368309021]
c792e1ce-7bf3-4435-b799-8a3d50d18cb9	hierarchical-and-contrastive-representation	2304.07506	null	https://arxiv.org/abs/2304.07506v1	https://arxiv.org/pdf/2304.07506v1.pdf	Hierarchical and Contrastive Representation Learning for Knowledge-aware Recommendation	Incorporating knowledge graph into recommendation is an effective way to alleviate data sparsity. Most existing knowledge-aware methods usually perform recursive embedding propagation by enumerating graph neighbors. However, the number of nodes' neighbors grows exponentially as the hop number increases, forcing the nodes to be aware of vast neighbors under this recursive propagation for distilling the high-order semantic relatedness. This may induce more harmful noise than useful information into recommendation, leading the learned node representations to be indistinguishable from each other, that is, the well-known over-smoothing issue. To relieve this issue, we propose a Hierarchical and CONtrastive representation learning framework for knowledge-aware recommendation named HiCON. Specifically, for avoiding the exponential expansion of neighbors, we propose a hierarchical message aggregation mechanism to interact separately with low-order neighbors and meta-path-constrained high-order neighbors. Moreover, we also perform cross-order contrastive learning to enforce the representations to be more discriminative. Extensive experiments on three datasets show the remarkable superiority of HiCON over state-of-the-art approaches.	['Yongji Wang', 'Bei guan', 'Daoguang Zan', 'Yangyuxuan Kang', 'Bingchao Wu']	2023-04-15	null	null	null	null	['knowledge-aware-recommendation']	['miscellaneous']	[-2.96933413e-01 2.98047781e-01 -6.17279410e-01 -2.64928848e-01 -1.71223879e-01 -2.68159747e-01 4.58195359e-01 3.30330312e-01 -1.29859298e-01 5.29532611e-01 8.29865813e-01 -8.24122354e-02 -4.40743595e-01 -1.27218676e+00 -3.97846937e-01 -7.46769011e-01 -2.26713255e-01 2.20024005e-01 4.00224864e-01 -2.20916927e-01 1.05918273e-01 2.39589438e-01 -1.22768354e+00 -3.02467938e-03 9.79086578e-01 7.40533412e-01 1.60810784e-01 -1.09472401e-01 -4.39067185e-01 5.79304338e-01 -2.51995295e-01 -4.76026207e-01 3.30107473e-02 -2.55832374e-01 -5.09276748e-01 -1.66853191e-03 2.30528146e-01 -2.87914366e-01 -7.79384851e-01 1.10685265e+00 3.02167565e-01 4.49952543e-01 5.94661236e-01 -1.08179522e+00 -1.12510836e+00 1.14822757e+00 -7.12128818e-01 1.19774312e-01 1.52185470e-01 -2.52657682e-01 1.35467017e+00 -7.15725303e-01 4.58823740e-01 1.22976363e+00 6.72105968e-01 8.57505426e-02 -1.02672601e+00 -6.67524517e-01 7.80431211e-01 1.76352814e-01 -1.62154603e+00 -6.27181027e-03 1.12226093e+00 -2.34171584e-01 5.21247208e-01 2.54601240e-01 5.89096189e-01 8.64801109e-01 -4.93646622e-01 5.45443296e-01 5.71556151e-01 -5.06209619e-02 7.05630258e-02 1.96195632e-01 4.67347920e-01 7.91836262e-01 6.58643842e-01 -1.01790085e-01 -3.61307085e-01 -4.65465397e-01 7.99755335e-01 4.79815573e-01 -4.17567790e-01 -3.83238018e-01 -9.21666980e-01 1.00355721e+00 8.19251180e-01 5.00178099e-01 -4.06901777e-01 1.05098903e-01 3.24968457e-01 2.06592530e-01 4.53169703e-01 2.60428727e-01 -3.76409411e-01 4.00469065e-01 -5.89801610e-01 -2.81575471e-01 6.55499876e-01 8.16342354e-01 1.15901077e+00 -3.40988748e-02 -3.63632530e-01 8.99545252e-01 5.50711274e-01 -1.39017880e-01 3.88316453e-01 -5.78868389e-01 4.13649172e-01 9.39383209e-01 -2.05126867e-01 -1.71288383e+00 -1.42225519e-01 -9.73677218e-01 -1.17180657e+00 -4.21823025e-01 7.85535350e-02 -4.32586819e-02 -6.03850245e-01 1.57921433e+00 4.43217576e-01 6.38283908e-01 -2.46724397e-01 1.02872407e+00 8.42882633e-01 8.38322759e-01 1.94468766e-01 -4.48780924e-01 1.21656394e+00 -1.15217257e+00 -5.14762461e-01 6.57031909e-02 7.10662544e-01 -4.43106592e-01 1.00117207e+00 2.84690596e-02 -5.82757711e-01 -5.17255604e-01 -9.06331480e-01 1.22783277e-02 -3.30036521e-01 -7.84853995e-02 9.33367908e-01 3.69816691e-01 -6.86488450e-01 6.37299836e-01 -4.61013734e-01 -1.85630433e-02 4.40654010e-01 1.85271502e-01 -2.77739227e-01 -3.08815807e-01 -1.46827030e+00 2.80716240e-01 5.57722092e-01 2.02175938e-02 -4.65364128e-01 -8.31758022e-01 -6.59550548e-01 3.82181644e-01 5.53773582e-01 -6.06422365e-01 4.55010116e-01 -7.60307193e-01 -1.16360486e+00 1.63284048e-01 -1.75938666e-01 1.34655810e-03 5.24628386e-02 -1.91125318e-01 -7.71834850e-01 -1.50793893e-02 -1.49985254e-01 1.57109782e-01 8.66512239e-01 -1.45670998e+00 -3.89471054e-01 -2.43232355e-01 3.91631722e-01 3.39006215e-01 -1.03553188e+00 -5.60819149e-01 -9.02810872e-01 -9.00814533e-01 3.26357782e-01 -6.15181625e-01 -5.18140733e-01 -8.83727372e-02 -4.81600046e-01 -5.06455779e-01 7.31563807e-01 -4.16805565e-01 1.84962440e+00 -2.21071005e+00 2.00958714e-01 6.53726757e-01 7.05368161e-01 1.51312232e-01 -5.64506292e-01 4.88841593e-01 2.20787257e-01 2.36900777e-01 2.36241683e-01 -2.82605905e-02 -1.41833320e-01 4.68194336e-01 -1.73708931e-01 4.12787557e-01 -2.80640543e-01 6.99409008e-01 -1.31330407e+00 -5.05535781e-01 2.01398171e-02 8.91452909e-01 -7.46570528e-01 5.10299392e-02 -1.00836113e-01 3.39956969e-01 -9.84678328e-01 3.17590386e-01 7.39201009e-01 -6.09353483e-01 3.91681105e-01 -7.40597010e-01 1.77051827e-01 5.40851176e-01 -1.16725779e+00 1.51600504e+00 -4.03458118e-01 -1.34158388e-01 -1.15068421e-01 -1.10687923e+00 9.93330598e-01 -4.35318872e-02 4.56954449e-01 -4.79287416e-01 -1.73915327e-02 -7.32229948e-02 -2.69274682e-01 -2.25531995e-01 5.18930912e-01 1.09751299e-01 1.74623385e-01 2.85154164e-01 -1.47402778e-01 5.96565306e-01 5.32641262e-03 5.54766297e-01 9.86156106e-01 -3.77182215e-01 2.17599235e-02 -1.92526802e-01 5.69194198e-01 -5.06298006e-01 8.41628253e-01 5.37092388e-01 2.29373217e-01 2.75112718e-01 5.06037414e-01 -2.57631421e-01 -5.90239525e-01 -8.49277139e-01 3.65673035e-01 1.28205502e+00 4.71038193e-01 -9.58257258e-01 -1.71633959e-01 -1.11157000e+00 2.66635329e-01 6.41427398e-01 -5.92763960e-01 -4.53779578e-01 -4.59602743e-01 -5.85190713e-01 1.79606959e-01 4.06051427e-01 2.43747383e-01 -5.69685042e-01 4.07695115e-01 2.49857634e-01 -1.39984161e-01 -7.11599410e-01 -7.31962085e-01 -1.52527362e-01 -9.32287097e-01 -8.94008160e-01 -7.38932073e-01 -8.70450437e-01 1.03956950e+00 6.99624181e-01 1.05698252e+00 5.82463861e-01 1.20822392e-01 2.52935499e-01 -7.98116207e-01 3.78796041e-01 7.29083344e-02 3.16498220e-01 -5.57112321e-02 5.30932732e-02 2.92083532e-01 -1.07569337e+00 -9.82532263e-01 3.29673409e-01 -7.83729553e-01 -2.93010354e-01 7.09348261e-01 8.13344121e-01 7.44780242e-01 5.01689196e-01 6.22857928e-01 -1.00316966e+00 6.55543208e-01 -8.25739741e-01 -3.43386114e-01 2.65522718e-01 -7.71652102e-01 1.91737160e-01 9.05197859e-01 -5.85466862e-01 -8.95882249e-01 -9.60260183e-02 -1.61927417e-02 -4.22536790e-01 2.17966482e-01 8.73822331e-01 -1.90161332e-01 -8.90303552e-02 2.45113894e-01 2.33154848e-01 -5.01843631e-01 -7.77585208e-01 7.51375794e-01 4.13936406e-01 2.02210188e-01 -4.13648635e-01 1.05690277e+00 3.43859971e-01 -4.53196913e-02 -8.90091896e-01 -1.13779056e+00 -5.49625635e-01 -2.75951833e-01 1.02925874e-01 4.41223145e-01 -9.25360799e-01 -4.21737999e-01 -1.06979169e-01 -8.91448140e-01 1.67789668e-01 -2.74291247e-01 6.28898621e-01 2.48359650e-01 7.22940505e-01 -5.82203984e-01 -5.82174659e-01 -2.90554941e-01 -7.31950164e-01 5.89099824e-01 2.49500945e-01 7.46244416e-02 -1.13275361e+00 2.01110631e-01 2.02530265e-01 4.11471993e-01 -2.10598394e-01 1.15259540e+00 -8.22763860e-01 -6.52507544e-01 -1.25660717e-01 -6.24043882e-01 1.46375313e-01 2.89831132e-01 -2.45441094e-01 -5.88331342e-01 -3.23107958e-01 -5.89299381e-01 -3.57493237e-02 1.28066206e+00 -2.27534268e-02 1.31649804e+00 -7.73879588e-01 -6.47263169e-01 5.25415897e-01 1.24186385e+00 -4.70604509e-01 4.67827857e-01 -5.76486550e-02 1.17119896e+00 4.25023735e-01 4.00276542e-01 6.25758350e-01 6.85700595e-01 5.12867093e-01 4.20300454e-01 1.61477104e-02 -2.30266854e-01 -8.76674294e-01 1.62231013e-01 1.35392642e+00 -1.86835259e-01 -3.76587331e-01 -3.08599591e-01 5.29653251e-01 -1.80040896e+00 -8.69874358e-01 -1.78247660e-01 2.25962782e+00 8.23754430e-01 -3.98801006e-02 3.29844579e-02 -5.17495070e-03 8.26774478e-01 5.82020760e-01 -2.99267739e-01 1.85179114e-01 1.76196545e-02 -3.36686909e-01 5.19434810e-01 4.39280272e-01 -9.31675196e-01 8.83673310e-01 5.31808662e+00 1.12224770e+00 -9.13091421e-01 1.31349981e-01 3.56121480e-01 2.92640865e-01 -1.08880663e+00 2.28697658e-01 -7.67100036e-01 6.07454717e-01 3.56767714e-01 -1.00305557e-01 3.54865968e-01 7.70372331e-01 -7.95471072e-02 3.36233974e-01 -6.14984334e-01 7.80565679e-01 -9.16629433e-05 -1.35314155e+00 3.40019792e-01 1.26775980e-01 7.95169175e-01 6.82505779e-03 -1.91937387e-01 4.55193132e-01 4.97231632e-01 -6.52597308e-01 1.16397113e-01 4.35776979e-01 4.44408596e-01 -8.78442883e-01 5.49266756e-01 3.56679231e-01 -1.53815877e+00 -1.24645017e-01 -8.53021145e-01 1.18824929e-01 1.02165833e-01 1.15519202e+00 -3.33518654e-01 8.04298699e-01 5.15620708e-01 1.04111648e+00 -4.21365768e-01 1.01799560e+00 -3.34955275e-01 7.24637747e-01 -3.50645751e-01 -1.18788771e-01 2.50704229e-01 -3.92653704e-01 5.29160678e-01 1.16337013e+00 5.10711849e-01 3.44455928e-01 4.87986088e-01 5.48286736e-01 -4.12602395e-01 3.35008949e-01 -4.12747353e-01 -2.67529309e-01 8.50234389e-01 1.25931990e+00 -4.82351065e-01 -2.83554137e-01 -7.36671567e-01 1.00052369e+00 7.12589502e-01 4.60256100e-01 -5.73576510e-01 -4.04695898e-01 5.62250853e-01 3.09213400e-01 6.54281914e-01 -2.76926279e-01 1.31499305e-01 -1.20570838e+00 -3.84809598e-02 -3.68769020e-01 6.29176855e-01 -1.03092410e-01 -1.80496919e+00 3.63262147e-01 -3.20849210e-01 -1.19738102e+00 4.47866976e-01 -2.62085292e-02 -7.39692688e-01 5.41939557e-01 -1.87358570e+00 -1.15293443e+00 -2.20735341e-01 6.43291414e-01 6.03411980e-02 -3.99553254e-02 7.27016091e-01 6.74707115e-01 -5.12851298e-01 9.95723069e-01 1.86884612e-01 5.11014760e-02 5.49410462e-01 -7.19127536e-01 -2.27012917e-01 4.38288361e-01 3.46783668e-01 8.71659160e-01 3.44976395e-01 -8.29443395e-01 -1.47103417e+00 -1.30781066e+00 8.50261927e-01 5.61847873e-02 8.44918311e-01 -2.90880427e-02 -1.22929525e+00 5.13984323e-01 -1.54794544e-01 2.79402196e-01 8.83437991e-01 6.70219302e-01 -9.09421682e-01 -4.18512225e-01 -7.20974624e-01 6.31613195e-01 1.29797232e+00 -4.74637419e-01 -5.67321122e-01 2.88102061e-01 9.76910651e-01 3.53535205e-01 -1.01195443e+00 4.70117629e-01 3.80508304e-01 -9.03450787e-01 1.13522816e+00 -3.75216097e-01 1.86344236e-01 -4.84494686e-01 1.02086896e-02 -1.29008651e+00 -8.18396091e-01 -5.91855228e-01 -6.62327826e-01 1.65783894e+00 3.64007562e-01 -6.61879718e-01 8.27886343e-01 3.40298600e-02 2.05555058e-04 -7.79054880e-01 -6.40495300e-01 -8.19267750e-01 -1.44533351e-01 -5.14122732e-02 6.61318421e-01 1.37457740e+00 2.24251553e-01 6.04048073e-01 -6.57518506e-01 4.94882643e-01 5.85226595e-01 2.68954009e-01 4.63672459e-01 -1.52219689e+00 -4.72323000e-01 -4.34266657e-01 -3.78007770e-01 -1.63053119e+00 5.55198863e-02 -1.10565031e+00 -2.19465613e-01 -1.68200529e+00 3.14391613e-01 -1.01511323e+00 -8.97330105e-01 4.96763349e-01 -2.92677253e-01 3.17734331e-02 -1.36477262e-01 4.06219482e-01 -9.30322886e-01 8.31410229e-01 1.47345948e+00 -7.63042346e-02 -2.35974908e-01 -2.30045035e-01 -1.12943327e+00 6.83845758e-01 6.96107030e-01 -5.41770101e-01 -7.97337353e-01 -5.30587494e-01 5.20667732e-01 -2.54450589e-01 1.32519081e-01 -6.00770891e-01 3.70532334e-01 -1.79811120e-01 1.35696992e-01 -4.95765805e-01 1.06095716e-01 -9.27678108e-01 6.62088469e-02 1.30220622e-01 -3.97566885e-01 -4.50227976e-01 -3.24243695e-01 1.11957788e+00 -1.89182714e-01 -1.10119916e-02 3.97427022e-01 3.99620980e-02 -6.88161016e-01 6.27372682e-01 1.14438804e-02 -2.97698323e-02 6.80769861e-01 9.44934785e-02 -4.22224969e-01 -4.95097280e-01 -5.38072109e-01 3.98473054e-01 3.46545458e-01 5.12155950e-01 6.80532217e-01 -1.51772380e+00 -5.57235837e-01 1.20720036e-01 3.82145345e-01 -7.28815049e-02 4.82102275e-01 8.34984064e-01 2.03028843e-01 2.07232162e-02 3.25624943e-01 -8.15231819e-04 -8.67877007e-01 7.90531397e-01 -1.81533873e-01 -4.88318056e-01 -7.88432300e-01 9.85317469e-01 3.55988979e-01 -3.91832769e-01 4.04128015e-01 1.38780192e-01 -4.72346038e-01 1.61759108e-01 5.11231601e-01 5.76370716e-01 -3.79895985e-01 -4.62819517e-01 -2.39856437e-01 6.36084497e-01 -4.24419045e-01 5.76678932e-01 1.31064558e+00 -3.49498987e-01 -3.21379393e-01 5.92715703e-02 1.34528625e+00 3.23492944e-01 -9.04878318e-01 -6.42255187e-01 -1.39115095e-01 -4.70847666e-01 4.09003556e-01 -3.91749531e-01 -1.45216286e+00 5.62206626e-01 8.32159147e-02 3.65655214e-01 9.50171053e-01 2.41876453e-01 9.79548633e-01 5.78527331e-01 2.06642091e-01 -9.21526909e-01 4.43939716e-02 4.65930730e-01 5.64802945e-01 -9.14986968e-01 2.93683320e-01 -8.96355391e-01 -4.03724253e-01 8.55525315e-01 6.16304874e-01 -2.32071206e-01 1.14831209e+00 -1.54026315e-01 -3.88368994e-01 -2.16020837e-01 -5.05563855e-01 -2.43042022e-01 5.32222867e-01 5.80995262e-01 4.62949395e-01 5.67380711e-02 -6.14149392e-01 8.71389091e-01 2.62779653e-01 -1.53901950e-01 8.02920908e-02 4.94609326e-01 -6.66699409e-01 -1.24395287e+00 1.75872460e-01 6.17167473e-01 -1.59765273e-01 -3.15293163e-01 -3.21160436e-01 5.02360046e-01 2.13742092e-01 9.04684126e-01 -8.02184045e-02 -6.84896171e-01 6.47706315e-02 -3.62873942e-01 2.78960448e-02 -5.26466012e-01 -2.46108294e-01 1.53947711e-01 1.18681878e-01 -3.37957412e-01 -2.87937075e-01 -1.15144350e-01 -1.28161108e+00 -3.19214940e-01 -5.48745036e-01 4.52454358e-01 1.28800198e-02 7.28126466e-01 6.96785569e-01 5.77757835e-01 9.20242429e-01 -5.05634367e-01 -5.28218389e-01 -7.07496703e-01 -8.35560143e-01 4.19859171e-01 2.11243361e-01 -6.65994406e-01 -6.13774121e-01 -4.95975435e-01]	[10.243395805358887, 5.664527416229248]
c2b75b59-6b9c-4483-b2ef-efe6c24940ae	generalized-product-of-experts-for-learning	2211.03587	null	https://arxiv.org/abs/2211.03587v1	https://arxiv.org/pdf/2211.03587v1.pdf	Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environments	A real-world application or setting involves interaction between different modalities (e.g., video, speech, text). In order to process the multimodal information automatically and use it for an end application, Multimodal Representation Learning (MRL) has emerged as an active area of research in recent times. MRL involves learning reliable and robust representations of information from heterogeneous sources and fusing them. However, in practice, the data acquired from different sources are typically noisy. In some extreme cases, a noise of large magnitude can completely alter the semantics of the data leading to inconsistencies in the parallel multimodal data. In this paper, we propose a novel method for multimodal representation learning in a noisy environment via the generalized product of experts technique. In the proposed method, we train a separate network for each modality to assess the credibility of information coming from that modality, and subsequently, the contribution from each modality is dynamically varied while estimating the joint distribution. We evaluate our method on two challenging benchmarks from two diverse domains: multimodal 3D hand-pose estimation and multimodal surgical video segmentation. We attain state-of-the-art performance on both benchmarks. Our extensive quantitative and qualitative evaluations show the advantages of our method compared to previous approaches.	['Danail Stoyanov', 'Ashutosh Modi', 'Binod Bhattarai', 'Jinang Shah', 'Naman Gupta', 'Abhinav Joshi']	2022-11-07	null	null	null	null	['3d-hand-pose-estimation', '3d-hand-pose-estimation']	['computer-vision', 'graphs']	[ 3.88684571e-01 4.65926155e-02 -2.45162144e-01 -2.42477670e-01 -1.55606556e+00 -4.52825487e-01 4.30530399e-01 5.05534649e-01 -4.43624377e-01 6.06251597e-01 4.53847855e-01 6.16120808e-02 -2.00074464e-01 -2.19490647e-01 -6.70877993e-01 -9.24017727e-01 3.37417364e-01 5.26181102e-01 1.03199013e-01 -4.59879488e-02 6.68000132e-02 1.01404712e-01 -1.41365016e+00 6.12773538e-01 7.82499492e-01 1.01616240e+00 3.23305249e-01 5.49575150e-01 -1.35431007e-01 9.01394486e-01 -5.13591051e-01 -3.98540825e-01 -6.76731318e-02 -3.47860098e-01 -8.24697435e-01 3.24043810e-01 4.83566932e-02 -6.48207963e-03 -3.13007623e-01 1.22973406e+00 7.40399718e-01 1.26836792e-01 6.98789060e-01 -1.09578979e+00 -2.44695581e-02 7.81952918e-01 -7.99794197e-01 -3.40950117e-02 6.18845344e-01 5.15770316e-02 6.27545416e-01 -7.94732392e-01 7.01521516e-01 1.35535836e+00 3.36785585e-01 4.03098732e-01 -1.12058973e+00 -3.30400497e-01 3.02096456e-01 1.37906477e-01 -1.25115120e+00 -4.56166476e-01 9.02771592e-01 -4.95286971e-01 1.52814202e-02 1.52917594e-01 2.49249682e-01 1.29865730e+00 2.02162400e-01 1.21644723e+00 1.07578230e+00 -2.28676289e-01 1.27171934e-01 2.55115271e-01 -7.82096386e-02 5.82521319e-01 -1.21855661e-01 -1.84387833e-01 -7.54521132e-01 -3.98860574e-01 3.76300484e-01 2.01208472e-01 -4.20626879e-01 -2.50590473e-01 -1.42358840e+00 5.78327179e-01 3.24351072e-01 1.21414162e-01 -5.81433415e-01 4.60495688e-02 5.48930526e-01 -5.04948478e-03 2.60425568e-01 3.40083204e-02 -8.60458538e-02 -1.66000277e-01 -6.57672882e-01 -2.10497845e-02 6.63268685e-01 6.85826480e-01 2.24042118e-01 -5.00192344e-01 -1.93409517e-01 9.75371063e-01 7.47433662e-01 3.38447541e-01 5.56091070e-01 -8.85274112e-01 6.26296937e-01 3.67874444e-01 2.52029318e-02 -1.17338693e+00 -3.92918795e-01 -1.45923868e-01 -1.03863144e+00 -8.02949741e-02 5.79222977e-01 -2.08515614e-01 -9.36453462e-01 1.71732330e+00 4.22264516e-01 2.48934388e-01 1.54183373e-01 1.05218232e+00 1.16999710e+00 5.63318372e-01 1.15991555e-01 -2.93500602e-01 1.24261785e+00 -6.73751771e-01 -9.27125633e-01 -1.39909118e-01 2.61884332e-01 -9.93838668e-01 4.74866778e-01 6.41071439e-01 -1.01883936e+00 -2.36108825e-01 -8.43618274e-01 2.14291453e-01 2.00823508e-02 6.01276159e-02 2.07739696e-01 2.55514652e-01 -5.69456637e-01 3.80457789e-01 -9.03387725e-01 -1.02112800e-01 4.91282076e-01 3.90877306e-01 -6.09409571e-01 -6.23233497e-01 -1.11357868e+00 7.92676330e-01 3.41196418e-01 4.06158626e-01 -9.87234712e-01 -4.03435677e-01 -9.67124820e-01 -2.60646731e-01 6.37014747e-01 -6.12388432e-01 1.20727217e+00 -9.24787581e-01 -1.36484206e+00 6.62019074e-01 -1.00044534e-01 -3.38500291e-02 6.94460392e-01 -1.82697281e-01 -1.47546470e-01 2.74815410e-01 -1.47725165e-01 4.02578801e-01 9.59082901e-01 -1.72087181e+00 -5.87209284e-01 -4.98566389e-01 -1.10111274e-01 3.17414939e-01 1.62910316e-02 8.69965088e-03 -6.63119078e-01 -5.83961308e-01 3.80700916e-01 -9.71793771e-01 -3.71219426e-01 -1.39426272e-02 -4.93345857e-01 -6.87346756e-02 4.15145129e-01 -8.58487308e-01 9.32507694e-01 -2.30712724e+00 7.86091805e-01 4.11361665e-01 3.88443321e-01 -4.90239672e-02 -9.31622237e-02 3.26505631e-01 2.30886430e-01 2.10146308e-02 -4.28594291e-01 -6.94400966e-01 -2.10205451e-01 3.45293254e-01 1.43046565e-02 6.50289953e-01 2.03989469e-03 3.90008420e-01 -1.12830830e+00 -8.65544796e-01 1.28733486e-01 7.47591794e-01 -1.71603918e-01 4.11346614e-01 -1.32494839e-02 9.67841446e-01 -4.14349765e-01 8.13612759e-01 4.86867845e-01 -2.13241279e-01 3.11998516e-01 -5.61252415e-01 4.49384630e-01 -2.13944241e-01 -1.35648763e+00 2.15456963e+00 -5.48436701e-01 4.33931142e-01 1.10372722e-01 -9.21088576e-01 5.42989492e-01 6.68619931e-01 6.88243926e-01 -3.64656568e-01 4.97040182e-01 3.53815824e-01 -6.32531196e-02 -7.78700829e-01 4.59724426e-01 -2.69319981e-01 -1.71306819e-01 2.78806388e-01 2.49640197e-01 -6.19136542e-02 -3.16702798e-02 2.95793563e-01 9.25332189e-01 -2.05090120e-01 3.43096614e-01 4.22313958e-01 4.64461982e-01 -2.55622119e-01 5.11588991e-01 5.98245621e-01 -1.99353725e-01 9.14039433e-01 6.76108539e-01 6.55792877e-02 -5.28584659e-01 -1.00965250e+00 2.67031696e-02 7.77869463e-01 5.21719635e-01 -3.27134669e-01 -3.11678767e-01 -9.71133769e-01 -1.82359070e-01 3.39656174e-01 -5.44670045e-01 -1.80340752e-01 -2.61892259e-01 -6.87430382e-01 2.43464664e-01 5.33247709e-01 -3.36596854e-02 -8.58372808e-01 -3.55268449e-01 1.01094306e-01 -7.21497715e-01 -1.35799015e+00 -4.28841233e-01 -2.96432264e-02 -7.63403714e-01 -1.08042443e+00 -8.23443353e-01 -5.82994938e-01 8.57842803e-01 1.66449547e-01 9.75263953e-01 -9.41667855e-02 -1.24854341e-01 6.26255989e-01 -4.19555724e-01 -1.98919028e-01 -5.56639612e-01 -5.18155992e-02 -2.30611563e-01 3.58419776e-01 -1.42187431e-01 -2.39743069e-01 -4.37631071e-01 3.28733504e-01 -1.24740577e+00 -9.25805978e-03 7.05590427e-01 1.02846074e+00 7.78993666e-01 9.46188644e-02 4.99500692e-01 -9.33571577e-01 5.75617373e-01 -9.31802690e-01 -2.59147316e-01 3.04782838e-01 7.95567036e-02 -1.99559075e-03 2.60907024e-01 -6.57428980e-01 -1.15389574e+00 3.33836466e-01 1.46834198e-02 -5.79343438e-01 -1.77186713e-01 1.10875690e+00 -2.72969097e-01 2.26279438e-01 4.53586012e-01 -5.18709831e-02 2.49981701e-01 -3.19834769e-01 3.58408093e-01 8.01951766e-01 6.58140361e-01 -6.75685108e-01 4.55391824e-01 4.23011452e-01 -5.21599576e-02 -5.33972383e-01 -7.57223248e-01 -4.92500901e-01 -3.60877156e-01 -3.69353652e-01 6.21959329e-01 -1.01636076e+00 -5.25636971e-01 5.02089322e-01 -1.30280268e+00 1.76242352e-01 -1.00741507e-02 6.75919414e-01 -4.58999932e-01 4.33505803e-01 -4.02859002e-01 -8.90491426e-01 -9.13284421e-02 -1.74982464e+00 1.23076546e+00 3.98269027e-01 -2.37657040e-01 -9.72399831e-01 1.74175017e-02 6.16038799e-01 7.88482279e-02 4.19238180e-01 7.09015429e-01 -7.66126871e-01 -3.79549593e-01 -5.96094549e-01 -2.04817757e-01 3.53732973e-01 3.33241284e-01 -1.90296337e-01 -9.75695074e-01 -1.43457800e-01 -1.17292553e-01 -4.09177721e-01 7.76702642e-01 4.19127464e-01 1.26949847e+00 -4.14475687e-02 -3.60954314e-01 1.10975273e-01 1.17363501e+00 -1.04785837e-01 4.39541489e-01 -1.00284621e-01 7.57912397e-01 8.40740979e-01 7.74706423e-01 5.92059076e-01 4.08557385e-01 4.27434921e-01 7.12111115e-01 -2.31381040e-02 1.36032879e-01 -6.10060543e-02 2.43989289e-01 7.60318696e-01 -1.10290870e-01 -3.90350968e-01 -9.25114214e-01 5.70780337e-01 -2.33022571e+00 -5.71558595e-01 2.62614459e-01 2.42601085e+00 8.58711302e-01 -1.27021179e-01 -6.74999028e-04 -8.26894119e-02 8.32471609e-01 8.10526386e-02 -3.77237678e-01 3.70171607e-01 2.21582465e-02 -3.17294687e-01 1.80255622e-01 3.14146936e-01 -1.13298213e+00 4.43144888e-01 5.36298513e+00 7.90899277e-01 -9.33569372e-01 1.89812303e-01 6.45786583e-01 -3.98427248e-02 -3.91066521e-01 -2.94900447e-01 -2.05676615e-01 4.58564579e-01 6.07497752e-01 -4.32396270e-02 2.23073184e-01 4.15912509e-01 5.67760468e-02 -4.50496972e-01 -1.16115570e+00 1.31621528e+00 3.44754398e-01 -1.12709785e+00 -1.15532190e-01 -6.13587797e-02 6.95208132e-01 -4.46968004e-02 1.66697115e-01 -5.32562323e-02 1.23633966e-01 -1.21360183e+00 6.08298898e-01 9.01386380e-01 5.06234407e-01 -7.61027157e-01 1.35886240e+00 3.54047745e-01 -9.12780166e-01 1.64436996e-02 5.32680601e-02 7.79526234e-01 3.84087741e-01 5.82066536e-01 -6.71188772e-01 9.08000469e-01 5.56031883e-01 7.40573704e-01 -4.28069949e-01 1.27143681e+00 -1.50062218e-01 3.58410150e-01 -3.46001923e-01 4.17182386e-01 -1.48473278e-01 2.51101285e-01 6.93778038e-01 1.01674938e+00 3.02985609e-01 -2.52868645e-02 3.84614617e-01 4.87831593e-01 -3.63376319e-01 6.67890161e-02 -5.25379717e-01 -2.68343419e-01 2.88020670e-01 1.32006991e+00 -5.82335055e-01 -2.18824178e-01 -4.03563172e-01 6.69743001e-01 9.88189057e-02 3.32710683e-01 -7.05014944e-01 3.31719965e-02 3.34277719e-01 -2.08332703e-01 -5.62231690e-02 -7.80827329e-02 -1.90125793e-01 -1.09419298e+00 1.54597610e-01 -1.06094122e+00 7.30107903e-01 -5.75931728e-01 -1.70961368e+00 6.96608961e-01 4.09753919e-02 -1.53181493e+00 -3.53609741e-01 -4.23135370e-01 -2.21914172e-01 8.08637321e-01 -1.35057282e+00 -1.15525496e+00 -4.81450200e-01 6.21392190e-01 4.95899022e-01 -1.81056306e-01 6.08239889e-01 3.24682117e-01 -4.06366497e-01 4.21892822e-01 -9.76219028e-02 3.18576396e-02 1.01725817e+00 -1.09002841e+00 -5.70319593e-01 4.95870978e-01 -2.40547191e-02 3.22688013e-01 7.02398419e-01 -6.05063558e-01 -1.57748520e+00 -7.24314868e-01 2.78216243e-01 -3.06141078e-01 6.15830719e-01 1.62173092e-01 -9.96005714e-01 3.90079170e-01 2.49832928e-01 2.13033125e-01 9.55802977e-01 -2.57452298e-02 -2.78157264e-01 -7.60039175e-03 -1.22164547e+00 4.15321112e-01 5.12473822e-01 -4.33499098e-01 -4.18073595e-01 3.28210890e-01 4.98823047e-01 -7.85928369e-01 -1.01035273e+00 5.57830334e-01 6.34342790e-01 -6.64769113e-01 7.12403655e-01 -5.81674695e-01 6.73798978e-01 -3.63075882e-01 -4.97182161e-01 -1.58263361e+00 4.42551613e-01 -4.86225277e-01 -1.80925325e-01 1.12126744e+00 4.28495705e-01 -2.91347265e-01 3.71793449e-01 7.09846318e-01 -6.77971467e-02 -6.88871920e-01 -1.05174839e+00 -1.62628993e-01 -2.24255174e-01 -6.80675924e-01 2.47077391e-01 6.33364916e-01 1.94282860e-01 1.51665702e-01 -6.02113605e-01 4.35332954e-01 6.76824033e-01 -5.00987694e-02 5.44703126e-01 -1.03320754e+00 -3.30068320e-01 -2.21189007e-01 -5.46060383e-01 -7.00594187e-01 2.27256626e-01 -7.81337798e-01 5.73527992e-01 -1.68676090e+00 4.93155807e-01 -1.54868454e-01 -4.56882000e-01 3.31618071e-01 -3.83352846e-01 9.96147767e-02 3.92489493e-01 1.49974689e-01 -7.51270831e-01 6.15240753e-01 1.17675602e+00 -4.14486140e-01 -1.00766741e-01 3.00661325e-01 -6.48373902e-01 8.51792693e-01 4.47411984e-01 -5.68208039e-01 -3.45463276e-01 -3.71698320e-01 3.03032130e-01 4.23527896e-01 4.06747371e-01 -6.08073592e-01 4.60339159e-01 -1.45043269e-01 2.32831419e-01 -4.68180269e-01 4.82896507e-01 -1.14739764e+00 5.72239608e-03 -4.51054610e-02 -4.15735811e-01 -2.49870330e-01 1.26203105e-01 9.50084329e-01 -6.31939948e-01 -3.38185638e-01 6.84971273e-01 -6.05856627e-02 -4.24116194e-01 1.57263398e-01 -3.20785284e-01 6.82658777e-02 7.62808561e-01 3.25445175e-01 -3.26594025e-01 -6.29139543e-01 -1.06763792e+00 4.54777509e-01 1.72860309e-01 5.12001395e-01 9.74612355e-01 -1.27894163e+00 -7.93023586e-01 -2.47592017e-01 3.59758019e-01 3.61685008e-01 6.39335513e-01 1.37946260e+00 -5.15845418e-02 -2.67463267e-01 6.00488558e-02 -9.65380371e-01 -1.50530541e+00 2.91601837e-01 2.68903792e-01 -3.18400532e-01 -3.11959326e-01 4.56430376e-01 6.87835068e-02 -4.55614328e-01 4.95721757e-01 -4.39804792e-02 -4.02974308e-01 3.21534216e-01 5.58566093e-01 2.33269751e-01 -6.13350905e-02 -8.16284180e-01 -3.35858405e-01 4.05805677e-01 -1.10199302e-01 -3.03577781e-01 1.19673049e+00 -2.89592683e-01 -1.37115330e-01 8.41129243e-01 1.08233595e+00 -6.89500794e-02 -1.02039349e+00 -5.75578570e-01 -2.35560387e-01 -5.45213163e-01 1.06158972e-01 -8.14427972e-01 -1.31968856e+00 7.62317002e-01 7.11346447e-01 -9.87486243e-02 1.20957828e+00 4.91382986e-01 6.63095653e-01 9.28094983e-02 2.29949206e-01 -1.08133674e+00 2.21737042e-01 1.13640316e-01 9.89609778e-01 -1.81650567e+00 -1.65454336e-02 -4.81864512e-01 -1.12499750e+00 1.12924755e+00 3.18966091e-01 3.70165616e-01 7.09151804e-01 1.36674404e-01 2.35213101e-01 -1.58889398e-01 -4.63809729e-01 -1.63189098e-01 7.17177570e-01 4.19788420e-01 3.69970798e-01 7.06884861e-02 1.93460938e-02 7.92912841e-01 3.77688736e-01 -7.12114722e-02 4.49175328e-01 1.06301653e+00 2.07295660e-02 -9.39536035e-01 -6.33900344e-01 3.69804800e-01 -5.11433005e-01 2.71849960e-01 -1.44714013e-01 4.51295733e-01 -3.93894911e-02 1.10627878e+00 -2.65402466e-01 -4.33024466e-01 2.95127958e-01 -1.09098986e-01 5.10485768e-01 -5.13810277e-01 -3.27896059e-01 5.50647557e-01 8.87232088e-03 -5.44746876e-01 -8.12121451e-01 -8.00812900e-01 -1.30243039e+00 1.73907325e-01 -1.27731785e-01 -8.89497846e-02 8.54811847e-01 1.21584380e+00 1.82198733e-01 8.09151113e-01 5.59157014e-01 -1.03644645e+00 -4.39139009e-01 -8.98324788e-01 -4.17923898e-01 4.55686033e-01 4.30851728e-01 -8.33144963e-01 -2.69081086e-01 3.29110697e-02]	[12.949098587036133, 4.856298446655273]
e9232959-f946-4541-a746-bc36eac7ba48	contrastive-deep-supervision	2207.05306	null	https://arxiv.org/abs/2207.05306v1	https://arxiv.org/pdf/2207.05306v1.pdf	Contrastive Deep Supervision	The success of deep learning is usually accompanied by the growth in neural network depth. However, the traditional training method only supervises the neural network at its last layer and propagates the supervision layer-by-layer, which leads to hardship in optimizing the intermediate layers. Recently, deep supervision has been proposed to add auxiliary classifiers to the intermediate layers of deep neural networks. By optimizing these auxiliary classifiers with the supervised task loss, the supervision can be applied to the shallow layers directly. However, deep supervision conflicts with the well-known observation that the shallow layers learn low-level features instead of task-biased high-level semantic features. To address this issue, this paper proposes a novel training framework named Contrastive Deep Supervision, which supervises the intermediate layers with augmentation-based contrastive learning. Experimental results on nine popular datasets with eleven models demonstrate its effects on general image classification, fine-grained image classification and object detection in supervised learning, semi-supervised learning and knowledge distillation. Codes have been released in Github.	['Kaisheng Ma', 'Runpei Dong', 'Junbo Zhang', 'Xin Chen', 'Linfeng Zhang']	2022-07-12	null	null	null	null	['fine-grained-image-classification']	['computer-vision']	[ 3.62429082e-01 3.98091644e-01 -2.94062048e-01 -6.79735422e-01 -5.52202389e-02 -3.02281708e-01 5.98115504e-01 7.69587457e-02 -6.67937696e-01 6.97771430e-01 -5.82280234e-02 -1.52824402e-01 3.66351679e-02 -7.68553972e-01 -7.82172740e-01 -8.81935954e-01 4.37242277e-02 2.53462374e-01 3.26636583e-01 -5.37517965e-02 1.22758985e-01 6.36025071e-01 -1.48948884e+00 5.47970951e-01 6.81647480e-01 1.33162034e+00 3.83924484e-01 4.27421778e-01 -1.52275905e-01 1.12992239e+00 -4.47511077e-01 -3.73174429e-01 1.95606068e-01 -1.70230702e-01 -9.57470298e-01 4.57784198e-02 4.20165747e-01 -2.15621397e-01 -9.19741765e-02 1.18147147e+00 2.86211103e-01 -1.72079429e-01 6.03366256e-01 -1.29323184e+00 -6.65421784e-01 4.58650351e-01 -5.82216024e-01 3.15271407e-01 -2.57153898e-01 -4.81663831e-03 1.05084276e+00 -9.65191841e-01 1.93810388e-01 1.17764938e+00 7.90086687e-01 4.76339519e-01 -9.97133672e-01 -6.64162874e-01 5.02449274e-01 1.73255891e-01 -1.19731581e+00 -2.78479218e-01 7.06080556e-01 -2.66371042e-01 8.36460412e-01 -6.14920072e-02 3.90094578e-01 9.22593832e-01 -4.01683785e-02 9.98943210e-01 1.19238520e+00 -5.21835864e-01 -6.76406622e-02 5.84522963e-01 3.41321081e-01 9.98905957e-01 2.70884752e-01 3.77389938e-01 -3.64502668e-01 2.81865090e-01 5.19348383e-01 1.46417573e-01 1.04673970e-02 -1.65727556e-01 -6.98085666e-01 8.22503984e-01 9.28015471e-01 1.81270137e-01 -3.64213526e-01 -2.58210246e-02 5.01256227e-01 3.69854718e-01 5.73542655e-01 3.76230866e-01 -9.39702153e-01 3.40167314e-01 -8.73343587e-01 -1.63859189e-01 6.76427424e-01 7.26027548e-01 1.08163106e+00 4.53870110e-02 -1.21024631e-01 9.23521757e-01 4.43375975e-01 1.76036078e-03 5.79238176e-01 -6.67653203e-01 4.46465671e-01 8.77680600e-01 -3.93445313e-01 -5.55641711e-01 -3.72116029e-01 -9.84737694e-01 -9.66209590e-01 5.93930602e-01 2.28285387e-01 -1.38566777e-01 -1.17115831e+00 1.55552948e+00 2.71976709e-01 5.28099462e-02 1.40727252e-01 7.41077602e-01 8.92410636e-01 5.28906345e-01 2.44913489e-01 3.80546562e-02 1.07934070e+00 -1.65343845e+00 -4.80799049e-01 -4.28523302e-01 6.73972368e-01 -5.52316070e-01 1.16226077e+00 4.38074678e-01 -9.96126771e-01 -9.86658990e-01 -1.10749209e+00 -1.50886759e-01 -7.72521377e-01 3.71904552e-01 6.63422823e-01 5.00647485e-01 -1.03974831e+00 6.32585824e-01 -6.67533457e-01 -4.89300638e-02 9.66105342e-01 5.24830043e-01 -3.06333542e-01 -1.07497489e-02 -1.11883092e+00 1.02702260e+00 8.09694290e-01 3.03689957e-01 -1.22042608e+00 -6.62864268e-01 -7.48710215e-01 1.73858345e-01 2.62872130e-01 -5.40757835e-01 1.12440705e+00 -1.63101530e+00 -1.53967869e+00 1.12076664e+00 9.19945166e-02 -4.43908960e-01 4.13639694e-01 -2.98566818e-01 -4.50351052e-02 2.23952979e-02 2.06220850e-01 9.41721618e-01 9.66636240e-01 -1.23971951e+00 -1.00900257e+00 -5.09066403e-01 3.42164338e-01 2.48970270e-01 -4.63835567e-01 -1.52759284e-01 -1.97911382e-01 -6.78893983e-01 3.56354415e-02 -7.62521982e-01 -2.65421718e-01 4.37000394e-03 -3.56736392e-01 -4.06552583e-01 1.05854881e+00 -4.86011535e-01 8.03015172e-01 -2.34269810e+00 9.93345827e-02 6.18528612e-02 1.31898567e-01 4.20792788e-01 -1.99901715e-01 -1.48314923e-01 -2.59407341e-01 -8.58818516e-02 -2.43823439e-01 -5.63133836e-01 -1.73905820e-01 3.29202890e-01 -2.35531509e-01 3.59010071e-01 5.71302116e-01 1.02835619e+00 -7.96736956e-01 -4.44606721e-01 1.53316721e-01 4.12185371e-01 -6.22891247e-01 3.44865412e-01 -1.25984982e-01 3.61382067e-01 -3.09227765e-01 6.84086561e-01 6.27627671e-01 -5.08878887e-01 -2.22824231e-01 -2.23373160e-01 -1.33264199e-01 3.45840007e-01 -8.12871754e-01 1.62836719e+00 -4.65878218e-01 5.33074141e-01 1.23693347e-01 -1.63429308e+00 7.42004514e-01 2.36447956e-02 -1.45861702e-02 -7.44389296e-01 8.81855264e-02 1.44305855e-01 4.74183746e-02 -3.92756909e-01 2.20444068e-01 -2.36729458e-01 1.10099278e-01 1.34011909e-01 2.40198091e-01 8.75897482e-02 4.83585894e-02 -5.96742518e-03 5.96546292e-01 3.63820702e-01 9.55930203e-02 -1.94992170e-01 6.65165484e-01 1.12594189e-02 3.91613185e-01 6.71639323e-01 -1.10133305e-01 3.49140614e-01 4.50408638e-01 -5.02876222e-01 -7.81164587e-01 -9.38529849e-01 -2.81261891e-01 1.62820125e+00 -2.74328608e-02 -1.57080770e-01 -8.03296387e-01 -1.17754471e+00 1.30250119e-03 3.52515399e-01 -9.87614393e-01 -4.50905919e-01 -3.31855446e-01 -8.13252032e-01 6.01214647e-01 7.11086094e-01 1.02935064e+00 -1.21065712e+00 -4.70844239e-01 4.07599583e-02 2.51876444e-01 -1.10420287e+00 -4.24593799e-02 8.50339592e-01 -1.17939281e+00 -9.95244384e-01 -7.00066507e-01 -1.00416195e+00 1.06309175e+00 1.07163481e-01 1.03173590e+00 3.60845238e-01 -3.36764455e-01 -2.80574337e-02 -3.58701050e-01 -5.80656290e-01 -2.24403530e-01 4.26734298e-01 -1.81412831e-01 8.72772411e-02 3.50880444e-01 -3.99895489e-01 -5.37330985e-01 1.88823000e-01 -7.74902225e-01 1.20926917e-01 9.84972239e-01 1.11635709e+00 5.00273168e-01 1.86344013e-01 7.43218720e-01 -1.09842861e+00 1.57101750e-01 -3.00528944e-01 -5.06193697e-01 1.58767551e-01 -6.86179280e-01 3.07181329e-01 7.28247106e-01 -3.00888538e-01 -1.30068576e+00 1.52068585e-01 -2.54969031e-01 -2.89049953e-01 -3.52213234e-01 5.99349260e-01 -1.26348630e-01 -9.30761471e-02 6.37848258e-01 2.29925513e-01 -6.66658133e-02 -5.98331749e-01 2.07034677e-01 5.39588153e-01 3.76496822e-01 -3.54840279e-01 6.45971656e-01 5.16817987e-01 -1.32493824e-01 -6.52168989e-01 -1.58038759e+00 -2.88016558e-01 -8.81477952e-01 1.07045934e-01 8.05197656e-01 -1.01601934e+00 -3.68043065e-01 6.86550915e-01 -9.95641947e-01 -5.21399260e-01 -5.81666410e-01 3.27297807e-01 -1.20273471e-01 -1.44159030e-02 -5.51714480e-01 -4.21805203e-01 -1.69028759e-01 -1.06918943e+00 9.55921173e-01 3.02602053e-01 1.23289637e-01 -1.21334291e+00 -2.50843853e-01 4.11650360e-01 3.43230546e-01 -1.96609050e-02 7.83060372e-01 -6.03432596e-01 -4.51876998e-01 -1.12884633e-01 -6.01045430e-01 1.01165795e+00 1.76853448e-01 -3.11840355e-01 -1.44124317e+00 -2.67904133e-01 1.23515641e-02 -8.12813997e-01 1.37790954e+00 3.69168580e-01 1.45581377e+00 -2.07714394e-01 -2.76079029e-01 9.10752416e-01 1.29976237e+00 -1.88410744e-01 5.45932591e-01 5.75820565e-01 8.02166462e-01 7.36364067e-01 4.61377591e-01 9.95697007e-02 2.37456366e-01 2.69121051e-01 6.41983032e-01 -4.73872125e-01 -2.98712343e-01 -1.07899494e-01 2.74537891e-01 5.11772275e-01 -1.39422461e-01 2.19690517e-01 -6.79657876e-01 4.19852883e-01 -1.53530574e+00 -6.92239940e-01 4.30319495e-02 1.91080403e+00 1.06535161e+00 5.07225215e-01 -1.15633048e-01 3.63598585e-01 4.74731386e-01 1.56646475e-01 -5.72731376e-01 -4.10299867e-01 -7.30799064e-02 2.00927377e-01 5.51958740e-01 4.98163253e-01 -1.24029279e+00 1.08041894e+00 6.09005165e+00 7.74956822e-01 -1.47795093e+00 3.92363876e-01 8.75086010e-01 6.97370172e-02 1.37647569e-01 -1.33024246e-01 -1.20978284e+00 3.88599694e-01 7.78745413e-01 4.81216252e-01 5.93171194e-02 1.05020571e+00 9.34256334e-03 -1.48445398e-01 -1.16535926e+00 7.85955787e-01 -7.82447308e-02 -1.26472294e+00 2.58599341e-01 -1.74096879e-02 8.54383111e-01 2.27567405e-01 2.21441567e-01 6.60535395e-01 1.52389377e-01 -1.22062337e+00 6.21670425e-01 2.36763820e-01 6.70077443e-01 -7.48734951e-01 8.56309950e-01 5.26055753e-01 -9.55608904e-01 -2.76365280e-01 -5.15024304e-01 -3.97350341e-01 -2.94569492e-01 5.56598842e-01 -7.28234470e-01 2.96979457e-01 8.09523463e-01 9.01320755e-01 -7.43111074e-01 7.34838903e-01 -5.68420708e-01 6.89417064e-01 -1.02638960e-01 1.75576866e-01 6.52027428e-01 9.62482020e-03 -1.32179968e-02 1.40726316e+00 -2.90510058e-01 -1.00112386e-01 2.05804050e-01 7.20158041e-01 -3.00019979e-01 -1.23663098e-01 -4.05966729e-01 6.83625937e-02 -5.20734452e-02 1.32713497e+00 -6.40510499e-01 -5.19328773e-01 -5.07540345e-01 1.12188268e+00 6.19624794e-01 4.31424201e-01 -7.65945971e-01 -4.58991319e-01 3.50176990e-01 1.05616108e-01 3.08355600e-01 1.33369327e-01 -6.51960254e-01 -9.04308856e-01 2.23273486e-02 -5.86336792e-01 4.31976974e-01 -4.44768876e-01 -1.14192688e+00 5.79976201e-01 -1.59758314e-01 -8.00885499e-01 7.93492794e-02 -9.70747232e-01 -6.10021651e-01 9.65359747e-01 -2.29089665e+00 -1.19639611e+00 -3.26563388e-01 8.12558711e-01 5.75368226e-01 -4.09123182e-01 7.01017976e-01 4.65475529e-01 -5.97885370e-01 6.84934497e-01 -1.83496401e-02 2.49765754e-01 4.67188239e-01 -1.38370478e+00 -1.22195683e-01 4.22617286e-01 -4.65011969e-02 4.11793292e-01 3.56903523e-01 -1.65617839e-01 -7.35449255e-01 -1.30651331e+00 8.01791251e-01 -1.81777358e-01 4.96396601e-01 -2.90880740e-01 -1.01400912e+00 6.87113464e-01 2.36053601e-01 4.84749675e-01 5.84062576e-01 1.57268524e-01 -4.26935822e-01 -4.70284790e-01 -9.68964517e-01 9.56799462e-02 8.63450050e-01 -6.91012025e-01 -7.50412762e-01 3.30665976e-01 6.46387577e-01 -1.60244584e-01 -4.81762230e-01 6.49308503e-01 4.21363950e-01 -7.86968350e-01 9.66297626e-01 -7.80547798e-01 6.19440198e-01 -1.74744204e-01 4.75327261e-02 -1.22682345e+00 -3.12525213e-01 1.16502449e-01 -1.59373194e-01 9.78744507e-01 6.40293479e-01 -6.35318875e-01 1.06662846e+00 7.01744929e-02 -3.47321898e-01 -9.39308405e-01 -5.47971964e-01 -6.69546902e-01 1.69574261e-01 -2.49705743e-02 1.50175124e-01 1.14044082e+00 -5.28324962e-01 7.28133261e-01 -1.16208434e-01 2.34709993e-01 6.69541061e-01 -1.14594884e-01 4.60900128e-01 -1.49678588e+00 -4.23538864e-01 -3.95952076e-01 -3.13605130e-01 -1.19155931e+00 2.30662256e-01 -1.04655814e+00 1.65358428e-02 -1.46687341e+00 3.47617984e-01 -7.29957640e-01 -6.06113374e-01 7.96073496e-01 -2.62111723e-01 4.29366469e-01 -9.79194641e-02 1.39983296e-01 -6.80199385e-01 5.44465303e-01 1.38917232e+00 -2.38857135e-01 -1.77686270e-02 1.77619308e-01 -7.22391784e-01 1.11418104e+00 9.30534780e-01 -5.29016018e-01 -5.95904648e-01 -4.94795889e-01 2.53578186e-01 -5.79566061e-01 5.56140184e-01 -8.86137903e-01 2.23643512e-01 1.09919541e-01 6.72104895e-01 -5.62590480e-01 1.97186962e-01 -9.29264426e-01 -4.83942568e-01 6.68038845e-01 -5.95820367e-01 -4.07674640e-01 3.12028944e-01 2.71557510e-01 -5.55173516e-01 -5.87021470e-01 1.09427631e+00 -2.83076376e-01 -8.57169688e-01 3.10980767e-01 -5.49418740e-02 8.58734921e-02 9.47495401e-01 -3.94081652e-01 -1.84856102e-01 1.75247908e-01 -9.89824772e-01 1.81080028e-01 -1.88049991e-02 3.80667567e-01 5.60784638e-01 -1.16958511e+00 -7.38323808e-01 3.55659753e-01 5.21275433e-05 3.74603778e-01 -8.41065794e-02 8.86724710e-01 -3.21982414e-01 3.91660333e-01 -3.55106711e-01 -7.52957702e-01 -1.16632104e+00 5.24441242e-01 4.66695845e-01 -4.30819243e-01 -2.85138935e-01 1.33193767e+00 6.58150077e-01 -5.69453478e-01 6.94996536e-01 -3.26355189e-01 -3.32844377e-01 1.95622280e-01 4.86867040e-01 9.61029530e-02 1.08978204e-01 -3.17498684e-01 -3.06161642e-01 3.67138475e-01 -4.79697734e-01 3.22515011e-01 1.37566638e+00 -6.11435287e-02 -2.00217962e-01 4.42992151e-01 1.65296078e+00 -4.89496380e-01 -1.56830013e+00 -4.78681058e-01 2.15490565e-01 -4.31816913e-02 3.62617761e-01 -9.78801668e-01 -1.37459469e+00 1.25739694e+00 6.73976898e-01 1.28961146e-01 1.25299203e+00 1.85773000e-02 4.37702537e-01 5.62717676e-01 1.42262042e-01 -1.25566137e+00 4.37774807e-01 7.55661547e-01 8.61381650e-01 -1.60786092e+00 -5.72315603e-02 -2.20691845e-01 -4.04802144e-01 9.55832183e-01 8.48206758e-01 -2.48199895e-01 8.48902524e-01 3.10037822e-01 -4.91252318e-02 -1.47963062e-01 -6.70656562e-01 -1.33945152e-01 2.91477382e-01 2.74680406e-01 5.73799908e-01 -1.70839489e-01 1.34857506e-01 5.13120174e-01 6.32125810e-02 3.46497111e-02 5.58604114e-03 9.39994276e-01 -6.11378729e-01 -9.89111662e-01 -1.57764539e-01 4.84256953e-01 -7.19283521e-01 -3.92038673e-01 -3.04424167e-01 6.81268454e-01 6.03297591e-01 5.27144432e-01 1.55778590e-03 -1.40408024e-01 2.34639943e-01 -5.15581518e-02 3.92030120e-01 -8.76605153e-01 -7.72125304e-01 -2.88290828e-01 -5.69052808e-02 -3.59441698e-01 -6.11747205e-01 -3.21198314e-01 -1.24980783e+00 6.00708425e-02 -5.09359837e-01 2.90663242e-01 6.27302468e-01 1.00308204e+00 9.56921354e-02 7.85992205e-01 6.18308306e-01 -8.57982457e-01 -6.43685222e-01 -1.02900052e+00 -4.78481174e-01 2.81702280e-01 6.29146278e-01 -6.83317840e-01 -4.60618675e-01 1.90856799e-01]	[9.487485885620117, 2.4082868099212646]
117a3240-9eae-400d-9c91-98ab97c52b66	asr-and-emotional-speech-a-word-level	2305.16065	null	https://arxiv.org/abs/2305.16065v2	https://arxiv.org/pdf/2305.16065v2.pdf	ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition	In Speech Emotion Recognition (SER), textual data is often used alongside audio signals to address their inherent variability. However, the reliance on human annotated text in most research hinders the development of practical SER systems. To overcome this challenge, we investigate how Automatic Speech Recognition (ASR) performs on emotional speech by analyzing the ASR performance on emotion corpora and examining the distribution of word errors and confidence scores in ASR transcripts to gain insight into how emotion affects ASR. We utilize four ASR systems, namely Kaldi ASR, wav2vec2, Conformer, and Whisper, and three corpora: IEMOCAP, MOSI, and MELD to ensure generalizability. Additionally, we conduct text-based SER on ASR transcripts with increasing word error rates to investigate how ASR affects SER. The objective of this study is to uncover the relationship and mutual impact of ASR and SER, in order to facilitate ASR adaptation to emotional speech and the use of SER in real world.	['Catherine Lai', 'Peter Bell', 'Ondrej Klejch', 'Zeyu Zhao', 'Yuanchao Li']	2023-05-25	null	null	null	null	['automatic-speech-recognition', 'speech-emotion-recognition']	['speech', 'speech']	[-1.05128892e-01 -8.61031413e-02 4.18689787e-01 -3.79621774e-01 -7.56124079e-01 -5.03273368e-01 5.81919700e-02 2.99781617e-02 -4.67333227e-01 4.17300045e-01 5.27469993e-01 -2.85301328e-01 3.72759849e-01 -4.22474779e-02 -1.65204436e-01 -2.48927563e-01 8.04487765e-02 -2.44929656e-01 -3.28091234e-01 -4.46496964e-01 -3.88212432e-03 3.52906018e-01 -1.31330180e+00 2.09954888e-01 6.74237609e-01 1.02804422e+00 -2.91988719e-02 9.55031991e-01 -9.16251764e-02 9.47003901e-01 -1.20785379e+00 -6.55743182e-01 -1.06123321e-01 -4.69577998e-01 -4.48904335e-01 8.19756463e-02 -3.80483627e-01 9.71798971e-02 -3.96689951e-01 8.68758798e-01 9.37702775e-01 5.18319190e-01 3.92284483e-01 -9.19157743e-01 -7.30203927e-01 6.44178152e-01 -3.99854183e-02 4.83043015e-01 5.64264655e-01 8.81155301e-03 9.14459229e-01 -1.05898130e+00 2.82036692e-01 1.05499327e+00 3.75912547e-01 7.10580528e-01 -7.54155874e-01 -7.12464988e-01 -5.91258928e-02 2.20094785e-01 -1.55851197e+00 -1.09441423e+00 8.94514203e-01 -1.58658549e-01 1.44740796e+00 3.22666556e-01 4.03079718e-01 1.59640014e+00 -1.65247008e-01 8.22000027e-01 9.25152719e-01 -5.15524626e-01 4.95282173e-01 6.19077206e-01 1.57778248e-01 8.10922831e-02 -4.91860479e-01 4.28766990e-03 -1.23618329e+00 -8.53063837e-02 9.77721065e-02 -6.51592433e-01 -4.42855775e-01 7.48918772e-01 -6.97798073e-01 6.28131032e-01 -2.72090405e-01 5.13164937e-01 -4.78256017e-01 -1.61991879e-01 7.79671967e-01 7.06485629e-01 8.16982508e-01 6.89888537e-01 -6.93930447e-01 -9.42936838e-01 -7.12195277e-01 -4.55212951e-01 6.85688734e-01 5.33145785e-01 1.72909513e-01 8.87909532e-01 4.59936485e-02 1.52295876e+00 3.56957406e-01 4.77489263e-01 1.00688720e+00 -5.38370490e-01 2.84523219e-01 2.45790616e-01 -2.24461675e-01 -9.00222540e-01 -1.28954738e-01 -3.78485620e-01 -4.68463182e-01 -2.01333001e-01 -3.46014291e-01 -4.58952487e-01 -5.44062495e-01 1.52449298e+00 -6.00358546e-02 7.15853870e-02 5.02309799e-01 8.42120826e-01 7.62338579e-01 9.09825742e-01 1.52095914e-01 -3.92384678e-01 1.13580179e+00 -6.07235789e-01 -1.11281049e+00 -3.37526947e-01 8.47695827e-01 -8.40318382e-01 1.39066672e+00 5.08035660e-01 -8.12654674e-01 -2.92323023e-01 -8.84202778e-01 2.47923091e-01 -4.23588067e-01 2.72178113e-01 1.50877744e-01 1.11744714e+00 -8.68986130e-01 1.94827374e-02 -6.50962889e-01 -2.96421617e-01 -1.64032951e-01 -1.35084435e-01 -3.63001227e-01 6.11464024e-01 -1.66192615e+00 1.04714084e+00 5.62622398e-02 2.35798404e-01 -2.83518136e-01 -5.54859281e-01 -9.88188684e-01 1.22038290e-01 1.37136597e-02 1.70479268e-01 1.40763950e+00 -1.29919672e+00 -2.03497624e+00 5.60262084e-01 -3.04287434e-01 -4.08304065e-01 3.53959575e-02 -3.00915807e-01 -1.12372720e+00 -1.34092957e-01 -7.30624020e-01 1.19117536e-01 6.10269487e-01 -9.89217758e-01 -1.23351812e-01 -2.87161410e-01 -7.76213884e-01 2.53780276e-01 -5.90309858e-01 6.58486426e-01 2.36249529e-02 -7.64834642e-01 -2.24214762e-01 -6.73821032e-01 1.66245326e-01 -7.50246942e-01 -1.97940245e-01 -2.59483814e-01 4.90382761e-01 -1.08961320e+00 1.72547483e+00 -2.59623647e+00 -1.04124568e-01 3.22041124e-01 -2.83991367e-01 5.15194416e-01 -2.29491860e-01 4.53865975e-01 -4.30140719e-02 3.26273888e-01 9.39847082e-02 -3.13062608e-01 2.40252972e-01 1.65969670e-01 -4.01720107e-01 1.17383569e-01 5.56751668e-01 5.51984489e-01 -4.41749573e-01 -2.83196211e-01 2.76399046e-01 7.92344034e-01 -3.42268050e-01 5.12442648e-01 2.07464918e-01 9.44973677e-02 -1.95520036e-02 5.64010024e-01 1.33270659e-02 3.36962223e-01 3.01513746e-02 -6.17117174e-02 -2.16119573e-01 6.64574921e-01 -9.63225126e-01 9.45853114e-01 -8.03726435e-01 1.00081801e+00 1.97509587e-01 -6.86645627e-01 1.45542169e+00 9.42155182e-01 1.88729629e-01 -8.62306476e-01 5.20472288e-01 1.84749246e-01 1.08217224e-01 -5.76692462e-01 8.67940068e-01 -2.12913409e-01 -1.38451636e-01 1.32392302e-01 1.72958046e-01 -5.59623204e-02 -2.62994260e-01 3.94521095e-03 1.07240367e+00 -5.97313046e-01 3.12037915e-01 3.80083859e-01 2.60806620e-01 -4.07212704e-01 4.73166406e-01 3.89686227e-01 -5.44129491e-01 5.89484274e-01 3.43122989e-01 1.39356047e-01 -6.07752442e-01 -8.96539032e-01 -1.95693187e-02 1.10418761e+00 -3.91438484e-01 -3.85346860e-01 -5.72201312e-01 -3.40837806e-01 -4.54135716e-01 1.22376096e+00 -3.55996281e-01 -4.24536794e-01 -4.93026823e-02 -5.64770579e-01 9.92738664e-01 4.00601506e-01 -4.29536179e-02 -1.39387202e+00 -2.59522110e-01 4.37609822e-01 -3.06378990e-01 -1.15483463e+00 -4.96926129e-01 3.78405601e-01 -1.05591089e-01 -4.41626340e-01 -3.84555846e-01 -2.51519769e-01 -8.12249165e-03 -1.24276847e-01 9.24691558e-01 -3.21830481e-01 -2.13972442e-02 5.58051944e-01 -9.98537898e-01 -4.38156545e-01 -7.31910944e-01 1.06866941e-01 3.38421255e-01 2.53662229e-01 6.76101625e-01 -3.87060255e-01 -3.90354618e-02 2.82458693e-01 -8.51974726e-01 -5.07374108e-01 3.41618419e-01 5.71927667e-01 1.30695060e-01 2.67879255e-02 9.84036088e-01 -5.01412868e-01 1.21869969e+00 -6.06257617e-01 2.45248456e-03 2.71571606e-01 -4.69254196e-01 -2.32315838e-01 4.80521739e-01 -5.84197998e-01 -1.25068355e+00 -4.43156958e-01 -6.57320201e-01 -4.64531809e-01 -1.11169294e-01 7.76768804e-01 -1.94986150e-01 3.15817714e-01 6.83298826e-01 1.89168587e-01 -2.09099919e-01 -2.40950942e-01 1.45326706e-03 1.69451666e+00 2.55170286e-01 -2.60349303e-01 2.23671436e-01 -4.75300938e-01 -9.91286576e-01 -1.47789991e+00 -6.03221297e-01 -5.55054247e-01 3.14832404e-02 -5.46356082e-01 6.73626721e-01 -9.33434188e-01 -5.27775109e-01 2.40543693e-01 -1.14729714e+00 -3.54445517e-01 -4.75024953e-02 8.35393667e-01 -2.43017808e-01 1.31505579e-01 -7.76756048e-01 -1.41722679e+00 -5.63595116e-01 -9.42437768e-01 6.98508441e-01 -2.74588433e-06 -9.67786074e-01 -7.96777368e-01 1.91789001e-01 4.26884353e-01 5.98775864e-01 -3.63983810e-01 4.67536300e-01 -1.04496384e+00 3.88036817e-01 -1.64202392e-01 2.34806135e-01 8.14375043e-01 3.38869393e-02 3.59250635e-01 -1.16434693e+00 9.25423428e-02 -5.10452539e-02 -5.33336997e-01 1.41756102e-01 7.32413605e-02 9.42461908e-01 -3.29849511e-01 5.39661884e-01 1.60555840e-01 7.98668683e-01 5.60204268e-01 7.23860264e-01 1.42643854e-01 1.60678610e-01 5.85159719e-01 5.65829992e-01 7.15376556e-01 1.34023264e-01 4.55570459e-01 -1.30957216e-01 2.25887373e-01 2.17565954e-01 -7.98338950e-02 9.33483303e-01 1.76878440e+00 3.80935609e-01 -6.64032876e-01 -9.44483459e-01 5.31559229e-01 -1.26181698e+00 -6.63502932e-01 1.14537753e-01 1.87565005e+00 8.35422575e-01 -1.03137299e-01 -1.15427881e-01 3.55915576e-01 5.37875712e-01 2.19562829e-01 -1.86657950e-01 -9.88177240e-01 -2.18691364e-01 1.75784111e-01 5.46985902e-02 3.73732358e-01 -4.63495761e-01 9.66973126e-01 6.04084969e+00 7.12033153e-01 -1.44303906e+00 8.51425752e-02 6.12714469e-01 -2.93302387e-01 -3.18521857e-01 -6.43913031e-01 -3.60891640e-01 5.30228317e-01 1.52984881e+00 -1.49625719e-01 6.71499848e-01 8.31022978e-01 5.54556966e-01 2.46726409e-01 -7.02440798e-01 1.17080522e+00 2.27786064e-01 -4.32889402e-01 -3.24462324e-01 -4.54599261e-01 1.32855311e-01 2.16469646e-01 1.40795365e-01 7.19107866e-01 1.37552246e-01 -9.47369158e-01 6.89418435e-01 1.04255989e-01 7.47355103e-01 -7.52364099e-01 8.26130092e-01 -3.35119776e-02 -7.93899775e-01 1.78162679e-01 1.56886748e-03 5.34559861e-02 1.75656170e-01 3.69649231e-01 -1.07995260e+00 1.02766111e-01 6.01903856e-01 2.34882757e-01 -1.87281609e-01 3.58215630e-01 -1.03338718e-01 1.35706472e+00 -2.23820776e-01 -3.66460770e-01 -8.95107388e-02 1.19525596e-01 5.45331478e-01 1.64390874e+00 4.92451966e-01 2.31198639e-01 -2.84699112e-01 3.89808774e-01 -2.68675953e-01 5.23783803e-01 -3.77915978e-01 -6.94433153e-01 9.61864173e-01 1.00651944e+00 -2.57666886e-01 8.17757659e-03 -3.78901929e-01 1.06345344e+00 3.27377021e-01 6.75740361e-01 -7.31170893e-01 -4.45731223e-01 1.09408414e+00 -2.85396844e-01 -1.50689870e-01 -3.90011519e-01 -2.70587802e-01 -1.10073864e+00 -2.94656008e-02 -1.30244493e+00 8.73829946e-02 -1.15299296e+00 -1.32684755e+00 9.62068260e-01 -6.39885783e-01 -8.20260167e-01 -1.34633124e-01 -3.94479007e-01 -5.69457114e-01 7.87866652e-01 -1.33884394e+00 -4.39112902e-01 3.50538827e-02 3.48403513e-01 8.53128493e-01 -3.99709016e-01 8.32812548e-01 4.95410949e-01 -9.32390511e-01 1.01366365e+00 -1.68671697e-01 1.78904235e-01 8.55473638e-01 -8.57440472e-01 2.11333156e-01 6.28696203e-01 1.93213224e-01 3.70954275e-01 7.67447412e-01 -4.00550425e-01 -1.17056215e+00 -9.96563554e-01 9.55193520e-01 -2.96959609e-01 9.12950754e-01 -2.94957608e-01 -1.11861563e+00 5.36856890e-01 2.57494360e-01 -3.16434264e-01 1.15193760e+00 3.53427052e-01 -4.20714676e-01 -3.67706940e-02 -8.83595467e-01 7.00947225e-01 5.78417361e-01 -1.01844990e+00 -5.16628683e-01 -3.65107775e-01 9.01454747e-01 -1.02498025e-01 -9.95256126e-01 2.15095311e-01 4.12740499e-01 -6.65845990e-01 4.30358082e-01 -5.02381980e-01 2.26785168e-01 -3.40045057e-02 -5.42122543e-01 -1.83630788e+00 -8.97278916e-03 -7.48835742e-01 1.36925191e-01 1.74363923e+00 7.26300299e-01 -6.61663532e-01 2.18988001e-01 8.15023005e-01 -3.11767668e-01 -4.73659277e-01 -9.80778515e-01 -5.96062362e-01 -4.15208966e-01 -9.16196883e-01 3.15612763e-01 1.09948921e+00 4.17083621e-01 3.25008065e-01 -3.95628572e-01 4.33197916e-01 -2.22948879e-01 -7.52174258e-01 5.00315964e-01 -6.06871009e-01 -1.70876592e-01 -2.82355726e-01 -5.50669968e-01 -4.33039904e-01 5.13418853e-01 -6.66161060e-01 2.74268240e-01 -7.67651618e-01 -3.67948920e-01 -5.95165640e-02 -5.82500160e-01 3.77127081e-01 -2.20225409e-01 5.58010302e-03 2.20983610e-01 -3.15682173e-01 -5.32044470e-01 1.08611858e+00 3.29250515e-01 1.61650404e-01 -4.90477175e-01 -3.03024650e-01 -4.93085772e-01 4.87260103e-01 9.60813046e-01 -4.47442174e-01 -1.96468636e-01 -2.11554274e-01 2.62091488e-01 3.12393665e-01 -1.13515712e-01 -7.90728331e-01 3.58521380e-02 7.84255639e-02 2.80115679e-02 -1.96732238e-01 4.60494071e-01 -7.78725088e-01 1.27380699e-01 -3.83238107e-01 -6.32596672e-01 1.89034328e-01 3.63249987e-01 1.29893184e-01 -7.10206389e-01 -2.55774587e-01 6.08277321e-01 2.69737393e-01 -5.28597653e-01 -7.67741352e-02 -1.07615614e+00 2.98384786e-01 5.35432696e-01 -1.33945718e-01 -6.56450987e-02 -7.61681974e-01 -5.11642098e-01 4.48277034e-02 1.60283774e-01 6.35999560e-01 7.48348832e-01 -1.03371334e+00 -6.46585405e-01 3.36399257e-01 3.50690693e-01 -7.12910354e-01 4.00936365e-01 7.01812088e-01 -1.28684929e-02 3.51503422e-03 1.91620380e-01 -5.24915308e-02 -1.61392462e+00 5.78084104e-02 5.18485665e-01 2.44535759e-01 7.88573362e-03 8.68350744e-01 -2.95808524e-01 -4.32927340e-01 4.56260264e-01 7.35943466e-02 -1.22265622e-01 1.97011992e-01 3.53844404e-01 3.46358299e-01 3.35959494e-01 -5.83359540e-01 -3.03723842e-01 -1.78898767e-01 1.34533077e-01 -5.74788034e-01 1.07505524e+00 -4.96577561e-01 1.56894967e-01 9.69704390e-01 1.29196191e+00 3.99364859e-01 -6.35651350e-01 -4.08100970e-02 1.14927635e-01 -2.05139235e-01 2.92878747e-01 -8.19164157e-01 -7.55080581e-01 8.24329138e-01 4.17066813e-01 3.77648115e-01 1.07235420e+00 -1.32560253e-01 8.98406088e-01 3.67165864e-01 -6.04701117e-02 -1.61724830e+00 7.42060244e-02 8.15331757e-01 8.69895816e-01 -1.18244767e+00 -7.88728893e-01 8.71309265e-02 -1.31903756e+00 9.14133191e-01 4.98014122e-01 4.41750526e-01 7.09301889e-01 4.24421132e-01 7.91745365e-01 -2.18870584e-02 -1.06692028e+00 -1.12483367e-01 1.61492437e-01 2.99150676e-01 8.53919506e-01 1.46412224e-01 -8.53441209e-02 8.56703699e-01 -6.44577324e-01 -2.18107015e-01 5.82017779e-01 5.26359439e-01 -2.88766921e-01 -7.30920315e-01 -2.35814989e-01 3.26048464e-01 -8.59252095e-01 -2.25364059e-01 -8.08606088e-01 2.09805503e-01 -5.26337683e-01 1.42399943e+00 1.66329108e-02 -6.95217073e-01 5.41359901e-01 6.52971387e-01 -1.95700377e-01 -5.35390556e-01 -7.68981338e-01 -5.03343642e-02 6.27142489e-01 -2.96614796e-01 -9.36452374e-02 -4.65239435e-01 -1.10155642e+00 -3.38718928e-02 -6.33557796e-01 4.64906633e-01 1.14843225e+00 8.13360810e-01 4.72159326e-01 8.27868938e-01 8.73714745e-01 -2.09091410e-01 -4.61334288e-01 -1.32131839e+00 -7.29800403e-01 4.18532073e-01 2.54270613e-01 -1.64610326e-01 -7.73393869e-01 -2.28033252e-02]	[13.64093017578125, 5.836283206939697]
27131225-591c-4860-8e01-c7dfd24e00da	atrial-fibrillation-detection-using-deep	1903.11775	null	http://arxiv.org/abs/1903.11775v1	http://arxiv.org/pdf/1903.11775v1.pdf	Atrial Fibrillation Detection Using Deep Features and Convolutional Networks	Atrial fibrillation is a cardiac arrhythmia that affects an estimated 33.5 million people globally and is the potential cause of 1 in 3 strokes in people over the age of 60. Detection and diagnosis of atrial fibrillation (AFIB) is done noninvasively in the clinical environment through the evaluation of electrocardiograms (ECGs). Early research into automated methods for the detection of AFIB in ECG signals focused on traditional bio-medical signal analysis to extract important features for use in statistical classification models. Artificial intelligence models have more recently been used that employ convolutional and/or recurrent network architectures. In this work, significant time and frequency domain characteristics of the ECG signal are extracted by applying the short-time Fourier trans-form and then visually representing the information in a spectrogram. Two different classification approaches were investigated that utilized deep features in the spectrograms construct-ed from ECG segments. The first approach used a pretrained DenseNet model to extract features that were then classified using Support Vector Machines, and the second approach used the spectrograms as direct input into a convolutional network. Both approaches were evaluated against the MIT-BIH AFIB dataset, where the convolutional network approach achieved a classification accuracy of 93.16%. While these results do not surpass established automated atrial fibrillation detection methods, they are promising and warrant further investigation given they did not require any noise prefiltering, hand-crafted features, nor a reliance on beat detection.	['Sara Ross-Howe', 'H. R. Tizhoosh']	2019-03-28	null	null	null	null	['arrhythmia-detection', 'atrial-fibrillation-detection', 'electrocardiography-ecg']	['medical', 'medical', 'methodology']	[ 3.09445173e-01 -2.23426685e-01 2.07771719e-01 -2.39713177e-01 -5.58122873e-01 -6.88165009e-01 1.88576251e-01 4.09828156e-01 -4.72317576e-01 8.47243845e-01 8.25140551e-02 -7.49016225e-01 -3.92184973e-01 -6.37419581e-01 7.98183605e-02 -5.89201391e-01 -6.30419493e-01 -4.04215092e-03 -4.85104918e-01 5.65677062e-02 2.07480155e-02 8.94652903e-01 -1.15059519e+00 4.67939943e-01 7.86635339e-01 1.23350215e+00 -3.27440917e-01 1.12510288e+00 1.38692603e-01 4.47135061e-01 -1.08885384e+00 2.32135102e-01 9.77604538e-02 -8.38123798e-01 -4.54282433e-01 -2.25662544e-01 -3.33295837e-02 -4.00091568e-03 -2.64465928e-01 3.99194419e-01 1.07644856e+00 -4.07073736e-01 5.44890761e-01 -5.61474860e-01 -9.21017826e-02 3.37576807e-01 -1.73189715e-01 1.05023146e+00 3.26732576e-01 3.36643420e-02 5.91139317e-01 -1.04183578e+00 2.86611378e-01 5.93480110e-01 1.29938042e+00 1.40480787e-01 -1.24799752e+00 -5.71128070e-01 -6.15436912e-01 1.25619203e-01 -1.37233078e+00 -2.30340093e-01 9.43309486e-01 -5.58081567e-01 1.20379221e+00 3.88655335e-01 1.21659970e+00 7.61992872e-01 4.56760108e-01 3.76997948e-01 1.12527919e+00 -6.29274070e-01 7.79775828e-02 -2.00393111e-01 3.62645388e-01 5.83396435e-01 4.31663632e-01 4.26402509e-01 -3.47684622e-01 -6.75187290e-01 7.88942039e-01 1.06113903e-01 -5.82633197e-01 1.20325796e-01 -1.43100166e+00 8.15203488e-01 3.60384375e-01 7.22601831e-01 -7.81034589e-01 4.90724780e-02 6.03646755e-01 4.62683111e-01 2.76363879e-01 6.93043470e-01 -4.99925196e-01 -3.00423384e-01 -1.27347195e+00 8.63724574e-02 6.68752730e-01 -4.29779887e-02 2.83109874e-01 4.68508184e-01 -3.23679477e-01 4.61730093e-01 1.98970139e-01 4.22157794e-01 7.57389486e-01 -4.69799191e-01 1.38257757e-01 6.86546803e-01 -2.90511884e-02 -1.01539183e+00 -7.99064815e-01 -9.30799663e-01 -1.11061549e+00 2.45492220e-01 6.23094678e-01 -5.36486924e-01 -1.15119839e+00 1.13512349e+00 -1.63108021e-01 1.26945093e-01 4.74733487e-02 8.39312613e-01 9.17911530e-01 2.95514405e-01 -1.18297935e-01 -2.88744390e-01 1.39626873e+00 1.68164272e-03 -6.98946238e-01 1.33506462e-01 5.06548762e-01 -5.48391521e-01 6.90864086e-01 7.31167972e-01 -7.87329793e-01 -6.01509631e-01 -1.43899095e+00 3.66174996e-01 -2.71722257e-01 5.52336812e-01 5.19699693e-01 1.26774144e+00 -1.13226044e+00 8.09074402e-01 -8.74626160e-01 -2.21068427e-01 7.64860332e-01 4.85635370e-01 -2.35257298e-01 3.58827293e-01 -1.29198384e+00 8.05578649e-01 1.30307928e-01 3.99428457e-01 -6.20517433e-01 -5.80762923e-01 -7.91224122e-01 7.43959844e-02 -5.87633252e-01 -6.66693389e-01 7.26387918e-01 -1.05266905e+00 -1.23278344e+00 7.18099356e-01 -1.17227584e-01 -7.22773194e-01 3.13648373e-01 -2.88624674e-01 -6.65396571e-01 3.06123823e-01 -1.64169580e-01 -6.23759478e-02 9.44019675e-01 -5.84949851e-01 -3.34094882e-01 -3.85306954e-01 -2.53339738e-01 -1.64528102e-01 -1.84222415e-01 1.56858321e-02 2.85874814e-01 -1.18360329e+00 3.10204178e-01 -8.21106493e-01 -3.17337215e-01 -3.71071428e-01 -2.57045835e-01 1.14303112e-01 8.39741468e-01 -9.46310222e-01 1.44123638e+00 -2.21387792e+00 -9.03308466e-02 6.35249734e-01 5.24225295e-01 7.30963767e-01 2.06157088e-01 3.82339418e-01 -3.91463846e-01 2.84396410e-01 -3.82177651e-01 2.64575958e-01 -6.48018360e-01 -1.99304730e-01 -2.25943714e-01 5.74319363e-01 2.68685609e-01 9.98301446e-01 -6.68081462e-01 2.53518112e-03 3.23702723e-01 1.03871417e+00 -2.99205557e-02 2.77679209e-02 4.80870217e-01 4.96800333e-01 -1.36032671e-01 4.14856315e-01 2.35459015e-01 -1.78648412e-01 2.44991183e-01 -3.60885024e-01 1.01632208e-01 5.10308981e-01 -8.96038711e-01 1.55462098e+00 -2.15458021e-01 8.87855530e-01 -3.98162633e-01 -1.24526334e+00 1.16095459e+00 8.67723227e-01 6.81859493e-01 -2.95668274e-01 3.10374290e-01 3.96059185e-01 5.89717090e-01 -4.08834219e-01 -3.94732445e-01 -1.68059692e-01 2.50866801e-01 5.69207847e-01 -2.82191765e-02 1.96882546e-01 -2.28378475e-02 -2.39509135e-01 1.24330533e+00 -1.38045460e-01 5.81525862e-01 -4.67168450e-01 5.26819825e-01 -1.09145105e-01 5.38760722e-01 8.97523999e-01 -1.11002147e-01 7.94866562e-01 2.49243841e-01 -1.32713246e+00 -4.48028088e-01 -1.02228212e+00 -3.55831265e-01 1.26472414e-01 -3.92205685e-01 -6.77915931e-01 -5.34699023e-01 -7.32372224e-01 -1.44690335e-01 8.54330435e-02 -5.80544293e-01 -3.43050927e-01 -7.66530633e-01 -9.59371865e-01 1.02431369e+00 7.43535757e-01 4.72046316e-01 -1.42238140e+00 -1.50360572e+00 6.53261840e-01 -7.66286179e-02 -5.25146604e-01 9.58421826e-02 5.16762972e-01 -1.18143547e+00 -1.09375358e+00 -9.99348938e-01 -5.17360389e-01 2.59830505e-01 -3.22037041e-01 1.04543638e+00 3.25310677e-01 -1.08356190e+00 2.10954934e-01 -1.64266497e-01 -9.22304571e-01 -1.45264894e-01 6.53432682e-02 6.62625358e-02 1.26670614e-01 6.43795848e-01 -8.55338037e-01 -1.00468397e+00 -1.32618725e-01 -3.52168351e-01 -3.20646495e-01 7.48430192e-01 8.76971304e-01 4.03416693e-01 -1.30476236e-01 1.04828560e+00 -5.76578617e-01 9.96657729e-01 -1.26139089e-01 -2.70617977e-02 -1.32901698e-01 -6.95303500e-01 -3.40148658e-01 6.01109922e-01 -3.31119895e-01 -2.82418609e-01 2.27148816e-01 -2.55826563e-02 -3.07560176e-01 -2.29929402e-01 8.65772903e-01 2.46273085e-01 8.62242058e-02 8.93784881e-01 1.35947883e-01 9.45853293e-02 -1.08811527e-01 -3.03545952e-01 7.90302217e-01 5.40229261e-01 -1.26273647e-01 3.81195337e-01 3.89836818e-01 -7.32910633e-02 -9.47543263e-01 -4.09444779e-01 -4.52734798e-01 -5.96170008e-01 -1.94213554e-01 8.28451395e-01 -6.71602547e-01 -4.22218680e-01 4.11026120e-01 -1.11934483e+00 1.18852146e-01 -4.09362257e-01 6.95412159e-01 -3.17721814e-01 3.47818196e-01 -5.12951136e-01 -8.94405961e-01 -1.04880047e+00 -6.68869376e-01 6.85951710e-01 -1.06228190e-03 -8.05939496e-01 -7.76581883e-01 1.46248490e-01 -1.71520948e-01 7.12829471e-01 7.88091123e-01 9.63965237e-01 -6.47533536e-01 9.12309065e-02 -4.97891843e-01 5.46235070e-02 4.18435603e-01 6.53996348e-01 -1.93533495e-01 -1.18505907e+00 -4.72762167e-01 1.68402582e-01 2.47014493e-01 8.27443600e-01 7.84542918e-01 1.03554881e+00 7.54290149e-02 -2.72206366e-01 6.03249490e-01 1.03063548e+00 6.20295286e-01 7.94063032e-01 1.13612548e-01 4.28767145e-01 -3.69210318e-02 8.16305328e-05 4.88270134e-01 -2.53335327e-01 3.30534458e-01 -9.41224024e-02 -5.66383839e-01 -2.13842019e-01 3.93872112e-01 1.21691741e-01 3.65125328e-01 -7.69038200e-01 2.33463809e-01 -1.27096522e+00 5.42675436e-01 -1.47762036e+00 -9.37979579e-01 -1.79223895e-01 2.28859115e+00 6.77710056e-01 1.94493309e-01 1.98587641e-01 1.00017273e+00 4.85299021e-01 -2.32329786e-01 -4.97486830e-01 -4.30035144e-01 -1.59336329e-01 9.58791375e-01 -8.94637685e-03 2.36759782e-02 -1.28329206e+00 1.20552063e-01 6.34338188e+00 -8.53604972e-02 -1.64134932e+00 -9.53179076e-02 7.92626500e-01 3.40487696e-02 2.63728559e-01 -3.19641232e-01 -2.07816899e-01 2.42093444e-01 1.22233701e+00 -1.94739234e-02 9.34450850e-02 2.90381193e-01 4.55255210e-01 1.50748849e-01 -9.98528361e-01 1.37434101e+00 -1.70200422e-01 -1.51016200e+00 -2.25552738e-01 6.58447295e-02 1.67595178e-01 3.88139784e-02 -2.00061649e-01 -5.67577630e-02 -4.86760676e-01 -1.53883183e+00 3.71243656e-01 8.55132818e-01 1.17856872e+00 -7.81432271e-01 9.91819799e-01 -3.04747634e-02 -1.24645758e+00 -2.71839559e-01 6.89217746e-02 -2.95466244e-01 4.47690226e-02 1.00993764e+00 -9.42492545e-01 4.48344916e-01 1.02683806e+00 9.04805064e-01 -5.41248918e-01 1.23255014e+00 2.94238105e-02 1.22605991e+00 -3.81866395e-01 2.70744801e-01 -2.34513760e-01 9.98606905e-02 7.05893934e-01 1.40314972e+00 3.78830314e-01 7.45144039e-02 3.53744105e-02 6.01908803e-01 3.89586300e-01 -9.52328444e-02 -6.42680824e-01 -1.20168306e-01 2.06386626e-01 1.14759767e+00 -9.32186127e-01 -3.96058112e-01 -2.59547591e-01 5.96468806e-01 -2.34171376e-01 4.63591367e-01 -4.49954033e-01 -1.04078424e+00 3.27280760e-01 3.89274091e-01 3.27255242e-02 -1.44818529e-01 -7.86287487e-01 -8.86145949e-01 1.72369391e-01 -1.05869961e+00 5.20478547e-01 -3.00491750e-01 -9.92328584e-01 1.06589186e+00 -4.28870708e-01 -1.24935222e+00 -6.20177746e-01 -4.93983686e-01 -8.63473654e-01 1.33001852e+00 -9.78773475e-01 -7.71031559e-01 -3.83355588e-01 6.00169539e-01 2.46358410e-01 -4.04024035e-01 1.51810062e+00 3.07292014e-01 -1.93979278e-01 2.70697355e-01 -5.59923828e-01 3.71976465e-01 2.78975874e-01 -1.37202191e+00 4.54275697e-01 8.43817174e-01 4.28174615e-01 7.67209172e-01 4.70085531e-01 -5.24334610e-01 -7.88214743e-01 -8.90946984e-01 1.14215088e+00 -2.69887358e-01 -5.37898690e-02 -1.33654445e-01 -8.07120621e-01 1.54022664e-01 1.23850457e-01 3.71890247e-01 8.34811866e-01 -9.63019952e-02 -4.13063727e-02 4.12533581e-02 -9.33801234e-01 4.60396707e-03 5.99914432e-01 -6.16504610e-01 -7.17436671e-01 -1.41998827e-01 -1.72183320e-01 -1.79740474e-01 -8.66212130e-01 7.38492608e-01 8.76141429e-01 -9.39305961e-01 1.05022848e+00 -6.15760207e-01 -5.74595369e-02 -3.28592360e-01 3.32230031e-01 -1.33811224e+00 -3.96694690e-01 -8.32984328e-01 -2.86082983e-01 5.28309405e-01 5.24875939e-01 -6.49896026e-01 7.68921375e-01 -2.44321693e-02 3.62320314e-03 -1.03796935e+00 -8.01106513e-01 -4.45771962e-01 -1.29179657e-01 -3.03092390e-01 2.68866092e-01 7.30662465e-01 3.12395431e-02 2.70058453e-01 -3.29070240e-02 -1.99462287e-02 1.77170813e-01 1.40918314e-01 1.27668232e-01 -1.69136715e+00 -1.18567437e-01 -3.50747496e-01 -8.19533169e-01 3.51415090e-02 -3.37231487e-01 -9.72140551e-01 -3.93591583e-01 -1.65448892e+00 -3.18856627e-01 -4.82127279e-01 -8.81497681e-01 6.30007446e-01 -1.06048360e-01 6.00534976e-01 -1.26469329e-01 5.99880554e-02 4.46731031e-01 -7.86294863e-02 4.59465384e-01 -2.96930611e-01 -6.71626806e-01 4.49112833e-01 -4.79760051e-01 7.70804286e-01 1.11883891e+00 -3.20405781e-01 -5.62848747e-01 1.55451789e-01 1.93492398e-01 6.88811615e-02 4.71475273e-01 -1.43177760e+00 -2.15923339e-01 6.49030685e-01 1.14452469e+00 -4.32440102e-01 1.37314111e-01 -5.97872019e-01 3.24168324e-01 9.14506316e-01 -1.18233711e-01 3.64851147e-01 3.69801193e-01 4.19123858e-01 -3.41092795e-01 1.76546648e-01 6.09711945e-01 -2.03104615e-02 -1.40092596e-01 8.60902369e-02 -9.75687146e-01 -1.57181770e-01 7.98900008e-01 -4.11640912e-01 2.90828466e-01 -3.63509893e-01 -1.14447200e+00 -5.53229570e-01 -3.51562142e-01 2.92312771e-01 9.76856172e-01 -1.16284966e+00 -9.84867215e-01 5.17660558e-01 -8.74881446e-02 -2.99235791e-01 -4.85019833e-02 1.12983692e+00 -7.85820127e-01 3.97586226e-01 -4.14918840e-01 -8.31562459e-01 -1.35638118e+00 1.15460783e-01 9.26431596e-01 -2.05650389e-01 -1.31152344e+00 5.92579901e-01 -2.85675645e-01 2.43113503e-01 2.78983295e-01 -4.75472331e-01 -5.66736937e-01 7.12883323e-02 8.05641711e-01 1.61751166e-01 6.53583944e-01 -3.95273149e-01 -6.90982401e-01 4.17791486e-01 5.76509498e-02 -9.68911946e-02 1.29730499e+00 4.17541146e-01 -1.01870429e-02 4.56353635e-01 8.12446773e-01 -1.65336683e-01 -5.03452659e-01 1.41631201e-01 2.23032057e-01 -1.46094352e-01 2.08894119e-01 -1.15708601e+00 -1.24492681e+00 1.19996095e+00 1.24928081e+00 3.95214379e-01 1.38117862e+00 -4.88104194e-01 6.22993946e-01 4.12187457e-01 1.46792799e-01 -5.52127898e-01 -2.45632112e-01 7.07446635e-02 9.74974096e-01 -5.62896967e-01 -1.24112153e-02 -7.49675259e-02 -1.70133233e-01 1.67851043e+00 -6.71624243e-02 -2.57056057e-01 1.14027894e+00 3.86356831e-01 6.40966833e-01 -4.93363529e-01 -2.03961357e-01 5.06181642e-02 4.44552898e-01 6.57351732e-01 1.06080353e+00 1.01659857e-01 -5.89842021e-01 8.09919000e-01 -2.64726877e-01 5.06087065e-01 2.66141564e-01 1.10465217e+00 -1.68236762e-01 -1.07040310e+00 -3.21984142e-01 1.01306236e+00 -8.62575471e-01 -1.67197451e-01 -5.82705081e-01 3.29533547e-01 2.35587671e-01 1.03893971e+00 -1.13736942e-01 -2.60206550e-01 1.30328029e-01 4.34911788e-01 3.80436808e-01 -5.68146467e-01 -1.04360104e+00 1.45039903e-02 1.29104182e-01 -3.59178483e-01 -4.32970881e-01 -5.91485560e-01 -1.21857584e+00 4.94449943e-01 -1.75643548e-01 1.24011517e-01 5.91319144e-01 8.33340645e-01 6.41679525e-01 8.29334617e-01 3.56363863e-01 -8.15603733e-01 -1.19846068e-01 -1.24257696e+00 -5.07689476e-01 9.89185944e-02 7.74991572e-01 -3.34515929e-01 -3.02114427e-01 2.85596579e-01]	[14.294002532958984, 3.280867099761963]
ab751077-cf0e-43f5-a18f-2eb8992c44fe	detecting-the-open-world-objects-with-the	2303.11623	null	https://arxiv.org/abs/2303.11623v1	https://arxiv.org/pdf/2303.11623v1.pdf	Detecting the open-world objects with the help of the Brain	Open World Object Detection (OWOD) is a novel computer vision task with a considerable challenge, bridging the gap between classic object detection (OD) benchmarks and real-world object detection. In addition to detecting and classifying seen/known objects, OWOD algorithms are expected to detect unseen/unknown objects and incrementally learn them. The natural instinct of humans to identify unknown objects in their environments mainly depends on their brains' knowledge base. It is difficult for a model to do this only by learning from the annotation of several tiny datasets. The large pre-trained grounded language-image models - VL (\ie GLIP) have rich knowledge about the open world but are limited to the text prompt. We propose leveraging the VL as the ``Brain'' of the open-world detector by simply generating unknown labels. Leveraging it is non-trivial because the unknown labels impair the model's learning of known objects. In this paper, we alleviate these problems by proposing the down-weight loss function and decoupled detection structure. Moreover, our detector leverages the ``Brain'' to learn novel objects beyond VL through our pseudo-labeling scheme.	['Thomas H. Li', 'Enming Zhang', 'Jiaqi Fan', 'Zhixiang Ye', 'Peihao Chen', 'Ying WEI', 'Yuefeng Wang', 'Shuailei Ma']	2023-03-21	null	null	null	null	['open-world-object-detection']	['computer-vision']	[ 9.91999209e-02 5.19141078e-01 8.51010978e-02 -2.28303522e-01 -4.59688425e-01 -7.00537682e-01 6.05919659e-01 8.06121156e-02 -6.67116880e-01 3.53252262e-01 -3.85049544e-02 -1.17263339e-01 3.15542996e-01 -7.90248334e-01 -9.27264392e-01 -3.64171058e-01 -9.75348428e-02 6.69239819e-01 6.81433797e-01 -9.44724903e-02 4.46720272e-02 1.68362781e-01 -1.64335573e+00 2.21000835e-01 6.97720289e-01 9.99564469e-01 5.54413378e-01 7.66445756e-01 -1.69256002e-01 1.25622082e+00 -3.01606834e-01 -4.39405650e-01 5.48526049e-01 -4.79996167e-02 -7.95174837e-01 9.25383046e-02 7.40198314e-01 -7.02996254e-01 -3.94276977e-01 1.24826968e+00 3.59637260e-01 -1.09669708e-01 5.64553559e-01 -1.47336733e+00 -1.12385237e+00 5.62974513e-01 -6.18559480e-01 4.94778275e-01 1.91759765e-01 5.15121698e-01 1.30320573e+00 -1.01591766e+00 8.64338577e-01 1.33320570e+00 5.52266836e-01 6.89419389e-01 -1.23415101e+00 -6.99792445e-01 6.20180607e-01 3.17006469e-01 -1.47867382e+00 -5.18949866e-01 7.11417973e-01 -8.40042710e-01 7.26590991e-01 6.13052286e-02 4.22816545e-01 1.27457845e+00 -2.51616716e-01 1.09815133e+00 8.26780379e-01 -3.41823757e-01 2.75364578e-01 4.41409916e-01 3.90834987e-01 9.24578190e-01 6.20351791e-01 2.55709499e-01 -4.24807459e-01 6.48581907e-02 4.68553215e-01 2.36885875e-01 -2.28785709e-01 -7.77286232e-01 -1.36308563e+00 6.34417117e-01 8.72580945e-01 -2.14695148e-02 -1.45446852e-01 1.90318361e-01 3.16556782e-01 2.46137232e-01 3.87652367e-01 4.87877846e-01 -4.70326424e-01 2.43528128e-01 -5.56380510e-01 1.28220543e-01 8.54197204e-01 1.19279790e+00 9.27722037e-01 -2.81248629e-01 -2.06889987e-01 5.99041462e-01 3.49442482e-01 4.44933712e-01 3.70164156e-01 -6.56567633e-01 3.44388545e-01 9.07227814e-01 2.15559483e-01 -8.32737565e-01 -3.82753670e-01 -5.11313140e-01 -3.67648900e-01 2.24432826e-01 6.59455240e-01 -5.91651909e-02 -1.00935221e+00 1.84538102e+00 4.80797559e-01 1.70432627e-01 4.67432104e-02 9.40758109e-01 8.32702398e-01 4.36084867e-01 9.60647240e-02 1.38916269e-01 1.38878703e+00 -1.16932786e+00 -3.02773863e-01 -8.45873356e-01 6.66152477e-01 -3.38687152e-01 1.15988219e+00 2.58705378e-01 -6.57469392e-01 -5.74449658e-01 -9.99795854e-01 -4.56186682e-01 -4.60082054e-01 4.50991616e-02 6.87636435e-01 3.31793666e-01 -8.07761312e-01 4.44103070e-02 -7.27344215e-01 -5.20025551e-01 9.83430624e-01 1.05994560e-01 -3.40641975e-01 -2.60101974e-01 -6.85359895e-01 8.30604970e-01 6.94214106e-01 -1.52569324e-01 -1.48365915e+00 -3.71414125e-01 -9.23790455e-01 -6.02715723e-02 9.34631884e-01 -6.74839079e-01 1.40043974e+00 -1.07678044e+00 -7.36273944e-01 1.25924361e+00 8.17632228e-02 -6.04048491e-01 7.74048388e-01 -3.69755596e-01 -9.00736824e-02 8.32539648e-02 3.39325994e-01 9.43875074e-01 1.01849079e+00 -1.38801217e+00 -9.47643161e-01 -4.98949349e-01 4.15158093e-01 -4.53070141e-02 -3.28630239e-01 -2.11446937e-02 -2.75823563e-01 -4.28073257e-01 3.25872034e-01 -9.59622800e-01 -2.71492541e-01 6.59711599e-01 -5.27395785e-01 -4.03892130e-01 9.09610450e-01 -2.69826353e-01 7.85126150e-01 -2.20913649e+00 -2.47161642e-01 -3.68781358e-01 8.42648327e-01 1.59912437e-01 -3.27628851e-01 -9.70661566e-02 3.44317943e-01 -1.60322443e-01 1.55214015e-02 -2.00208634e-01 2.50109434e-01 3.08188885e-01 -7.67174125e-01 4.91230220e-01 3.85597646e-01 1.13957536e+00 -1.29007876e+00 -5.30514121e-01 -6.33418858e-02 2.23753024e-02 -6.42837763e-01 2.00109929e-01 -6.85110748e-01 2.03031823e-01 -4.66658950e-01 7.24486113e-01 5.88076353e-01 -4.16348070e-01 -1.44605041e-01 1.05155379e-01 -6.80410340e-02 1.39590546e-01 -1.29783106e+00 1.36925721e+00 -1.74043342e-01 7.35387802e-01 1.02161139e-01 -9.03391957e-01 7.29038596e-01 -8.30911845e-02 -1.45529862e-02 -4.79403108e-01 1.48214668e-01 1.62357941e-01 2.40655184e-01 -7.56498039e-01 1.95325941e-01 -1.47387192e-01 7.78734162e-02 6.11831069e-01 4.10648733e-01 2.32075498e-01 1.96345732e-01 5.55655599e-01 1.36492109e+00 3.73730846e-02 3.21056485e-01 -1.25820905e-01 2.58684933e-01 6.30926564e-02 7.99008906e-01 1.23774004e+00 -5.77759087e-01 4.58009571e-01 4.21917945e-01 -7.12926447e-01 -8.38414609e-01 -1.25422287e+00 -1.65337443e-01 1.54460025e+00 2.16247812e-01 -1.24601983e-01 -5.28117537e-01 -9.84237492e-01 9.18787792e-02 5.78493297e-01 -6.42903924e-01 -2.09879562e-01 -2.65642017e-01 -4.27478105e-01 5.87648153e-01 5.08014798e-01 3.65685850e-01 -1.08372736e+00 -1.01471257e+00 1.88568965e-01 -6.36519641e-02 -1.38473368e+00 -3.68868977e-01 4.54763561e-01 -4.18806970e-01 -1.23821628e+00 -3.97092581e-01 -1.05563712e+00 8.82027090e-01 5.49519300e-01 1.12057960e+00 1.06346719e-02 -6.42208517e-01 4.18673068e-01 -3.62221390e-01 -1.03038287e+00 -4.13400918e-01 -7.07644671e-02 3.04345608e-01 2.42819279e-01 6.95512474e-01 -2.80262589e-01 -5.93354046e-01 3.23474646e-01 -6.74868405e-01 1.70955583e-01 6.45525575e-01 7.40276992e-01 4.00053978e-01 -2.45836094e-01 5.48385620e-01 -9.49913204e-01 1.09568074e-01 -6.20603204e-01 -7.66355872e-01 2.53328383e-01 -3.49964589e-01 1.16181545e-01 3.99178952e-01 -8.35225463e-01 -9.58049715e-01 2.62992978e-01 2.25448608e-01 -5.27521253e-01 -2.82557249e-01 -2.53522191e-02 -2.78534651e-01 -4.61194776e-02 9.30177212e-01 1.32239863e-01 -4.65503246e-01 -5.22268951e-01 5.90030074e-01 6.61512673e-01 8.13002169e-01 -5.24833977e-01 1.16277099e+00 8.68820310e-01 -5.16436100e-01 -5.78492105e-01 -1.56621599e+00 -6.91000164e-01 -7.65113473e-01 9.93880257e-03 8.37339044e-01 -1.20951927e+00 -5.07546365e-01 2.68367082e-01 -1.39259470e+00 -2.05078900e-01 -6.55566454e-01 2.39952967e-01 -3.27137023e-01 1.40168279e-01 -3.25945228e-01 -7.32461512e-01 -1.45078868e-01 -9.11896288e-01 1.01372647e+00 7.38495067e-02 9.39132366e-03 -7.16323793e-01 -5.55796847e-02 3.24666917e-01 1.47272959e-01 1.42708290e-02 5.71983516e-01 -1.02225327e+00 -8.99284840e-01 -3.20246696e-01 -6.08747363e-01 3.86368513e-01 -1.15755044e-01 -3.56386036e-01 -1.45161819e+00 -2.70917058e-01 2.11525619e-01 -6.81582093e-01 1.18107033e+00 -2.56858200e-01 9.67757404e-01 -5.03104806e-01 -6.41240239e-01 5.41916966e-01 1.14010370e+00 -2.33065531e-01 3.14575061e-02 3.04060161e-01 8.54213655e-01 6.62750900e-01 3.87046337e-01 4.88910466e-01 6.38894141e-01 2.35107422e-01 5.67290783e-01 -2.76898276e-02 -2.93769747e-01 -5.31465113e-01 5.28706551e-01 3.51457030e-01 2.83897668e-01 -1.89135879e-01 -1.30900514e+00 7.77792335e-01 -1.80644858e+00 -9.40545678e-01 -4.62863669e-02 1.96171880e+00 8.03792834e-01 5.11423051e-01 -1.91747978e-01 -1.58930331e-01 7.40243733e-01 -1.66589599e-02 -8.94458532e-01 5.58510236e-02 -1.40126973e-01 -3.14285010e-01 3.86384100e-01 1.00195125e-01 -1.31441069e+00 1.03838420e+00 5.62437487e+00 3.63093734e-01 -9.50314164e-01 5.14401317e-01 2.94420272e-01 -2.38503873e-01 8.09962600e-02 2.69871294e-01 -1.21752799e+00 2.65001953e-01 5.42974591e-01 -1.28958285e-01 2.21617743e-01 1.22941327e+00 -2.28197694e-01 -1.52653858e-01 -1.65286553e+00 9.98672426e-01 3.42707664e-01 -1.08112466e+00 1.62060529e-01 -5.28647052e-03 7.72866607e-01 6.48573995e-01 -8.09380040e-02 7.08088875e-01 7.15081871e-01 -6.36327088e-01 1.13496971e+00 3.52723986e-01 4.40045774e-01 3.14638130e-02 3.04508030e-01 9.32096303e-01 -1.01510096e+00 -7.03919768e-01 -5.81238806e-01 -3.76031220e-01 -5.14062867e-02 4.83036786e-01 -1.01573145e+00 -2.70353854e-01 7.11533427e-01 6.30756915e-01 -8.83566797e-01 1.08037794e+00 -4.99784142e-01 5.59010029e-01 -4.13067669e-01 2.69526124e-01 3.34967732e-01 1.10960148e-01 7.84654260e-01 9.77835476e-01 -5.58373965e-02 2.74149626e-02 6.32394969e-01 1.29774129e+00 -4.24855143e-01 -2.57777154e-01 -7.30794728e-01 -1.27680808e-01 2.99329400e-01 1.24978805e+00 -7.46089697e-01 -4.36404407e-01 -6.72323167e-01 8.30919445e-01 6.79679036e-01 1.61913052e-01 -6.40559793e-01 -2.21633136e-01 5.51852107e-01 2.01720282e-01 3.99829030e-01 -1.21531434e-01 2.79362244e-03 -1.34519172e+00 1.23354614e-01 -6.19982362e-01 5.91451585e-01 -7.13350832e-01 -1.52193308e+00 3.84427607e-01 -3.63438278e-01 -1.02761614e+00 1.66246086e-01 -8.95881534e-01 -4.14262295e-01 3.27932686e-01 -1.83937931e+00 -1.48279989e+00 -4.08393621e-01 4.99977976e-01 7.71931112e-01 7.92095661e-02 3.83543015e-01 2.04610154e-01 -5.78400671e-01 4.10840243e-01 -7.23387301e-03 5.37360668e-01 6.28034174e-01 -1.23135567e+00 4.54823464e-01 9.71628070e-01 5.83920121e-01 4.99443024e-01 6.23614490e-01 -5.65725386e-01 -1.41632915e+00 -1.32115066e+00 7.04939961e-01 -1.05536628e+00 9.21957314e-01 -9.80852544e-01 -1.01482284e+00 1.13691676e+00 -3.99258941e-01 8.17723453e-01 2.89168268e-01 1.85248360e-01 -8.21146727e-01 1.34922192e-02 -9.13947105e-01 4.98776495e-01 1.45630145e+00 -6.43860459e-01 -9.28626895e-01 6.24406159e-01 1.03584611e+00 -2.55769968e-01 -1.88519835e-01 2.04619393e-01 2.85246104e-01 -6.70404851e-01 1.04075122e+00 -8.00538599e-01 1.87093496e-01 -4.95880246e-01 -1.80000991e-01 -8.67040038e-01 -1.79387480e-01 -3.85428637e-01 -4.12593275e-01 1.10792601e+00 8.90768990e-02 -6.30871952e-01 4.90280926e-01 6.32066727e-01 -9.17919055e-02 -2.55105406e-01 -7.86840200e-01 -1.10623181e+00 -2.03677103e-01 -6.82034492e-01 3.27737659e-01 9.57159281e-01 -1.06545582e-01 5.97974837e-01 -4.43960577e-02 5.07660925e-01 7.96285868e-01 1.46151707e-01 9.16093230e-01 -1.54953265e+00 -3.95644993e-01 -1.25559717e-01 -6.30270660e-01 -1.20264089e+00 1.80941030e-01 -1.24872696e+00 4.61693853e-01 -1.24176419e+00 7.74376273e-01 -6.54827714e-01 -4.52446133e-01 7.56938279e-01 -1.54032052e-01 3.68741214e-01 3.48868459e-01 4.37921405e-01 -1.30887818e+00 4.08410907e-01 1.18264651e+00 -3.78160775e-01 -2.78576687e-02 -2.93723315e-01 -7.41199017e-01 1.27585244e+00 3.05775344e-01 -8.67723286e-01 -2.80613989e-01 -8.13717365e-01 5.68128169e-01 -5.67420542e-01 1.04199111e+00 -1.03565216e+00 4.89860386e-01 -5.40834069e-02 2.01396957e-01 -4.04705286e-01 6.65547699e-02 -6.60169005e-01 -4.37684506e-01 5.21740675e-01 -3.21949750e-01 -5.05382299e-01 -6.84204772e-02 9.01404977e-01 1.13962054e-01 -2.57257521e-01 8.60188186e-01 -4.73659575e-01 -1.28772342e+00 3.93344432e-01 -7.61085898e-02 4.72475469e-01 1.27344143e+00 -2.39691615e-01 -6.37518287e-01 6.92590922e-02 -7.04554260e-01 5.35067201e-01 4.99569058e-01 6.24090910e-01 5.20744264e-01 -8.42598319e-01 -5.57300866e-01 2.06502602e-01 7.62410462e-01 4.67626452e-01 -6.88599423e-02 6.03226483e-01 -2.87463933e-01 2.36317605e-01 1.38316117e-02 -6.09287500e-01 -8.99682581e-01 1.00614750e+00 4.03102130e-01 7.63356611e-02 -7.93986917e-01 1.21284139e+00 8.64736199e-01 -6.07246876e-01 5.04295051e-01 -2.10121095e-01 4.64626029e-02 1.18447036e-01 7.12349117e-01 2.32344508e-01 -2.22839713e-01 -5.64189494e-01 -3.07746530e-01 1.91908777e-02 -4.35578793e-01 2.75982082e-01 1.36409187e+00 -2.64695913e-01 -6.58760369e-02 5.69140434e-01 9.65296328e-01 -3.93838435e-01 -1.57714117e+00 -8.40092897e-01 3.11636031e-01 -5.08750558e-01 1.41760975e-01 -8.41992080e-01 -5.58314264e-01 1.09157252e+00 6.98401749e-01 -3.58059742e-02 5.45408964e-01 6.23346031e-01 7.46447682e-01 9.78446484e-01 5.99779487e-01 -1.13244009e+00 5.32047153e-01 6.51876867e-01 7.05465913e-01 -1.78640044e+00 -1.87510774e-01 -2.59866416e-01 -4.03228372e-01 7.80980587e-01 1.01532555e+00 4.21730056e-02 4.35750365e-01 1.89013675e-01 9.77909192e-02 -2.99613386e-01 -8.81867647e-01 -5.35084784e-01 1.13409400e-01 6.77639484e-01 -1.67616829e-01 5.44143841e-03 3.73743653e-01 7.86400259e-01 3.25669274e-02 1.75553635e-02 5.51121056e-01 1.00798726e+00 -9.74739909e-01 -5.41657984e-01 -4.18627352e-01 5.30214906e-01 -4.05402482e-02 -1.21322170e-01 -4.27370489e-01 4.53435570e-01 6.90547287e-01 7.34905839e-01 5.68521544e-02 -3.31822247e-03 7.92150199e-02 4.12164964e-02 2.15290546e-01 -1.10652554e+00 -1.23856738e-02 -4.94001210e-01 -2.69111097e-01 -5.19071817e-01 -5.45039922e-02 -6.43110991e-01 -1.27144980e+00 1.58588588e-01 -5.99047065e-01 -3.68484378e-01 4.16535646e-01 9.65667963e-01 2.88288414e-01 2.15012893e-01 4.38167632e-01 -6.99863374e-01 -9.35499251e-01 -7.06926405e-01 -4.77139890e-01 6.14373147e-01 6.15264714e-01 -8.03027213e-01 -2.75005251e-01 1.85052291e-01]	[9.491948127746582, 1.5720456838607788]
7cea3d9c-af50-4887-9361-d83f7db42c3b	profiling-entity-matching-benchmark-tasks	null	null	https://dl.acm.org/doi/10.1145/3340531.3412781	https://dl.acm.org/doi/pdf/10.1145/3340531.3412781	Profiling Entity Matching Benchmark Tasks	Entity matching is a central task in data integration which has been researched for decades. Over this time, a wide range of benchmark tasks for evaluating entity matching methods has been developed. This resource paper systematically complements, profiles, and compares 21 entity matching benchmark tasks. In order to better understand the specific challenges associated with different tasks, we define a set of profiling dimensions which capture central aspects of the matching tasks. Using these dimensions, we create groups of benchmark tasks having similar characteristics. Afterwards, we assess the difficulty of the tasks in each group by computing baseline evaluation results using standard feature engineering together with two common classification methods. In order to enable the exact reproducibility of evaluation results, matching tasks need to contain exactly defined sets of matching and non-matching record pairs, as well as a fixed development and test split. As this is not the case for some widely-used benchmark tasks, we complement these tasks with fixed sets of non-matching pairs, as well as fixed splits, and provide the resulting development and test sets for public download. By profiling and complementing the benchmark tasks, we support researchers to select challenging as well as diverse tasks and to compare matching systems on clearly defined grounds.	['Christian Bizer', 'Anna Primpeli']	2020-10-19	null	null	null	international-conference-on-information-2	['data-integration', 'entity-resolution']	['knowledge-base', 'natural-language-processing']	[ 8.26596916e-02 -2.06485927e-01 -2.61233598e-01 -4.75015759e-01 -6.23546362e-01 -8.42278063e-01 7.72544384e-01 5.98160446e-01 -5.88698387e-01 5.69676399e-01 4.37625535e-02 -5.16024306e-02 -4.17174637e-01 -5.86777687e-01 -3.85844707e-01 -1.87118143e-01 -1.02957360e-01 6.24585629e-01 3.84851187e-01 -2.63648659e-01 2.45713964e-01 2.53729552e-01 -2.03744197e+00 5.76687694e-01 9.31528270e-01 8.12497556e-01 8.20595250e-02 3.11240286e-01 -2.84626752e-01 1.33835211e-01 -7.64821410e-01 -9.23990250e-01 3.30625772e-01 -7.96579421e-02 -9.82400119e-01 -3.54275018e-01 7.72888958e-01 2.30905399e-01 8.92453715e-02 1.03491735e+00 6.71059668e-01 1.12366192e-01 5.96156955e-01 -1.51536334e+00 -3.02742273e-01 6.25356317e-01 -1.74831629e-01 1.43681809e-01 7.68048525e-01 -1.60903126e-01 1.22942650e+00 -7.95350909e-01 9.61998880e-01 7.42372513e-01 9.86747801e-01 3.85507315e-01 -1.15441084e+00 -6.76469862e-01 3.90631221e-02 2.00253457e-01 -1.20451307e+00 -6.32249594e-01 4.88921613e-01 -4.85189676e-01 1.10769546e+00 5.29584169e-01 2.32937545e-01 9.88397419e-01 -6.71348050e-02 4.31557447e-01 8.18562031e-01 -5.69668531e-01 3.19171771e-02 3.89209539e-01 5.97398639e-01 1.88628376e-01 5.52510977e-01 -2.68032812e-02 -1.62859216e-01 -4.35372382e-01 -1.30023614e-01 -1.12600051e-01 -4.11940575e-01 -7.46011496e-01 -1.39407420e+00 3.81361365e-01 9.60276648e-02 6.42897606e-01 -7.50025734e-02 -3.46777886e-01 7.88391709e-01 6.23193204e-01 2.33419135e-01 8.06344807e-01 -5.03882766e-01 -2.61417925e-02 -7.72828579e-01 6.68176234e-01 1.23465288e+00 1.35957372e+00 8.32785308e-01 -7.40802824e-01 -5.57616651e-01 1.08733022e+00 -6.67767078e-02 1.09965339e-01 4.49083388e-01 -8.20455730e-01 8.92728448e-01 8.98172438e-01 3.02333593e-01 -7.93167055e-01 -4.61726308e-01 -5.78029454e-01 -6.93762064e-01 -5.09004071e-02 6.43472135e-01 8.27940851e-02 -5.33149123e-01 1.84022284e+00 2.45373145e-01 -1.44986898e-01 5.31121530e-02 5.28265119e-01 9.10646737e-01 4.45724028e-04 1.18747421e-01 5.42668998e-02 1.64884508e+00 -8.43725562e-01 -5.02965510e-01 2.27460153e-02 1.06486940e+00 -1.00126016e+00 1.11477339e+00 -8.61680731e-02 -1.04083729e+00 -6.33839548e-01 -1.10148931e+00 -8.45433176e-02 -8.99120450e-01 7.30443513e-03 5.22981584e-01 7.28643894e-01 -9.21059370e-01 8.47765803e-01 -3.83558095e-01 -6.72495306e-01 -4.30007502e-02 2.32632726e-01 -6.07789755e-01 -7.87592307e-02 -1.44043612e+00 1.17514133e+00 3.36587787e-01 -3.27349573e-01 -9.00655314e-02 -1.07470179e+00 -8.25691104e-01 -2.78897025e-02 1.46824643e-01 -9.79373455e-01 1.40608108e+00 -3.90956700e-01 -7.43096471e-01 1.42458165e+00 -4.24536541e-02 -1.86650351e-01 6.64510429e-01 -9.09299254e-02 -6.23117328e-01 -4.33102369e-01 2.75581777e-01 3.76034886e-01 1.39648095e-01 -1.02995789e+00 -8.99527133e-01 -3.71180266e-01 2.33734518e-01 1.14551336e-01 -3.33064139e-01 5.20438790e-01 -7.56657064e-01 -5.16918480e-01 -3.63570035e-01 -8.55396032e-01 -2.63600815e-02 -4.13263381e-01 -3.33617866e-01 -3.87925327e-01 3.30596477e-01 -2.45252952e-01 1.54892087e+00 -2.26891160e+00 5.00207655e-02 8.62646550e-02 3.99983972e-01 2.57889748e-01 -2.06107095e-01 6.13745570e-01 -3.79792601e-01 1.61645904e-01 -3.46308380e-01 -7.06190884e-01 4.26405132e-01 -1.00647442e-01 -1.67057246e-01 1.92022488e-01 1.60474658e-01 8.56102467e-01 -8.77554715e-01 -3.12198102e-01 -1.15010224e-01 3.76621112e-02 -2.95700490e-01 2.54221946e-01 -1.83600768e-01 2.44534967e-05 -3.09207976e-01 6.72809660e-01 6.39422297e-01 -1.76189601e-01 1.15582362e-01 -4.04935151e-01 -1.32077724e-01 4.93458271e-01 -1.41975939e+00 1.77617073e+00 -3.36423278e-01 3.93615395e-01 -1.77587196e-01 -1.00937927e+00 8.55416596e-01 3.79648775e-01 5.53788185e-01 -8.01559091e-01 -1.57198340e-01 5.61665952e-01 -1.02143148e-02 -5.58590174e-01 7.02723324e-01 2.25606933e-01 -4.35866863e-01 6.59724355e-01 1.39121607e-01 2.27643296e-01 7.61047125e-01 -5.86847812e-02 1.37802422e+00 -3.79855372e-02 3.80661249e-01 -2.92514563e-01 6.22208357e-01 1.22302316e-01 5.65310121e-01 7.47012317e-01 -1.13897957e-01 7.02278674e-01 3.32708478e-01 -4.73619491e-01 -1.06887901e+00 -9.34925377e-01 -4.30631161e-01 1.14475572e+00 2.35538140e-01 -8.13163280e-01 -6.63997233e-01 -7.08246410e-01 3.21189463e-01 4.39188480e-01 -7.20424891e-01 -8.80478024e-02 -5.46659052e-01 -8.38645637e-01 7.88947940e-01 3.55165571e-01 2.16494694e-01 -1.11960733e+00 -5.46037257e-01 1.18607439e-01 -1.73580423e-01 -1.09936368e+00 -3.50413978e-01 2.59749383e-01 -5.15357077e-01 -1.34637380e+00 -6.95519030e-01 -7.19911993e-01 4.04590935e-01 4.21776533e-01 1.91706920e+00 4.16781336e-01 -2.54236639e-01 3.34235847e-01 -4.49064940e-01 -3.78067136e-01 -3.62663418e-01 7.02504456e-01 -1.34646207e-01 -3.13899279e-01 6.62122309e-01 -5.66245794e-01 -3.35685879e-01 7.18430638e-01 -9.21271980e-01 -2.26923108e-01 5.38489044e-01 5.70268691e-01 3.86816502e-01 -4.02359456e-01 4.65682179e-01 -1.12893403e+00 8.58206689e-01 -7.61527300e-01 -5.55918515e-01 7.32071221e-01 -9.33339536e-01 1.62279397e-01 4.34372693e-01 -2.56119519e-01 -6.29938543e-01 -1.84454352e-01 -5.18846698e-02 -3.08436085e-03 -2.60623991e-01 5.88109732e-01 -4.11297619e-01 1.52550027e-01 8.67671609e-01 -1.53722599e-01 -1.94222778e-01 -8.61842394e-01 2.66635239e-01 6.93059683e-01 4.99358505e-01 -9.33848023e-01 8.71958852e-01 1.42701134e-01 -3.53406489e-01 -1.33987084e-01 -5.57126462e-01 -7.93354928e-01 -6.81241274e-01 1.93895504e-01 5.59409857e-01 -6.99217260e-01 -3.37364107e-01 4.06250805e-01 -1.18823624e+00 -1.15972765e-01 -2.87423939e-01 2.96553403e-01 -4.19678450e-01 3.29476327e-01 -3.13595593e-01 -2.20821723e-01 -3.94667804e-01 -1.19125509e+00 1.02475011e+00 2.79493108e-02 -5.55270791e-01 -9.12252069e-01 4.22699094e-01 1.46410123e-01 5.46116412e-01 3.39852005e-01 8.83798778e-01 -1.05707777e+00 -3.60206455e-01 -3.90161276e-01 -2.50102371e-01 -6.57904223e-02 7.29209185e-02 1.18921474e-01 -8.49898338e-01 -3.43762189e-01 -3.11906904e-01 4.72086889e-04 8.24686944e-01 -2.56344974e-01 7.49266803e-01 3.46705675e-01 -7.92437434e-01 6.98725998e-01 1.11591327e+00 1.29172996e-01 6.14639997e-01 8.01786005e-01 3.40957314e-01 9.96668816e-01 7.25052476e-01 -7.74159608e-03 6.90487564e-01 1.19538641e+00 -9.26949922e-03 -8.42731893e-02 -1.47941122e-02 9.65722799e-02 1.05321687e-02 4.72816110e-01 -4.52717878e-02 -2.04855740e-01 -1.03559244e+00 6.37003839e-01 -1.93849611e+00 -9.40393329e-01 -2.11202711e-01 2.52078629e+00 8.72098505e-01 4.72284555e-02 3.57323617e-01 2.80075580e-01 7.97499239e-01 -2.72191390e-02 -2.38329038e-01 -1.33850947e-01 -1.86609328e-02 3.17512035e-01 1.83951139e-01 1.23653904e-01 -1.06370831e+00 5.03420830e-01 6.22071743e+00 5.45075059e-01 -9.29679990e-01 8.20312556e-03 3.41030583e-02 1.71072081e-01 -4.77495998e-01 1.37751237e-01 -1.10541487e+00 5.71758747e-01 8.71471286e-01 -4.90326673e-01 6.45920709e-02 6.50303364e-01 -4.19506431e-01 2.25909069e-01 -1.70110416e+00 8.58995318e-01 -1.93524823e-01 -1.16705596e+00 -3.02705288e-01 -5.14021814e-02 4.33892906e-01 1.70057178e-01 -2.04955742e-01 5.75394273e-01 2.30584085e-01 -9.34955060e-01 6.38956428e-01 4.43636507e-01 8.06509793e-01 -2.76213706e-01 8.74911785e-01 1.15865916e-01 -1.34991515e+00 1.14177428e-02 -3.21254253e-01 4.69173975e-02 9.64677557e-02 7.32001305e-01 -1.45999923e-01 1.30524111e+00 8.79996359e-01 6.50013089e-01 -8.27098370e-01 1.45336783e+00 1.43515736e-01 -3.80179584e-02 -3.17315072e-01 3.07677686e-01 -2.85815030e-01 -6.24306761e-02 3.59440982e-01 1.54569018e+00 4.27434832e-01 -5.04873693e-01 -2.29345821e-02 7.45602369e-01 -2.65263230e-01 3.30039352e-01 -6.08240008e-01 2.31670856e-01 9.36079323e-01 1.34674489e+00 -3.61411095e-01 -2.25792244e-01 -5.63468814e-01 6.58508062e-01 6.26210570e-01 1.75433084e-01 -7.80223608e-01 -7.27259815e-01 9.89198983e-01 9.99346673e-02 -5.36430478e-02 1.43877054e-02 -2.01943219e-01 -1.28946912e+00 5.42089164e-01 -9.86880064e-01 7.67874777e-01 -2.70115376e-01 -1.45614147e+00 7.77517200e-01 3.60690773e-01 -1.52359128e+00 -3.58563572e-01 -1.80617318e-01 -7.48064280e-01 1.06026828e+00 -1.65702283e+00 -9.24354434e-01 -8.36412728e-01 3.28441381e-01 -2.18928270e-02 -2.61454701e-01 1.02304733e+00 1.01930130e+00 -8.41754913e-01 1.00728953e+00 -3.32322009e-02 2.04740956e-01 1.29601610e+00 -1.23783040e+00 9.88496304e-01 4.84893888e-01 1.76215544e-01 9.58222449e-01 6.85483932e-01 -3.03817362e-01 -1.12046945e+00 -1.03811944e+00 1.34661472e+00 -8.74736309e-01 5.23353159e-01 -5.35414279e-01 -1.19566453e+00 4.43778664e-01 7.31629878e-02 1.13591775e-01 6.84094548e-01 5.35355985e-01 -6.55197203e-01 -2.52143323e-01 -1.02623296e+00 3.74600500e-01 1.45896554e+00 -5.28947234e-01 -7.94933796e-01 2.39826918e-01 5.17101049e-01 -5.32119274e-01 -1.17302322e+00 8.04194510e-01 7.18809366e-01 -1.15466309e+00 9.93510365e-01 -8.00894976e-01 2.49024674e-01 -4.04847682e-01 -8.92670453e-02 -1.22108173e+00 -2.58842081e-01 -3.18421721e-01 2.24056333e-01 1.71754324e+00 8.11140120e-01 -8.45306933e-01 6.02338493e-01 7.24149108e-01 -2.07824901e-01 -7.88311660e-01 -5.41209698e-01 -1.04766834e+00 1.61557868e-01 -2.31806949e-01 9.77198839e-01 1.27431834e+00 2.33944263e-02 1.69317797e-01 1.59622803e-01 -5.36722094e-02 5.06811559e-01 4.46304560e-01 1.02561486e+00 -1.53621364e+00 -9.40834209e-02 -8.27374816e-01 -4.67215866e-01 -6.50146306e-01 2.52819747e-01 -1.21911907e+00 -3.52229506e-01 -1.38776457e+00 3.20682704e-01 -1.04630935e+00 -4.39707577e-01 3.23017746e-01 -3.77825558e-01 1.29022613e-01 9.95287076e-02 4.62431729e-01 -7.70542145e-01 4.75520492e-02 5.84316492e-01 -3.15666338e-03 -1.35421231e-01 2.02993572e-01 -7.43369579e-01 1.53399482e-01 7.17038453e-01 -5.51376164e-01 -3.45518023e-01 -4.89018321e-01 4.79057670e-01 -3.24380815e-01 8.71968269e-02 -1.08583856e+00 3.70166659e-01 3.62861454e-02 -3.66481021e-02 -3.77581000e-01 -6.10539652e-02 -6.68018281e-01 6.95029974e-01 2.25059107e-01 -3.48854095e-01 4.52819496e-01 6.39392659e-02 1.15193777e-01 -4.74600881e-01 -4.00975198e-01 4.09378469e-01 4.35414650e-02 -7.28159487e-01 1.42664403e-01 3.13995034e-01 3.59989792e-01 1.16072822e+00 -4.65636730e-01 -6.29965842e-01 1.00088738e-01 -5.11934817e-01 4.42775279e-01 9.01508033e-01 8.65875483e-01 -7.15089291e-02 -1.42500913e+00 -7.93395340e-01 -1.04288384e-01 8.66281748e-01 -1.37151703e-01 -4.12299335e-02 8.76510978e-01 -1.57867506e-01 4.16742444e-01 -4.17659044e-01 -4.04849857e-01 -1.37228358e+00 6.54735863e-01 4.44147676e-01 -6.01205349e-01 -4.05760080e-01 3.74101967e-01 -2.02777926e-02 -8.10831845e-01 3.05671781e-01 -2.57690519e-01 -4.30427492e-01 3.53354871e-01 4.98574167e-01 3.05429518e-01 6.83759749e-01 -3.37663621e-01 -5.24650395e-01 5.57786286e-01 -1.28800854e-01 2.09957778e-01 1.14808118e+00 6.99766427e-02 -8.29156786e-02 4.00044322e-01 1.15796316e+00 1.29782572e-01 -5.77674210e-01 -4.08399761e-01 7.93695688e-01 -3.85528952e-01 -6.56317770e-01 -5.84227145e-01 -8.13855112e-01 5.30810773e-01 4.62240815e-01 5.52082837e-01 9.40945745e-01 5.66736038e-04 5.38776636e-01 2.01990798e-01 4.63032514e-01 -7.61803329e-01 -5.26623130e-01 5.71441829e-01 7.68702149e-01 -1.22740483e+00 5.56965033e-03 -6.56871319e-01 -1.84144884e-01 9.02876437e-01 5.04742146e-01 1.92678168e-01 4.65323091e-01 4.32139903e-01 8.19789320e-02 -3.31109792e-01 -8.01601887e-01 -3.90689939e-01 5.67908585e-01 5.81434190e-01 8.67626309e-01 -1.26829952e-01 -6.67458475e-01 7.99675405e-01 -2.75389194e-01 -2.33287122e-02 -1.99813154e-02 9.72281039e-01 -5.12094535e-02 -1.91216934e+00 -1.08861007e-01 5.43805897e-01 -4.59503740e-01 5.31113660e-03 -4.52322781e-01 9.61820006e-01 1.54482454e-01 6.47553146e-01 1.25032440e-01 -5.10828674e-01 1.01800573e+00 1.61652535e-01 4.51735675e-01 -6.62984610e-01 -1.13354349e+00 -8.55677843e-01 4.90397960e-01 -5.03693104e-01 -3.98532391e-01 -6.35857582e-01 -7.82736838e-01 -3.53669941e-01 -2.80745804e-01 3.40252608e-01 5.39369464e-01 8.48448753e-01 6.66767895e-01 2.44198054e-01 2.97803462e-01 -5.14371276e-01 -7.38800287e-01 -1.06378734e+00 -1.47442982e-01 1.09315395e+00 -5.11432439e-02 -9.50388134e-01 -2.22789198e-01 -2.30393708e-01]	[9.488061904907227, 8.438007354736328]
bbee712a-b697-4cfc-80b6-558ee0ab783c	hierarchical-video-moment-retrieval-and-step	2303.16406	null	https://arxiv.org/abs/2303.16406v1	https://arxiv.org/pdf/2303.16406v1.pdf	Hierarchical Video-Moment Retrieval and Step-Captioning	There is growing interest in searching for information from large video corpora. Prior works have studied relevant tasks, such as text-based video retrieval, moment retrieval, video summarization, and video captioning in isolation, without an end-to-end setup that can jointly search from video corpora and generate summaries. Such an end-to-end setup would allow for many interesting applications, e.g., a text-based search that finds a relevant video from a video corpus, extracts the most relevant moment from that video, and segments the moment into important steps with captions. To address this, we present the HiREST (HIerarchical REtrieval and STep-captioning) dataset and propose a new benchmark that covers hierarchical information retrieval and visual/textual stepwise summarization from an instructional video corpus. HiREST consists of 3.4K text-video pairs from an instructional video dataset, where 1.1K videos have annotations of moment spans relevant to text query and breakdown of each moment into key instruction steps with caption and timestamps (totaling 8.6K step captions). Our hierarchical benchmark consists of video retrieval, moment retrieval, and two novel moment segmentation and step captioning tasks. In moment segmentation, models break down a video moment into instruction steps and identify start-end boundaries. In step captioning, models generate a textual summary for each step. We also present starting point task-specific and end-to-end joint baseline models for our new benchmark. While the baseline models show some promising results, there still exists large room for future improvement by the community. Project website: https://hirest-cvpr2023.github.io	['Mohit Bansal', 'Yasher Mehdad', 'Barlas Oğuz', 'Xilun Chen', 'Satwik Kottur', 'Jaemin Cho', 'Abhay Zala']	2023-03-29	null	http://openaccess.thecvf.com//content/CVPR2023/html/Zala_Hierarchical_Video-Moment_Retrieval_and_Step-Captioning_CVPR_2023_paper.html	http://openaccess.thecvf.com//content/CVPR2023/papers/Zala_Hierarchical_Video-Moment_Retrieval_and_Step-Captioning_CVPR_2023_paper.pdf	cvpr-2023-1	['video-captioning', 'moment-retrieval', 'video-retrieval']	['computer-vision', 'computer-vision', 'computer-vision']	[ 4.75870341e-01 -2.14968354e-01 -6.90852344e-01 -2.23255947e-01 -1.72397852e+00 -7.81749845e-01 5.11314571e-01 3.16044450e-01 -4.27123934e-01 4.04769510e-01 8.17485869e-01 -1.08649559e-01 1.37799687e-03 2.58481950e-02 -1.07504535e+00 -4.31717485e-01 4.86151461e-04 3.32996339e-01 4.91073728e-01 7.28730261e-02 5.90594232e-01 -6.34940807e-03 -1.65405738e+00 8.26092541e-01 6.29817486e-01 8.37986887e-01 4.74461585e-01 1.34280527e+00 -4.49692793e-02 1.03304267e+00 -9.37894404e-01 -2.37482011e-01 -1.23796865e-01 -6.07952774e-01 -1.06183171e+00 2.54536271e-01 1.18255043e+00 -6.84868753e-01 -7.91090548e-01 6.83931112e-01 6.81385696e-01 6.00572228e-01 5.72877824e-01 -1.38014007e+00 -3.71242970e-01 9.17057693e-01 -5.67746997e-01 5.36386728e-01 8.97238493e-01 7.80646130e-02 8.62363696e-01 -5.90020657e-01 1.05360150e+00 1.04950678e+00 2.57145137e-01 5.74965954e-01 -7.33830154e-01 -4.91014987e-01 2.11128905e-01 5.06295979e-01 -1.04116774e+00 -6.70503676e-01 6.14457011e-01 -4.62017804e-01 1.07452130e+00 4.64431852e-01 6.90705597e-01 1.30271816e+00 5.73494248e-02 1.64753962e+00 2.36406177e-01 -3.52157563e-01 -6.72318712e-02 -3.23151350e-01 3.78071517e-01 4.93250817e-01 -1.91792175e-01 -7.35401034e-01 -9.45710719e-01 1.30698398e-01 5.00650823e-01 9.54561122e-03 -5.15562177e-01 -1.52024865e-01 -1.57997239e+00 4.46933538e-01 -1.08615272e-01 6.69166520e-02 -2.56949365e-01 2.60098249e-01 9.83518362e-01 3.18969667e-01 3.47660065e-01 4.64824706e-01 -2.00814918e-01 -8.28662813e-01 -1.57971442e+00 5.20289123e-01 8.22591245e-01 1.43868577e+00 4.75626945e-01 -1.67384088e-01 -8.35003316e-01 7.59297252e-01 -1.71408787e-01 4.59975660e-01 7.59014904e-01 -1.35907423e+00 9.00175154e-01 1.34118602e-01 8.85593612e-03 -8.25861990e-01 8.73305369e-03 2.12995395e-01 -1.66388437e-01 -7.79098272e-01 9.87292379e-02 2.05108244e-03 -1.11035907e+00 1.42143595e+00 7.48945996e-02 3.88060361e-01 1.09509937e-01 8.05206299e-01 1.48601341e+00 1.17309666e+00 -5.25540439e-03 -4.65555221e-01 1.50712597e+00 -1.63485312e+00 -9.35728550e-01 -2.16710344e-01 7.51727402e-01 -1.13381660e+00 1.18314886e+00 2.19165519e-01 -1.57422781e+00 -5.34421384e-01 -8.06137025e-01 -5.23386061e-01 -4.65761162e-02 2.16631427e-01 2.09638793e-02 -1.61612481e-01 -1.20801461e+00 2.23465055e-01 -8.29895020e-01 -5.21101415e-01 -1.72657456e-04 7.05288649e-02 -2.92376697e-01 -3.49627376e-01 -8.83324265e-01 2.71806419e-01 4.88525748e-01 -2.15252578e-01 -1.18748558e+00 -8.59813273e-01 -1.16000688e+00 8.89122263e-02 8.81599367e-01 -6.72641337e-01 1.84374106e+00 -7.19921350e-01 -1.28526485e+00 7.82617092e-01 -4.39084232e-01 -4.58413482e-01 3.10101956e-01 -6.26207292e-01 -7.38743395e-02 9.04761136e-01 3.70184749e-01 1.03414130e+00 9.15039241e-01 -8.04830492e-01 -7.20057249e-01 8.31386372e-02 1.03800200e-01 5.57717085e-01 -3.48794937e-01 3.40205520e-01 -1.47982144e+00 -7.30819821e-01 -2.90406793e-01 -1.08223498e+00 9.64084566e-02 -6.37582064e-01 -5.65823793e-01 -3.84330362e-01 9.15375173e-01 -9.86424863e-01 1.77645612e+00 -2.13653827e+00 3.80825400e-01 -5.36623120e-01 1.31080359e-01 1.08691059e-01 -4.61542696e-01 6.69998467e-01 -1.34350993e-02 1.75868988e-01 1.35119602e-01 -5.44844806e-01 -4.34445813e-02 -2.52492636e-01 -4.63305861e-01 1.04731970e-01 -1.05578229e-01 9.85424519e-01 -1.02972627e+00 -9.46762919e-01 1.72999337e-01 3.95667255e-01 -5.88344634e-01 4.09567088e-01 -4.74532962e-01 1.61838289e-02 -6.04898512e-01 7.13151217e-01 5.36413379e-02 -2.56290346e-01 -3.07812184e-01 -2.98287809e-01 -3.30830887e-02 2.97021717e-01 -7.54251719e-01 2.22422791e+00 -2.83472896e-01 1.22892690e+00 -6.47419319e-02 -7.12351501e-01 3.46342355e-01 5.23006916e-01 7.79187620e-01 -5.47428250e-01 -7.06553310e-02 -7.94514343e-02 -6.52518690e-01 -9.82182741e-01 1.25520778e+00 6.88563883e-01 -5.45923233e-01 3.82355630e-01 1.47585973e-01 -2.90567547e-01 9.79278386e-01 9.02721643e-01 1.33858228e+00 3.79769325e-01 -4.57931310e-03 2.83311635e-01 2.76130944e-01 5.05016565e-01 1.11016110e-01 7.53639698e-01 -2.16305614e-01 1.06014729e+00 7.30256438e-01 -1.00308903e-01 -9.14779782e-01 -6.75716102e-01 4.16719943e-01 1.49592578e+00 2.75177956e-01 -9.92357969e-01 -8.73398960e-01 -6.54175699e-01 -3.39810073e-01 6.52066231e-01 -2.94260025e-01 -1.52988300e-01 -9.06106770e-01 -5.15343845e-02 4.84945893e-01 3.92478704e-01 2.38259256e-01 -1.18558848e+00 -5.14713466e-01 1.68079957e-01 -9.62995887e-01 -1.52156913e+00 -1.28677213e+00 -2.75775999e-01 -6.84395373e-01 -9.76800084e-01 -1.12518287e+00 -1.05074465e+00 4.19954002e-01 8.25765729e-01 1.37899065e+00 -8.97274986e-02 -1.71840742e-01 1.09125090e+00 -6.94351315e-01 -1.27397208e-02 -3.93125296e-01 2.88359493e-01 -2.73025900e-01 -4.93755013e-01 1.72773272e-01 -1.13029517e-02 -6.76931620e-01 2.65060008e-01 -1.19767237e+00 3.02983671e-01 5.60778320e-01 3.78163099e-01 7.82753825e-01 -3.98014337e-01 3.31131011e-01 -4.98854250e-01 6.83689058e-01 -6.04435802e-01 -2.87576705e-01 4.79584098e-01 5.00071272e-02 -1.67899564e-01 4.34312701e-01 -5.84604681e-01 -8.38805974e-01 5.50317578e-03 1.38232976e-01 -9.17147160e-01 -2.24838972e-01 6.91102803e-01 1.24797530e-01 5.76340556e-01 3.95955801e-01 5.34860611e-01 -2.88217396e-01 -3.45681995e-01 3.21979135e-01 7.07432568e-01 8.86171222e-01 -6.87000871e-01 3.62491578e-01 -9.43147764e-02 -3.88216913e-01 -1.09756672e+00 -8.89587164e-01 -1.03943205e+00 -4.19143021e-01 -4.53971297e-01 1.01080322e+00 -1.25481272e+00 -5.74120820e-01 1.98854521e-01 -1.15785491e+00 -4.87732649e-01 -2.03812316e-01 5.33640325e-01 -8.81131113e-01 7.18581557e-01 -9.97302532e-01 -1.78944901e-01 -5.51505685e-01 -1.58588088e+00 1.51528513e+00 3.86104882e-01 -4.32470381e-01 -5.66275716e-01 -6.54654354e-02 9.27125633e-01 -1.08891748e-01 1.78969264e-01 3.60318720e-01 -8.69323373e-01 -7.16946542e-01 -5.11971235e-01 4.94644716e-02 8.06725919e-02 -2.30495170e-01 4.82373565e-01 -5.09561896e-01 -4.20628577e-01 -4.11780536e-01 -6.57770872e-01 1.07569766e+00 6.48448110e-01 1.33567739e+00 -5.23514390e-01 -3.83779973e-01 4.54275995e-01 1.08634758e+00 3.13074589e-01 4.52672213e-01 4.12230968e-01 8.38129401e-01 4.83693957e-01 1.00305247e+00 2.11309791e-01 5.10641754e-01 6.78936899e-01 9.93423238e-02 3.41986090e-01 -3.34253103e-01 -4.09741163e-01 9.05961931e-01 1.34615088e+00 2.35082373e-01 -7.46932030e-01 -7.52452970e-01 9.13027406e-01 -1.98534048e+00 -1.27074873e+00 5.46730086e-02 2.14096308e+00 9.54107463e-01 -6.68936642e-03 3.21891844e-01 -2.61691034e-01 7.09460020e-01 4.78930473e-01 -5.59930921e-01 -3.54505926e-01 2.28795975e-01 -3.58972490e-01 2.36668050e-01 3.43293339e-01 -1.13482547e+00 1.00532770e+00 5.39098454e+00 1.22516155e+00 -1.01049268e+00 -1.88673630e-01 6.65188730e-01 -6.21012449e-01 -1.53616592e-01 -1.58777714e-01 -1.10200906e+00 4.82166886e-01 1.21097493e+00 -5.92067838e-01 1.55859381e-01 8.15911412e-01 4.29158747e-01 -3.19070846e-01 -1.37225783e+00 1.04474556e+00 6.49386823e-01 -1.47825396e+00 3.25223088e-01 -2.70812362e-01 9.85459924e-01 -5.98876067e-02 -5.61127067e-02 7.22986400e-01 -1.03655182e-01 -6.29082084e-01 8.47869098e-01 2.06324875e-01 8.37158024e-01 -5.61301529e-01 3.87372106e-01 2.09032059e-01 -1.32972431e+00 2.09074989e-01 -6.67840019e-02 3.54187667e-01 3.47598165e-01 1.71939775e-01 -9.27290499e-01 5.61005771e-01 7.19589293e-01 9.95756388e-01 -7.41331041e-01 1.31020713e+00 -4.76366282e-03 6.60896480e-01 -1.55843630e-01 5.26102707e-02 5.24793983e-01 4.75403741e-02 7.62819231e-01 1.64099991e+00 4.46625650e-01 8.09855685e-02 5.32915235e-01 1.05834402e-01 -4.13287103e-01 1.93097308e-01 -6.35450780e-01 -4.34319586e-01 5.31577647e-01 1.24670553e+00 -9.88911092e-01 -8.37451816e-01 -3.73381585e-01 1.09515297e+00 -1.54866964e-01 6.59957767e-01 -1.07289755e+00 -6.26731575e-01 3.66620928e-01 5.89458384e-02 3.61014545e-01 -2.00112060e-01 4.84437138e-01 -1.32190251e+00 1.78472087e-01 -1.10961258e+00 5.65599203e-01 -1.16555846e+00 -6.30535007e-01 4.39865321e-01 6.18022084e-01 -1.31320095e+00 -7.63435304e-01 -6.87903836e-02 -5.32368183e-01 1.84012502e-01 -1.24619496e+00 -8.26982439e-01 -4.35564727e-01 5.54469347e-01 1.64771724e+00 2.41816968e-01 2.15501875e-01 3.64120662e-01 -7.08347142e-01 5.03932476e-01 1.36037096e-01 1.57298669e-01 1.30445659e+00 -1.06705010e+00 1.73281938e-01 9.78348970e-01 4.63473573e-02 5.01123369e-01 8.48867893e-01 -8.39735448e-01 -1.73248208e+00 -1.05552280e+00 7.83959746e-01 -6.36151791e-01 6.91314697e-01 -1.71827927e-01 -7.36478329e-01 9.61728632e-01 7.06595838e-01 -3.25128049e-01 6.23063803e-01 -3.63359064e-01 -3.28768343e-02 1.20334215e-01 -4.00732636e-01 9.22004879e-01 9.20706630e-01 -5.17576814e-01 -6.36143565e-01 8.11466217e-01 1.36430287e+00 -8.88751566e-01 -8.56522560e-01 1.35682642e-01 5.02723753e-01 -6.10589087e-01 1.00701642e+00 -4.12686050e-01 1.05481768e+00 -1.06780007e-01 4.62990664e-02 -1.08982241e+00 1.11454442e-01 -1.05598629e+00 -3.54536176e-01 1.44804561e+00 2.91353315e-01 4.45822448e-01 7.19712853e-01 6.94919646e-01 -7.43261337e-01 -6.41886413e-01 -5.40512145e-01 -6.02644563e-01 -3.46775413e-01 -4.47902858e-01 1.54663950e-01 6.70093715e-01 2.03458294e-01 5.15757143e-01 -4.56599474e-01 -2.50832170e-01 3.31135154e-01 2.80118495e-01 1.00598216e+00 -5.56043506e-01 7.86401052e-03 -5.94283819e-01 -8.77941102e-02 -1.62524784e+00 3.16894263e-01 -7.15274572e-01 4.22314882e-01 -1.94874191e+00 5.82477391e-01 5.45585930e-01 6.31314050e-03 3.77913237e-01 -3.20529163e-01 8.84612054e-02 4.48968470e-01 3.33183080e-01 -1.59012842e+00 2.75735617e-01 1.42273569e+00 -4.01169360e-01 -5.02783477e-01 -2.32028723e-01 -3.93302441e-01 3.67878944e-01 5.39489925e-01 -3.24353486e-01 -5.88087022e-01 -6.14777744e-01 2.41364706e-02 7.66219437e-01 -1.11419261e-02 -1.07946050e+00 5.63384712e-01 -2.76250809e-01 1.24024451e-01 -1.00285923e+00 4.41358924e-01 -3.95887107e-01 -1.30035043e-01 4.22674976e-02 -7.94843912e-01 3.42562854e-01 4.17891353e-01 4.17882144e-01 -6.01654470e-01 -4.50992405e-01 8.59914050e-02 -1.08178720e-01 -1.08091164e+00 3.70050192e-01 -6.74152255e-01 3.27220708e-01 1.10201550e+00 -4.27506953e-01 -6.50970638e-01 -7.21403241e-01 -6.56358480e-01 6.09169245e-01 5.54356754e-01 7.70731509e-01 7.44823515e-01 -1.13353181e+00 -8.14234972e-01 -3.31672549e-01 2.93623596e-01 2.48560935e-01 5.20112753e-01 7.75641859e-01 -6.31915092e-01 6.93517923e-01 4.30039763e-02 -7.61235297e-01 -1.73205829e+00 6.58752382e-01 -5.16702831e-01 -2.50587374e-01 -5.44260740e-01 7.45457232e-01 2.41149276e-01 3.23222429e-01 5.64443409e-01 -6.06854737e-01 -3.48167181e-01 4.23690826e-01 7.99669981e-01 4.02616590e-01 -1.38131574e-01 -7.26704478e-01 -1.75508130e-02 6.27276599e-01 -4.26441699e-01 -4.81717624e-02 1.06910217e+00 -3.70859295e-01 2.04723433e-01 3.58539760e-01 1.62862897e+00 -3.16061229e-02 -1.11089921e+00 -2.38958634e-02 -3.08354944e-02 -3.08561027e-01 -1.19849272e-01 -4.51536030e-01 -8.46212745e-01 6.59198582e-01 -1.19005404e-02 1.27315730e-01 1.24910522e+00 1.15056098e-01 1.27807498e+00 4.97272104e-01 -1.55842274e-01 -1.06996620e+00 5.15544295e-01 6.07843161e-01 8.13207865e-01 -1.24689722e+00 1.49270162e-01 -2.49564037e-01 -7.61068344e-01 1.10589683e+00 7.34394550e-01 2.56337941e-01 -7.08965510e-02 -6.53482229e-02 -2.39529312e-01 -1.07813329e-01 -1.07694829e+00 -3.70173492e-02 6.50209963e-01 1.71517283e-01 5.44129372e-01 -1.81912899e-01 -1.70398682e-01 4.26680863e-01 -1.71516597e-01 8.78672227e-02 9.27749693e-01 1.17722070e+00 -4.43337977e-01 -6.16468072e-01 -3.93641710e-01 4.63230729e-01 -7.07791388e-01 -1.74480602e-01 -3.46257299e-01 6.55361772e-01 -6.76289976e-01 9.92844582e-01 2.17570886e-01 -2.27059901e-01 3.71153265e-01 1.75887018e-01 2.82581002e-01 -7.76050270e-01 -6.05651796e-01 4.72524583e-01 1.56319141e-01 -8.21549416e-01 -3.39936405e-01 -6.27097964e-01 -1.21711624e+00 -2.44251058e-01 4.56493236e-02 5.68639398e-01 6.95851386e-01 4.98543888e-01 5.85938632e-01 7.31818199e-01 2.70043135e-01 -1.12490928e+00 -3.12857591e-02 -9.09629464e-01 1.00392021e-01 5.24925232e-01 4.40811902e-01 -7.48959854e-02 -3.18175495e-01 6.70438528e-01]	[10.323317527770996, 0.6943582892417908]
eef01024-29e5-49b7-a615-4e607e649a83	dynamic-knowledge-graphs-as-semantic-memory	2101.01099	null	https://arxiv.org/abs/2101.01099v3	https://arxiv.org/pdf/2101.01099v3.pdf	Dynamic Knowledge Graphs as Semantic Memory Model for Industrial Robots	In this paper, we present a model for semantic memory that allows machines to collect information and experiences to become more proficient with time. Post semantic analysis of the sensory and other related data, the processed information is stored in the knowledge graph which is then used to comprehend the work instructions expressed in natural language. This imparts industrial robots cognitive behavior to execute the required tasks in a deterministic manner. The paper outlines the architecture of the system along with an implementation of the proposal.	['Said Zahrai', 'Vishakh Duggal', 'Mohak Sukhwani']	2021-01-04	null	null	null	null	['industrial-robots']	['robots']	[ 3.24971259e-01 3.81692231e-01 -5.76947331e-02 -5.67464888e-01 7.20921457e-01 -5.19324362e-01 5.38146794e-01 5.47385693e-01 -3.24956506e-01 8.25654387e-01 -4.52814102e-02 -9.04947072e-02 -4.79811370e-01 -1.20645511e+00 -5.12953520e-01 -1.02542110e-01 2.42496535e-01 5.52462339e-01 5.88929713e-01 -4.37693477e-01 7.57852435e-01 6.20099187e-01 -2.10205483e+00 4.20126915e-01 4.84007955e-01 7.91819453e-01 1.19072497e+00 5.09179056e-01 -5.24330139e-01 1.26523137e+00 -5.63011408e-01 4.41897333e-01 -2.83013850e-01 -4.47496474e-01 -1.58254218e+00 1.23859875e-01 -7.38219917e-01 8.92874151e-02 2.74770483e-02 1.10669386e+00 -2.97176600e-01 5.61938465e-01 5.31521678e-01 -1.00263286e+00 -5.07790625e-01 5.32361627e-01 5.72644532e-01 1.13070775e-02 9.74971592e-01 -6.87742308e-02 1.66794851e-01 -5.84723949e-01 9.22875345e-01 1.39590859e+00 1.07142113e-01 4.41849738e-01 -5.86525440e-01 6.65268525e-02 -1.44623220e-01 7.37576902e-01 -1.02799439e+00 -1.25020787e-01 6.81628048e-01 -3.62756878e-01 1.51525724e+00 -3.31595987e-02 9.40218747e-01 6.71222627e-01 6.11799181e-01 3.17681313e-01 1.40967596e+00 -9.97091889e-01 5.97751081e-01 4.23996210e-01 8.13758671e-01 7.61781335e-01 5.71965158e-01 6.06848821e-02 -7.44038165e-01 5.64193606e-01 7.01648653e-01 1.03772596e-01 2.56111473e-01 -3.97396237e-01 -9.36543167e-01 3.01699758e-01 2.47842371e-01 9.17102754e-01 -9.15416121e-01 -2.40226001e-01 4.24247026e-01 5.01489520e-01 -3.40274692e-01 5.16247928e-01 -4.26271826e-01 -2.76538521e-01 -1.32438883e-01 -1.84068959e-02 1.13507926e+00 1.04257381e+00 9.29015696e-01 -1.21085905e-01 3.50571990e-01 3.07791948e-01 5.06347656e-01 5.93300104e-01 6.19440794e-01 -9.13434863e-01 5.48633635e-02 1.19492960e+00 1.62374854e-01 -1.02226865e+00 -5.03604293e-01 1.42742828e-01 -7.17777461e-02 5.70178807e-01 6.20788410e-02 2.16838241e-01 -9.57633674e-01 1.20725620e+00 1.63633555e-01 -2.47773096e-01 6.83336735e-01 9.67057824e-01 6.09059572e-01 6.67382598e-01 4.83482689e-01 -1.64734140e-01 1.64933121e+00 -6.61109269e-01 -1.25836718e+00 -3.54686141e-01 4.45669025e-01 -5.15598893e-01 8.57948065e-01 4.03049439e-01 -8.55863929e-01 -8.76501679e-01 -1.32292378e+00 -1.37214854e-01 -1.07276487e+00 -1.15566775e-01 5.90142667e-01 2.34618396e-01 -1.04723728e+00 7.81962752e-01 -8.50771964e-01 -1.09579456e+00 -1.14823349e-01 3.37677985e-01 -4.05866206e-01 5.79542071e-02 -1.17155325e+00 1.58157849e+00 1.46209216e+00 1.63684919e-01 -9.19469118e-01 1.53722251e-02 -9.99104142e-01 -7.11835325e-02 4.87887084e-01 -6.89560950e-01 1.23510432e+00 -7.07188845e-01 -1.67632008e+00 8.80245566e-01 -1.38986766e-01 -4.95243102e-01 -1.29795000e-01 -1.55476913e-01 -6.35128975e-01 4.01586801e-01 8.57408270e-02 1.55975208e-01 2.35589325e-01 -1.30154288e+00 -6.05743229e-01 -8.40479910e-01 1.95412353e-01 2.29617327e-01 4.61821109e-02 -2.73062706e-01 -6.77421838e-02 1.71888411e-01 1.96152359e-01 -5.49488962e-01 -1.80058032e-01 -7.35051334e-01 5.84404133e-02 -2.72251487e-01 8.76694202e-01 -3.83110136e-01 9.30674553e-01 -2.08947253e+00 1.45406485e-01 4.45334285e-01 -1.51499674e-01 2.79460847e-01 1.80388108e-01 9.04221833e-01 5.53597324e-02 -3.40429217e-01 2.68411934e-01 2.24880263e-01 9.18635353e-02 6.51544333e-01 -1.37357816e-01 -3.34857315e-01 -2.05523729e-01 6.30573809e-01 -1.11192906e+00 -5.83450854e-01 8.94689023e-01 -8.88865143e-02 9.57991034e-02 4.48267311e-01 -2.54230261e-01 3.41476083e-01 -1.15084457e+00 3.89502048e-01 8.84922147e-02 3.19711156e-02 5.34002781e-01 1.09380208e-01 -2.24088490e-01 4.76673096e-01 -1.04951143e+00 1.96405470e+00 -6.44894838e-01 3.43173742e-01 -5.80266193e-02 -1.16422999e+00 1.15181148e+00 5.04074156e-01 7.93679506e-02 -9.12413001e-01 4.48669046e-01 1.17983386e-01 -6.55257821e-01 -1.02420723e+00 5.07563651e-01 -1.00340664e-01 -2.92863846e-02 3.78066272e-01 3.08092497e-02 -3.52477252e-01 4.83071595e-01 -1.69188215e-03 9.47502136e-01 4.32881176e-01 7.41092026e-01 -4.32614118e-01 8.02717209e-01 6.66086495e-01 -1.63222179e-02 4.68540221e-01 3.31911258e-02 -6.09959722e-01 -7.22308364e-03 -8.46724689e-01 -7.41791070e-01 -1.16974461e+00 4.00460154e-01 8.03645492e-01 5.65624058e-01 -2.21367747e-01 -1.06027961e+00 -2.56783485e-01 -3.38617176e-01 1.39423299e+00 -2.53919154e-01 -4.17975485e-01 -1.90827459e-01 2.10379615e-01 -1.46664798e-01 3.21292609e-01 8.20163667e-01 -1.88603759e+00 -1.55895066e+00 3.00011396e-01 2.80981474e-02 -1.07476425e+00 6.93550646e-01 2.91810662e-01 -1.20562530e+00 -1.07358325e+00 5.02913654e-01 -1.05727386e+00 7.41527915e-01 1.82444245e-01 8.36145937e-01 4.64865901e-02 -2.72910863e-01 6.50999427e-01 -7.48030961e-01 -8.47746372e-01 -7.91552067e-01 -9.82036963e-02 -7.78133869e-02 -5.15016675e-01 8.06827426e-01 -5.08590758e-01 -1.40830398e-01 -1.32859692e-01 -9.96713758e-01 1.37152404e-01 5.23805916e-01 1.97538152e-01 4.80949163e-01 7.07429647e-01 4.53639746e-01 -6.76212966e-01 9.30144310e-01 -3.01787674e-01 -4.88112152e-01 3.79565060e-01 -8.92430425e-01 5.66547453e-01 5.59889019e-01 1.79189488e-01 -1.56808436e+00 3.15086961e-01 3.25421631e-01 1.67141840e-01 -6.44527972e-01 6.86794817e-01 -2.20720947e-01 3.10481399e-01 5.07396877e-01 4.26869899e-01 3.31677616e-01 -4.56586689e-01 2.12347165e-01 7.41284490e-01 6.54718280e-01 -5.16693652e-01 4.18718196e-02 1.52563572e-01 2.39905745e-01 -7.19383061e-01 -5.93587637e-01 -3.59211951e-01 -9.36200321e-01 -6.14091456e-01 1.27272487e+00 -3.60406965e-01 -1.02990317e+00 1.32778391e-01 -1.23397839e+00 -4.66094837e-02 -5.63512683e-01 6.38680875e-01 -9.85763967e-01 -7.99553692e-02 -4.51455623e-01 -1.09813428e+00 1.32967858e-02 -8.28387856e-01 6.50260746e-01 4.09735769e-01 -5.75449288e-01 -9.87982512e-01 -1.01928473e-01 2.99318880e-01 1.69053674e-01 1.15854390e-01 1.07076824e+00 -6.99020624e-01 -6.34559810e-01 -1.79120913e-01 1.07830890e-01 3.38090330e-01 3.44588578e-01 -5.46093643e-01 -6.59895301e-01 4.16096509e-01 3.05007398e-01 -2.18024269e-01 2.88851231e-01 6.97109178e-02 8.42411995e-01 1.18959449e-01 -6.56552911e-01 -2.37982482e-01 1.50983310e+00 1.00588822e+00 7.45626390e-01 4.61858690e-01 9.35232192e-02 8.67832363e-01 1.05966401e+00 1.66338652e-01 3.12369496e-01 3.16613913e-01 4.37146693e-01 4.52365905e-01 3.16133760e-02 -3.09321642e-01 2.04080999e-01 8.88670146e-01 -4.52642918e-01 1.62872300e-01 -6.86243117e-01 4.22682703e-01 -2.03011918e+00 -1.04671133e+00 -1.84497073e-01 1.73891902e+00 5.15955865e-01 9.69834104e-02 -3.71234536e-01 3.29482585e-01 6.07659280e-01 -3.25367182e-01 -1.74580216e-01 -1.03701723e+00 4.00276840e-01 4.34628040e-01 3.21742773e-01 6.30965590e-01 -6.87888861e-01 1.27839160e+00 7.06922245e+00 2.13481039e-01 -6.97711587e-01 -3.93517129e-03 -3.20455402e-01 4.60995674e-01 1.43444538e-01 5.65869063e-02 -2.75468737e-01 1.59035161e-01 1.29277432e+00 -4.63717043e-01 8.27863216e-01 1.05370545e+00 4.20264244e-01 -7.58039236e-01 -1.13165617e+00 8.61056089e-01 5.12219705e-02 -1.09306741e+00 2.92459190e-01 -3.57608050e-01 2.04509228e-01 -5.91091394e-01 -5.24834931e-01 -2.79313661e-02 3.25408280e-01 -8.78181279e-01 8.70357573e-01 1.16422105e+00 5.60566690e-03 -7.06114173e-01 8.07734847e-01 4.70724255e-01 -1.05615973e+00 -4.05549318e-01 -5.77129126e-01 -7.49598682e-01 3.18372577e-01 3.10902447e-01 -1.24406147e+00 1.11448979e+00 4.79540706e-01 3.55290443e-01 -3.21594387e-01 4.06868756e-01 -4.90911871e-01 -2.29852032e-02 -6.67251199e-02 -5.97674727e-01 -3.90712870e-03 -2.22508147e-01 3.97753924e-01 7.84702241e-01 5.41996896e-01 2.60795861e-01 1.60192534e-01 9.18849587e-01 6.55082166e-01 1.46476731e-01 -1.11469722e+00 -4.22145218e-01 5.88078678e-01 7.44559288e-01 -1.12645018e+00 -7.41095781e-01 4.00916068e-03 1.16993976e+00 1.58681914e-01 2.14441374e-01 -2.08793685e-01 -5.92526376e-01 1.58032566e-01 6.26085699e-03 -1.11971140e-01 -4.20182407e-01 -2.81081438e-01 -4.74624038e-01 1.74497411e-01 -3.47343117e-01 2.99837649e-01 -1.45777249e+00 -7.84186125e-01 5.78784943e-01 4.40789253e-01 -6.46131039e-01 -6.22860372e-01 -1.04867196e+00 -1.62609681e-01 8.21946681e-01 -8.91403377e-01 -8.18637908e-01 -4.75357503e-01 7.63542712e-01 5.10745704e-01 -4.11794186e-01 1.26806009e+00 -2.49657303e-01 1.21924654e-01 -7.72212565e-01 -6.46153986e-01 -2.47584820e-01 8.50692019e-02 -1.03560221e+00 -3.14028919e-01 6.95380151e-01 -8.25645626e-02 7.46549070e-01 8.77818465e-01 -1.03672910e+00 -1.42981744e+00 -5.68474114e-01 1.08206260e+00 -3.95516634e-01 4.33158249e-01 1.74884200e-01 -5.65586329e-01 8.16899478e-01 4.51657444e-01 -5.93866944e-01 4.07418728e-01 -2.97593623e-01 9.84495133e-02 -2.47136354e-01 -1.21891677e+00 3.61417472e-01 1.10016298e+00 -6.43490195e-01 -1.64818978e+00 3.04308776e-02 8.49948108e-01 -4.50664908e-02 -6.90606833e-01 -4.58579212e-02 3.70946616e-01 -9.95481491e-01 7.03230858e-01 -7.33286619e-01 2.60228634e-01 -5.87632656e-01 -1.39498547e-01 -1.17917860e+00 -2.20865428e-01 -1.55622795e-01 2.94082403e-01 7.75210381e-01 2.86294162e-01 -7.81549573e-01 3.71610343e-01 5.43989241e-01 -4.43759799e-01 1.13315798e-01 -5.28515756e-01 -7.26398826e-01 -7.73800194e-01 -6.00749612e-01 7.56524384e-01 7.84745991e-01 7.40034461e-01 4.17606145e-01 2.88345367e-01 9.16856304e-02 4.83054161e-01 2.62918591e-01 2.57457614e-01 -1.47730219e+00 2.40625873e-01 -2.35428959e-02 -8.62587154e-01 -5.75291157e-01 2.81631231e-01 -1.03377640e+00 1.67636991e-01 -2.20455790e+00 1.01684294e-04 8.51572081e-02 -4.95667368e-01 5.43986499e-01 5.27503908e-01 -4.69328612e-01 2.66359150e-01 -1.42223865e-01 -7.60010421e-01 2.50898935e-02 1.28217268e+00 2.27589846e-01 -4.00705755e-01 -3.29559952e-01 -4.34401751e-01 7.05573320e-01 9.79819775e-01 -3.00020009e-01 -9.92255270e-01 -1.96857378e-01 1.46824419e-01 8.04339796e-02 4.21899468e-01 -1.47731590e+00 4.05077517e-01 -4.74074066e-01 4.82625753e-01 -6.04361832e-01 3.08289021e-01 -1.60661030e+00 6.07651055e-01 8.97670686e-01 -3.10234606e-01 2.92348206e-01 -1.59989502e-02 3.66103679e-01 -3.73645335e-01 -6.48364365e-01 2.42411032e-01 -4.42079842e-01 -1.38696253e+00 -6.97871745e-01 -8.04705739e-01 -6.78162158e-01 1.64621353e+00 -5.73541045e-01 -5.33968434e-02 -1.00223899e-01 -1.25247371e+00 9.42997858e-02 4.27280933e-01 5.41014910e-01 6.41774595e-01 -1.03722811e+00 2.78726608e-01 5.47900259e-01 3.05675473e-02 -1.66936874e-01 2.56260902e-01 2.30408370e-01 -1.06753528e+00 9.08018708e-01 -1.06072176e+00 -2.08080798e-01 -1.00317538e+00 1.07692873e+00 -7.11184666e-02 1.25474306e-02 -5.30194402e-01 -7.16013275e-03 -3.11697602e-01 -1.50027648e-01 -1.79063559e-01 -5.77215254e-01 -7.32871771e-01 -3.32061321e-01 6.31139040e-01 4.77285922e-01 1.53701320e-01 -4.63651478e-01 -5.60759783e-01 4.36798930e-01 5.14565706e-01 -2.26571620e-01 1.09205627e+00 -4.53630358e-01 -5.05130649e-01 8.76752079e-01 6.13037050e-01 -3.42657804e-01 -5.25728762e-01 1.22853562e-01 5.95145404e-01 -3.03607911e-01 -2.12351024e-01 -1.13504684e+00 -4.95785654e-01 5.52014947e-01 5.80162346e-01 5.48714876e-01 1.22635174e+00 1.70052826e-01 4.68254864e-01 9.59569216e-01 1.10665464e+00 -1.65935194e+00 -1.00904610e-02 6.51967049e-01 6.05827987e-01 -5.60643554e-01 -6.40586019e-02 -7.04897404e-01 -7.09836602e-01 1.44049037e+00 3.58593345e-01 1.24315768e-02 7.11193144e-01 3.43827248e-01 6.99404180e-02 -6.97487414e-01 -5.74122071e-01 -2.92877287e-01 -2.19546214e-01 1.05693114e+00 8.86821747e-03 2.90418804e-01 -5.86033523e-01 5.28240919e-01 -3.15745354e-01 7.09717333e-01 4.24533725e-01 1.50300348e+00 -1.15483689e+00 -1.23562932e+00 -5.21832585e-01 -6.88713342e-02 -1.14566118e-01 5.29980540e-01 -6.81032181e-01 6.72481179e-01 2.13646695e-01 1.30744839e+00 1.14516720e-01 -3.17973077e-01 8.04656804e-01 6.00444138e-01 6.80742562e-01 -7.26987243e-01 -1.76865369e-01 -6.77897334e-01 4.39475775e-01 -9.82331753e-01 -6.83359444e-01 -3.27970058e-01 -2.31307769e+00 -4.86828387e-02 4.09411669e-01 4.44233447e-01 1.06710076e+00 1.33901787e+00 3.96537244e-01 9.31773543e-01 1.10073149e-01 -4.96298641e-01 -1.94695607e-01 -7.88881600e-01 -5.31032920e-01 6.53995335e-01 -2.33080447e-01 -8.99792075e-01 1.12495661e-01 5.57911038e-01]	[4.450706958770752, 1.186515212059021]
a4f7ae79-5073-4063-a88b-8f39a7b7cfba	attacking-cooperative-multi-agent	2302.03322	null	https://arxiv.org/abs/2302.03322v2	https://arxiv.org/pdf/2302.03322v2.pdf	Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence	This study probes the vulnerabilities of cooperative multi-agent reinforcement learning (c-MARL) under adversarial attacks, a critical determinant of c-MARL's worst-case performance prior to real-world implementation. Current observation-based attacks, constrained by white-box assumptions, overlook c-MARL's complex multi-agent interactions and cooperative objectives, resulting in impractical and limited attack capabilities. To address these shortcomes, we propose Adversarial Minority Influence (AMI), a practical and strong for c-MARL. AMI is a practical black-box attack and can be launched without knowing victim parameters. AMI is also strong by considering the complex multi-agent interaction and the cooperative goal of agents, enabling a single adversarial agent to unilaterally misleads majority victims to form targeted worst-case cooperation. This mirrors minority influence phenomena in social psychology. To achieve maximum deviation in victim policies under complex agent-wise interactions, our unilateral attack aims to characterize and maximize the impact of the adversary on the victims. This is achieved by adapting a unilateral agent-wise relation metric derived from mutual information, thereby mitigating the adverse effects of victim influence on the adversary. To lead the victims into a jointly detrimental scenario, our targeted attack deceives victims into a long-term, cooperatively harmful situation by guiding each victim towards a specific target, determined through a trial-and-error process executed by a reinforcement learning agent. Through AMI, we achieve the first successful attack against real-world robot swarms and effectively fool agents in simulated environments into collectively worst-case scenarios, including Starcraft II and Multi-agent Mujoco. The source code and demonstrations can be found at: https://github.com/DIG-Beihang/AMI.	['Xianglong Liu', 'Wenjun Wu', 'Aishan Liu', 'Xin Yu', 'Pu Feng', 'Jingqiao Xiu', 'Jun Guo', 'Simin Li']	2023-02-07	null	null	null	null	['starcraft-ii', 'continuous-control', 'smac-1', 'starcraft', 'smac']	['playing-games', 'playing-games', 'playing-games', 'playing-games', 'playing-games']	[-2.07031503e-01 3.84017110e-01 2.77908623e-01 3.38412136e-01 -2.75647134e-01 -8.49183321e-01 5.74939609e-01 -4.81604040e-02 -6.10500216e-01 9.08463180e-01 -3.18605244e-01 -2.89945066e-01 -5.26229441e-01 -7.50806928e-01 -5.69673359e-01 -9.77166057e-01 -8.80817831e-01 4.71143126e-01 2.36977860e-02 -6.28312528e-01 3.53252850e-02 5.89371383e-01 -1.13571656e+00 -3.69967729e-01 7.24142432e-01 2.18698040e-01 -8.74793082e-02 1.00149226e+00 7.45551705e-01 1.12829399e+00 -1.34899974e+00 -3.77012968e-01 4.15415794e-01 -5.72545290e-01 -3.44107330e-01 -1.90742329e-01 -4.02501345e-01 -5.99721193e-01 -2.86464363e-01 1.01220536e+00 7.83458292e-01 -5.14970347e-02 6.16044104e-01 -1.94819677e+00 -1.82299763e-01 9.27076399e-01 -5.84773958e-01 -6.32075071e-02 5.47321558e-01 5.95966578e-01 6.82274818e-01 4.82962392e-02 2.38632336e-01 1.56012917e+00 5.00116229e-01 8.86640072e-01 -1.03293359e+00 -8.51821899e-01 8.66861939e-02 -1.67644516e-01 -1.05886912e+00 -1.22752592e-01 6.84753478e-01 -1.13962069e-01 6.80864036e-01 4.08738017e-01 5.88550806e-01 1.29273486e+00 4.50475305e-01 5.27553856e-01 1.10075712e+00 2.23767068e-02 5.13818979e-01 -1.22851968e-01 -4.69035417e-01 5.48105478e-01 5.99501193e-01 8.36438835e-01 -1.58324420e-01 -9.07723725e-01 5.44178665e-01 -2.94918031e-01 -2.99995810e-01 -1.81056425e-01 -1.01347244e+00 8.56188655e-01 5.36576092e-01 3.94710712e-03 -5.75149298e-01 3.11189234e-01 1.96613863e-01 8.11804295e-01 -1.15413055e-01 9.65130925e-01 -3.32710862e-01 -1.91120401e-01 -5.51181957e-02 4.44627792e-01 1.22342765e+00 4.12521273e-01 5.04612207e-01 3.53845984e-01 4.02836651e-01 2.09653601e-01 4.01852190e-01 8.22797477e-01 2.98133632e-03 -1.23776400e+00 5.76621965e-02 4.34659481e-01 3.62154812e-01 -1.15409827e+00 -7.43435442e-01 -5.24037182e-01 -4.19145197e-01 1.10052454e+00 3.62719506e-01 -1.06008649e+00 -1.15239039e-01 2.07727790e+00 7.86867023e-01 1.30492710e-02 6.53977811e-01 1.01096821e+00 2.85710186e-01 3.68660659e-01 2.14353111e-02 -3.53802323e-01 1.06417215e+00 -4.74413723e-01 -2.90684372e-01 -2.82274395e-01 8.21146071e-01 -3.89070719e-01 5.71026444e-01 3.02372277e-01 -9.78682280e-01 2.51122952e-01 -1.16960216e+00 1.07492614e+00 -1.44615620e-01 -6.28129125e-01 4.68020618e-01 7.92442977e-01 -7.50337362e-01 3.75375450e-01 -8.62273633e-01 -3.31405759e-01 3.29306126e-01 7.18660295e-01 -2.63022184e-01 3.65320683e-01 -1.20636714e+00 1.06662798e+00 -5.93767827e-03 -5.47112450e-02 -1.63069594e+00 -6.28366530e-01 -5.45159817e-01 -1.71740219e-01 9.38988745e-01 -6.71334386e-01 8.38423312e-01 -9.18269336e-01 -1.65541649e+00 3.11394423e-01 8.23584974e-01 -6.27472341e-01 6.57819629e-01 -2.11061865e-01 -3.35933939e-02 2.77118981e-01 -3.21848877e-02 3.79649997e-01 8.03908348e-01 -1.80728590e+00 -3.50905418e-01 -2.01422498e-01 8.38546813e-01 7.44557679e-01 -2.98625916e-01 1.54213741e-01 6.75426126e-01 -4.74781960e-01 -8.27394187e-01 -1.22782123e+00 -5.86020231e-01 -4.85302806e-01 -3.82111311e-01 1.15891881e-01 9.47779834e-01 4.75526527e-02 5.78263462e-01 -2.02810931e+00 3.99269432e-01 1.42066954e-02 4.78296608e-01 3.74041736e-01 -5.29185176e-01 1.07620156e+00 3.17166984e-01 1.36860579e-01 -8.07660818e-02 -2.23924935e-01 2.51368999e-01 1.79954872e-01 -3.17108512e-01 7.44250476e-01 -3.33898421e-03 6.25952005e-01 -1.21772599e+00 -3.81855574e-03 -2.60798298e-02 1.76803485e-01 -7.35727608e-01 7.94434786e-01 -1.28345907e-01 6.47705317e-01 -6.96924090e-01 5.75914860e-01 5.53344309e-01 3.75783831e-01 3.54657650e-01 4.55190271e-01 -2.95744240e-02 -2.79480696e-01 -8.85728955e-01 6.39648199e-01 -2.84243912e-01 2.03767940e-01 8.00835311e-01 -6.97915733e-01 7.36470461e-01 1.85179248e-01 6.07820451e-01 -2.54409403e-01 6.10357523e-01 1.44089967e-01 6.31403625e-01 -2.46500656e-01 2.78944165e-01 2.37766337e-02 -4.60631251e-01 9.79285419e-01 -2.46104434e-01 -4.52167809e-01 3.32958736e-02 4.77322221e-01 1.63541198e+00 -2.62546003e-01 3.55299562e-01 -2.55620688e-01 2.34638169e-01 1.17941245e-01 6.74620628e-01 1.28447175e+00 -6.31528199e-01 -9.83112156e-02 9.03539002e-01 -2.04004705e-01 -4.79881078e-01 -1.10474348e+00 6.04704618e-01 1.19230330e+00 6.60405576e-01 -1.68698922e-01 -8.98101270e-01 -9.37586367e-01 1.72772497e-01 9.22420740e-01 -8.16736281e-01 -6.64404511e-01 -6.49840653e-01 -8.68270099e-01 1.12151349e+00 -2.55748779e-01 4.24925834e-01 -1.32002628e+00 -1.22579706e+00 1.29053652e-01 2.55280674e-01 -7.49191046e-01 -2.45188981e-01 2.28185147e-01 -3.16232294e-02 -1.54397690e+00 -1.67545632e-01 -1.54797688e-01 6.70975506e-01 2.79538602e-01 8.12648356e-01 5.72152376e-01 -2.12690815e-01 7.93952107e-01 -6.00076973e-01 -5.76405406e-01 -9.45179164e-01 -2.74528682e-01 6.22767568e-01 -2.73675829e-01 -6.44406006e-02 -7.59650350e-01 -5.83056629e-01 6.13278508e-01 -9.05327380e-01 -5.69902301e-01 6.27327561e-01 8.36018205e-01 -5.12898803e-01 2.24324331e-01 8.90985847e-01 -3.75335008e-01 1.10903955e+00 -7.38070488e-01 -7.82250464e-01 1.09468184e-01 -1.00914322e-01 -3.50350261e-01 9.80395257e-01 -9.56776917e-01 -6.20913386e-01 -4.32826579e-01 2.92853683e-01 -3.49824309e-01 -2.33759180e-01 2.40681380e-01 -2.39254132e-01 -4.77599502e-01 7.86150336e-01 3.79905314e-03 3.03617001e-01 1.98354885e-01 1.72875315e-01 4.47765648e-01 4.56764959e-02 -7.71285176e-01 1.21767747e+00 3.44153136e-01 1.65180549e-01 -8.32943738e-01 -2.61732668e-01 3.68370146e-01 -1.13975868e-01 -5.85014582e-01 5.58895051e-01 -6.58644974e-01 -1.43727791e+00 8.54943693e-01 -9.91077185e-01 -7.17835307e-01 -1.04409017e-01 4.30558175e-01 -4.27074045e-01 1.44966736e-01 -3.99767190e-01 -9.88016188e-01 -1.34026334e-01 -1.16557634e+00 4.49534684e-01 3.56897742e-01 -1.62947312e-01 -1.03740621e+00 3.11914980e-01 2.68767715e-01 5.76413035e-01 4.58867550e-01 5.20518720e-01 -1.10338068e+00 -3.41383755e-01 -1.06485233e-01 4.09580320e-01 3.42547637e-03 6.81244507e-02 -4.57035750e-02 -4.74368960e-01 -8.55053723e-01 2.99628139e-01 -7.25075424e-01 -2.46282481e-02 -9.27708391e-03 -8.89164209e-03 -7.11498797e-01 -2.39408329e-01 3.23342532e-01 8.98039341e-01 3.85836363e-01 2.04521224e-01 5.00413716e-01 4.32052493e-01 8.48152161e-01 8.02568078e-01 8.28248918e-01 4.93234366e-01 3.45441490e-01 1.21625435e+00 2.31090728e-02 3.06256056e-01 -1.85497046e-01 8.54297876e-01 2.74013907e-01 5.34908623e-02 -5.16375721e-01 -6.19721711e-01 1.66566059e-01 -1.74110985e+00 -9.75620210e-01 1.97840586e-01 2.21892834e+00 5.46309710e-01 1.64978713e-01 5.14358580e-01 -2.72901475e-01 6.48182154e-01 7.86245018e-02 -6.20999217e-01 -4.37463582e-01 -9.99012664e-02 -6.12586915e-01 7.59432137e-01 7.16643631e-01 -8.74059558e-01 8.97871912e-01 5.71352530e+00 7.22884774e-01 -9.14186001e-01 8.35170671e-02 2.48139843e-01 -5.02756357e-01 1.42162908e-02 2.00563043e-01 -5.13300717e-01 2.03004584e-01 7.84135282e-01 -5.01957357e-01 9.45584297e-01 5.59938669e-01 4.38970357e-01 -1.97769672e-01 -8.22426021e-01 2.28572294e-01 -3.07064056e-02 -6.47034407e-01 -3.39754879e-01 4.72672701e-01 5.77542543e-01 1.07284024e-01 1.58346236e-01 4.26455438e-01 1.28589880e+00 -9.21065629e-01 5.40692031e-01 2.79654898e-02 1.41446248e-01 -1.01627302e+00 6.59047544e-01 6.84110403e-01 -8.03024054e-01 -5.86586952e-01 -2.25392833e-01 -4.98767525e-01 8.31523016e-02 2.64998269e-03 -7.93154001e-01 4.30165440e-01 4.40518320e-01 4.77504469e-02 -1.32062882e-01 5.63189149e-01 -3.93604100e-01 5.55651784e-01 -4.17517811e-01 -3.90625268e-01 4.61794376e-01 -2.39197642e-01 1.32558763e+00 5.51453054e-01 -3.12838219e-02 2.90534765e-01 5.45851290e-01 7.78544962e-01 1.81197524e-01 -3.33824992e-01 -8.72162402e-01 1.00303825e-03 7.97937036e-01 1.36385942e+00 -4.36217844e-01 6.07071929e-02 1.91383228e-01 6.82843089e-01 4.06400383e-01 4.13513988e-01 -1.14141631e+00 -4.58276540e-01 1.04868948e+00 -4.77076977e-01 -1.40431851e-01 -1.68678075e-01 4.88723963e-02 -7.41073191e-01 -3.84540290e-01 -1.49282670e+00 2.52367496e-01 -2.12581500e-01 -1.39291370e+00 7.86601663e-01 -5.16259298e-02 -1.26422393e+00 -2.89030850e-01 -1.98203698e-01 -1.05406201e+00 2.57142991e-01 -1.03466487e+00 -1.24529076e+00 1.28531262e-01 5.88950574e-01 -1.77489053e-02 -5.49571276e-01 6.95905805e-01 -2.21388921e-01 -7.88274288e-01 7.04113364e-01 -1.69380605e-01 -1.45714924e-01 6.19404197e-01 -1.13967884e+00 -2.19696257e-02 8.63625228e-01 -3.98422211e-01 5.51538527e-01 1.17889476e+00 -9.57927883e-01 -1.75158179e+00 -8.60426664e-01 -1.36226192e-01 -3.95190716e-01 1.13843644e+00 -3.97288263e-01 -4.40720111e-01 3.80136967e-01 3.48529160e-01 -2.87030250e-01 4.38901901e-01 -1.80755526e-01 -1.58576056e-01 1.16654396e-01 -1.43365908e+00 1.26220703e+00 8.73209357e-01 -2.08338186e-01 -3.54688853e-01 3.00801337e-01 8.04230750e-01 -7.27185756e-02 -7.08148420e-01 4.41305429e-01 3.17939878e-01 -9.68659282e-01 7.52946734e-01 -6.13189757e-01 5.11939898e-02 -3.50395381e-01 -3.15895155e-02 -1.84131622e+00 4.88348585e-03 -1.33509362e+00 1.82601675e-01 8.88182402e-01 6.55043274e-02 -1.14153349e+00 5.77346504e-01 2.99931824e-01 9.12932903e-02 -5.29155433e-01 -9.98145103e-01 -9.35276568e-01 4.22622174e-01 7.44326040e-02 4.01139826e-01 9.20059741e-01 3.86493683e-01 -8.49035606e-02 -7.23830163e-01 8.48879755e-01 1.03653264e+00 -3.66139144e-01 1.25598967e+00 -5.91411412e-01 -6.65295303e-01 -4.35977817e-01 -2.22768322e-01 -4.85007226e-01 3.12253922e-01 -3.28925788e-01 1.65580496e-01 -6.88308537e-01 -1.28315881e-01 -7.26644397e-01 7.05193952e-02 4.75944251e-01 -1.63364947e-01 1.22329205e-01 6.67263210e-01 2.11666450e-01 -7.44397163e-01 7.29987085e-01 1.11672246e+00 -4.77990359e-02 -2.98073918e-01 5.14428094e-02 -7.17671812e-01 8.70209336e-01 9.62297499e-01 -7.63126791e-01 -5.04973531e-01 -1.16608171e-02 7.68941790e-02 4.54436839e-01 4.05113816e-01 -1.05840468e+00 4.06844318e-01 -6.18099988e-01 -2.98043221e-01 3.05795491e-01 4.53879118e-01 -8.44896853e-01 1.50122657e-01 1.10368741e+00 -2.13219836e-01 1.59380019e-01 1.00838840e-01 5.21758974e-01 2.61909008e-01 -2.31193408e-01 7.09262013e-01 -5.29668964e-02 7.23389238e-02 3.66459601e-02 -8.97293448e-01 1.34847954e-01 1.66644120e+00 2.81186074e-01 -1.00828183e+00 -6.90042377e-01 -3.27652067e-01 7.63338983e-01 8.04184616e-01 2.48214513e-01 5.30572593e-01 -6.80555880e-01 -1.08549190e+00 9.10156220e-03 -3.25123072e-01 -5.80711484e-01 2.38776565e-01 8.34370255e-01 -4.44408536e-01 -3.89646620e-01 -4.77780461e-01 -5.09273335e-02 -1.53602874e+00 6.22112632e-01 7.74568796e-01 -2.64794946e-01 -1.60329103e-01 6.65903568e-01 4.99869287e-01 -6.50598288e-01 1.12070084e-01 6.21804953e-01 -2.44634837e-01 -2.78873116e-01 5.00347435e-01 4.74350959e-01 -6.01754427e-01 -5.81798017e-01 -4.90722060e-01 1.23158611e-01 4.41229902e-02 -1.29850045e-01 1.20972991e+00 -1.52410448e-01 -2.25235134e-01 -1.65585652e-01 6.64937198e-01 3.89195412e-01 -1.40397358e+00 3.05472523e-01 -3.95606220e-01 -2.89802015e-01 -2.59788722e-01 -8.79481196e-01 -8.21699798e-01 1.64755613e-01 1.57094240e-01 6.51045084e-01 9.18187141e-01 -1.32001892e-01 4.17280287e-01 6.49507642e-01 6.37742043e-01 -7.50903070e-01 4.32272255e-01 5.38822234e-01 9.74129915e-01 -1.08302414e+00 2.25808937e-02 -1.52605519e-01 -8.30010116e-01 6.18162692e-01 1.02064359e+00 -5.37106812e-01 3.69078219e-01 6.96390390e-01 4.93015409e-01 -2.67748386e-01 -1.13181984e+00 -3.50160478e-03 -5.14031112e-01 9.89209294e-01 -4.93584096e-01 2.95455247e-01 -8.21387693e-02 3.43430549e-01 -2.47559100e-01 -7.82938659e-01 1.16351199e+00 1.02052891e+00 -5.41427493e-01 -1.08810425e+00 -8.81403685e-01 3.60924415e-02 -4.91442531e-01 3.18512559e-01 -7.99551070e-01 9.14063156e-01 -7.87330642e-02 1.54044986e+00 -2.81969488e-01 -5.69219589e-01 8.57455358e-02 -8.08257818e-01 1.16530903e-01 -2.04772606e-01 -1.06841111e+00 -2.23411262e-01 2.34054610e-01 -6.09389901e-01 -2.94263959e-01 -5.68243921e-01 -1.18496132e+00 -7.48967171e-01 -2.19728470e-01 5.54829836e-01 2.75590152e-01 8.91540706e-01 2.85164952e-01 4.72857833e-01 1.25830925e+00 -1.08722413e+00 -1.06143308e+00 -9.00377989e-01 -3.83474082e-01 2.15441048e-01 4.14750338e-01 -8.65398467e-01 -1.09408128e+00 -7.58340955e-01]	[3.8726890087127686, 2.3897526264190674]
f13126b5-1145-4775-b1b0-e763b27dc643	towards-real-time-and-light-weight-line	2106.00186	null	https://arxiv.org/abs/2106.00186v3	https://arxiv.org/pdf/2106.00186v3.pdf	Towards Light-weight and Real-time Line Segment Detection	Previous deep learning-based line segment detection (LSD) suffers from the immense model size and high computational cost for line prediction. This constrains them from real-time inference on computationally restricted environments. In this paper, we propose a real-time and light-weight line segment detector for resource-constrained environments named Mobile LSD (M-LSD). We design an extremely efficient LSD architecture by minimizing the backbone network and removing the typical multi-module process for line prediction found in previous methods. To maintain competitive performance with a light-weight network, we present novel training schemes: Segments of Line segment (SoL) augmentation, matching and geometric loss. SoL augmentation splits a line segment into multiple subparts, which are used to provide auxiliary line data during the training process. Moreover, the matching and geometric loss allow a model to capture additional geometric cues. Compared with TP-LSD-Lite, previously the best real-time LSD method, our model (M-LSD-tiny) achieves competitive performance with 2.5% of model size and an increase of 130.5% in inference speed on GPU. Furthermore, our model runs at 56.8 FPS and 48.6 FPS on the latest Android and iPhone mobile devices, respectively. To the best of our knowledge, this is the first real-time deep LSD available on mobile devices. Our code is available.	['Minchul Shin', 'Jingeun Lee', 'Sung-Hyun Lee', 'SeoungHyun Go', 'Byungsoo Ko', 'Geonmo Gu']	2021-06-01	null	null	null	null	['line-segment-detection']	['computer-vision']	[ 5.56640513e-03 -3.09367292e-02 -3.72102290e-01 -2.18249202e-01 -6.79557145e-01 -2.13637918e-01 5.77324592e-02 1.50527850e-01 -5.73137879e-01 4.49473321e-01 -5.12537301e-01 -6.84153676e-01 3.66591543e-01 -9.63586271e-01 -9.77066278e-01 -1.67287484e-01 -6.98365793e-02 2.78627127e-01 7.22952008e-01 -4.46051732e-02 1.01897851e-01 8.78483593e-01 -1.13220465e+00 1.88423902e-01 1.09844613e+00 1.35543299e+00 2.71565586e-01 6.81145847e-01 -1.18045628e-01 4.83828872e-01 -2.65764475e-01 -4.02065307e-01 4.25541222e-01 1.91142093e-02 -3.49651366e-01 -1.94010721e-03 8.90762508e-01 -7.55149186e-01 -6.58650160e-01 5.73885381e-01 9.01203096e-01 2.32201014e-02 1.71908408e-01 -1.34182262e+00 7.29088634e-02 4.85212654e-01 -9.41183627e-01 -9.35460925e-02 2.89741438e-03 -1.87243503e-02 5.98048210e-01 -1.09947479e+00 3.91330570e-01 8.07401121e-01 1.32738352e+00 2.55136400e-01 -9.35563862e-01 -5.71375012e-01 -3.22684683e-02 6.75547644e-02 -1.61763418e+00 -3.96542877e-01 8.50165725e-01 -1.62756413e-01 1.01994491e+00 9.69052464e-02 8.37746382e-01 8.02685618e-01 9.11966413e-02 1.21527624e+00 6.03388846e-01 -4.41123098e-01 7.05856234e-02 -3.83092910e-02 -1.13864332e-01 1.09600186e+00 2.12549791e-01 -2.84585953e-01 -5.10877430e-01 2.10498333e-01 1.17325938e+00 -1.37476936e-01 -2.14214683e-01 -4.92925525e-01 -8.96053612e-01 4.87020582e-01 5.73970437e-01 -1.50133669e-01 -9.27976966e-02 2.84071624e-01 4.44073528e-01 -1.57263964e-01 4.89856482e-01 -9.44461022e-03 -5.96020460e-01 -4.14259642e-01 -1.51690495e+00 1.51360303e-01 6.98065460e-01 1.19212174e+00 7.00772345e-01 7.61090517e-02 -1.64621383e-01 8.63915801e-01 3.06674659e-01 6.45851731e-01 2.23307848e-01 -7.76837111e-01 9.09104288e-01 5.05298972e-01 -8.14336091e-02 -1.13024855e+00 -8.38683903e-01 -1.10156178e+00 -7.85542011e-01 3.00874785e-02 4.54483539e-01 -4.54963714e-01 -5.15752077e-01 1.22077811e+00 3.66832912e-01 4.72806871e-01 -4.12491828e-01 6.16338670e-01 6.14942729e-01 6.20867431e-01 -3.08261245e-01 1.37030616e-01 1.14512384e+00 -1.61434078e+00 -3.30691367e-01 -4.63580579e-01 1.11921990e+00 -9.29329932e-01 1.20704448e+00 5.25040329e-01 -1.25620604e+00 -6.72611952e-01 -1.35809362e+00 -4.96562392e-01 4.29722704e-02 6.02015853e-01 9.27094817e-01 6.30424678e-01 -8.15444529e-01 5.07564723e-01 -1.09093797e+00 -7.51654506e-02 7.66969502e-01 6.54908419e-01 7.36970752e-02 -7.33534619e-02 -7.73570657e-01 3.31029922e-01 1.28288016e-01 3.31907868e-01 -8.34447891e-02 -9.69542384e-01 -8.58958066e-01 2.15888783e-01 6.77469134e-01 -6.51336372e-01 1.33771098e+00 -5.15324891e-01 -1.57873106e+00 6.58809185e-01 -3.03434342e-01 -8.08406532e-01 9.35746133e-01 -6.58618093e-01 -3.69694978e-01 1.85570389e-01 -6.66388795e-02 8.12976241e-01 5.31485140e-01 -9.56779659e-01 -7.64978290e-01 -1.88636124e-01 -2.55446322e-02 9.09227207e-02 -3.48164469e-01 -4.00349140e-01 -1.18110049e+00 -7.17347264e-01 1.44721255e-01 -1.07465172e+00 -2.91806519e-01 5.57283938e-01 -5.86928129e-01 4.96503301e-02 1.08074880e+00 -4.38066512e-01 1.60377550e+00 -2.05054569e+00 -7.56887555e-01 1.97884306e-01 4.42763418e-02 6.64274514e-01 1.69228256e-01 2.83986568e-01 3.47496778e-01 -1.41029686e-01 -1.81710973e-01 -8.67350996e-01 -9.38862041e-02 -4.37229499e-02 -2.28836283e-01 4.45002377e-01 -2.28014886e-02 9.08566177e-01 -5.30692995e-01 -7.56070852e-01 3.79151434e-01 6.78811848e-01 -9.02918696e-01 -2.04206899e-01 -1.14572430e-02 -6.65807948e-02 -2.48614475e-01 6.54453099e-01 1.03712916e+00 -1.28570050e-01 -1.28455430e-01 -5.98585844e-01 -4.92173284e-01 1.92182094e-01 -1.15301323e+00 1.97964787e+00 -6.42357826e-01 8.42333436e-01 -3.02757025e-01 -4.55814183e-01 1.13612914e+00 -2.25251317e-01 5.87774754e-01 -9.01616156e-01 1.54282048e-01 3.51385266e-01 -2.10033476e-01 -2.38945559e-01 8.02206993e-01 6.43938661e-01 3.16909179e-02 1.26988858e-01 -2.76433855e-01 -1.41787231e-01 2.40482464e-01 1.79548115e-01 8.40290785e-01 5.25722921e-01 -3.87523659e-02 -4.34771478e-02 4.24986541e-01 -1.99201077e-01 7.00179517e-01 8.14167857e-01 -1.36238888e-01 5.93766809e-01 3.30509484e-01 -3.81944329e-01 -1.12089610e+00 -1.02687311e+00 -2.25245714e-01 7.50996947e-01 3.68038863e-01 -6.58879757e-01 -8.33649397e-01 -4.52844352e-01 -1.27913713e-01 5.14076233e-01 1.66369546e-02 8.76574963e-02 -9.98368382e-01 -5.47380447e-01 7.96081007e-01 9.07697856e-01 1.06942618e+00 -6.21672392e-01 -4.86352116e-01 3.82190377e-01 1.77639857e-01 -1.45946896e+00 -7.18658209e-01 3.18437293e-02 -1.02801728e+00 -7.35782623e-01 -5.02344310e-01 -9.41720545e-01 6.12645566e-01 3.66664708e-01 9.14791524e-01 4.52840850e-02 -3.31861585e-01 -1.79805428e-01 3.84790637e-02 -3.88213128e-01 3.65231186e-01 4.16336089e-01 -2.03321144e-01 -2.15187237e-01 1.33302316e-01 -3.28548998e-01 -9.23622429e-01 2.51254857e-01 -4.54104185e-01 6.40798688e-01 5.53244293e-01 5.48072278e-01 9.69860792e-01 -3.90820019e-02 2.22832933e-02 -8.38362873e-01 2.20271632e-01 -1.36471108e-01 -8.37639689e-01 -3.18970159e-02 -5.19267917e-01 -2.71021277e-01 7.51219809e-01 -1.55087262e-01 -1.02165842e+00 3.41133237e-01 -5.33202231e-01 -2.49902517e-01 1.22824430e-01 3.57106805e-01 -3.04175187e-02 -3.07539761e-01 4.34701800e-01 -3.04344017e-02 -4.15608197e-01 -5.03423452e-01 2.25168511e-01 5.91812015e-01 7.69725859e-01 -4.23595756e-01 6.62859261e-01 6.37288749e-01 2.57285744e-01 -9.48167443e-01 -9.20895696e-01 -4.48851079e-01 -7.46811271e-01 -1.71840280e-01 4.14335936e-01 -9.82061684e-01 -8.23276222e-01 9.19234395e-01 -9.60107028e-01 -8.17333400e-01 -1.76865339e-01 3.89822453e-01 -5.62518120e-01 5.41098297e-01 -7.56133318e-01 -6.61162257e-01 -5.09892881e-01 -1.08128691e+00 1.12744844e+00 3.51605356e-01 7.42697194e-02 -9.32800293e-01 -2.38314286e-01 3.09047610e-01 1.81710333e-01 2.13387802e-01 3.09953600e-01 -1.90931469e-01 -5.73071718e-01 -3.33777815e-01 -5.70547521e-01 1.75694987e-01 -1.71596676e-01 2.45165482e-01 -8.33319485e-01 -1.87179178e-01 -4.04773712e-01 -1.22167699e-01 7.34694183e-01 4.53588575e-01 1.67592537e+00 -2.92742960e-02 -6.28478825e-01 1.24270666e+00 1.58379447e+00 2.50358254e-01 6.33865118e-01 5.67038774e-01 1.12086868e+00 1.02619149e-01 7.18708694e-01 6.77907407e-01 6.86637521e-01 9.51425552e-01 2.56824076e-01 -6.79491341e-01 -3.07949781e-01 -5.33702135e-01 1.33032620e-01 8.18321943e-01 1.89621836e-01 -6.88083649e-01 -9.74613786e-01 1.10922150e-01 -1.96388519e+00 -8.51520896e-01 -6.57335758e-01 2.19605350e+00 6.88411713e-01 7.64222264e-01 1.76226035e-01 3.26451123e-01 4.66813892e-01 6.21230640e-02 -6.27900422e-01 -4.90942538e-01 -2.01946229e-01 2.56067902e-01 9.73015785e-01 4.77685660e-01 -1.41600049e+00 1.06422579e+00 5.03073645e+00 1.25177073e+00 -1.26705408e+00 -1.60514846e-01 5.97311854e-01 -5.50425947e-02 -2.12279428e-02 -1.15222849e-01 -1.23860991e+00 4.32524651e-01 6.86827838e-01 2.30556622e-01 -1.28204701e-02 1.07339311e+00 5.67028999e-01 -2.21870854e-01 -8.36447775e-01 1.21013081e+00 -6.90600835e-03 -1.46293235e+00 -2.89270252e-01 2.35440675e-02 6.36008859e-01 2.72377133e-01 -4.58670743e-02 2.86597222e-01 -3.28620732e-01 -5.56192398e-01 7.56321073e-01 5.06177843e-01 8.79369497e-01 -1.08150899e+00 5.55092335e-01 3.50544155e-01 -1.34889698e+00 1.71976060e-01 -1.66354418e-01 3.60118523e-02 4.24509108e-01 7.74155974e-01 -8.83975029e-01 3.64355445e-01 4.14518118e-01 6.76266551e-01 -7.05602407e-01 1.47747052e+00 -3.80378403e-02 8.38054657e-01 -7.50313103e-01 2.82504469e-01 4.87444103e-01 -3.99161614e-02 8.13730359e-02 1.43367255e+00 4.01351780e-01 -4.53726947e-01 4.34843153e-01 4.23026323e-01 -1.45565361e-01 1.16057679e-01 -2.00128451e-01 4.73215729e-01 6.28920615e-01 1.13158786e+00 -1.03155208e+00 -2.19139352e-01 -6.77284300e-01 1.17854190e+00 3.75766724e-01 1.42678721e-02 -1.18573427e+00 -7.23404109e-01 2.87404805e-01 3.76123160e-01 4.09110844e-01 -7.45994568e-01 -5.62710106e-01 -1.01951945e+00 1.84744611e-01 -3.09073299e-01 -8.05688798e-02 -4.89332855e-01 -7.19760180e-01 5.27621150e-01 -3.35231811e-01 -1.41060495e+00 3.88685279e-02 -5.36025643e-01 -5.85715711e-01 4.24154967e-01 -1.74555147e+00 -1.33623922e+00 -5.64997435e-01 5.10638416e-01 7.31196582e-01 1.08079754e-01 3.94314826e-01 6.94452405e-01 -8.97529781e-01 1.21747553e+00 3.53712618e-01 2.56816685e-01 6.49648309e-01 -1.07278407e+00 9.42039192e-01 8.29401135e-01 -4.34605069e-02 4.21928912e-01 3.24085385e-01 -6.37553155e-01 -1.20840728e+00 -1.13228250e+00 7.93578744e-01 2.13530689e-01 4.73970056e-01 -5.57063997e-01 -7.57482648e-01 5.62283576e-01 -3.30470741e-01 1.92161694e-01 6.60870790e-01 -2.09205374e-01 -5.73700406e-02 -3.34178686e-01 -9.53206122e-01 9.73712385e-01 1.30071950e+00 -2.13670149e-01 1.70360193e-01 3.59621674e-01 6.91541255e-01 -8.38857591e-01 -6.93389118e-01 4.90605086e-01 7.32483566e-01 -1.17117679e+00 1.08708203e+00 2.26362109e-01 2.38084316e-01 -2.95183688e-01 2.36660391e-01 -6.94940150e-01 -1.48844160e-03 -7.18333066e-01 -4.52865571e-01 1.17427433e+00 2.83205211e-01 -3.93638879e-01 1.26908493e+00 3.69206280e-01 -7.61991680e-01 -1.40174305e+00 -6.13663495e-01 -7.53103912e-01 -3.58059794e-01 -9.05498266e-01 5.84423363e-01 5.72159231e-01 -3.78309697e-01 7.08668865e-03 -3.87546510e-01 1.82064489e-01 6.94366336e-01 1.34995744e-01 9.88050520e-01 -8.77867639e-01 -3.86200249e-01 -4.24829841e-01 -2.37838775e-01 -1.92229342e+00 -9.71630588e-02 -5.83070576e-01 -1.83755159e-01 -1.52763844e+00 -3.90220642e-01 -9.14973319e-01 1.55012444e-01 4.27163392e-01 1.42597616e-01 5.79573274e-01 3.42088342e-01 1.15061715e-01 -6.63261056e-01 5.21253765e-01 1.16721630e+00 9.10468996e-02 -4.63567108e-01 2.78963119e-01 -2.09945455e-01 1.15807950e+00 1.00526154e+00 -1.53513432e-01 -4.26190645e-01 -7.31348157e-01 3.18492562e-01 1.31237041e-02 1.92291617e-01 -1.46897459e+00 5.55945873e-01 2.63825327e-01 5.39014578e-01 -1.08298910e+00 5.49436927e-01 -6.64429486e-01 -3.50079566e-01 6.49510860e-01 -1.69282667e-02 -1.03369735e-01 4.90726054e-01 1.52126923e-01 -2.02495721e-03 -3.25180322e-01 6.22601092e-01 3.70366812e-01 -9.85088527e-01 7.70344675e-01 -1.66384727e-01 -2.13586569e-01 1.03924990e+00 -7.45034218e-01 -3.61692190e-01 -1.35806873e-01 -4.88822341e-01 3.47435832e-01 4.49802041e-01 2.58220851e-01 5.80058634e-01 -1.31283677e+00 -3.38718563e-01 2.18588278e-01 -1.61992565e-01 4.76050109e-01 4.66114849e-01 8.53982747e-01 -1.37999547e+00 5.45642376e-01 -1.50619922e-02 -4.02144879e-01 -1.12466156e+00 2.98054248e-01 2.54466146e-01 -2.88257837e-01 -7.56311774e-01 1.02964067e+00 -7.43082166e-02 -8.47943947e-02 3.43408316e-01 -3.75653446e-01 1.83861554e-01 -1.45362854e-01 2.83761650e-01 7.17700243e-01 2.17167914e-01 -4.36179936e-01 -3.27584535e-01 8.03750992e-01 -1.35105744e-01 1.99614018e-01 1.15594625e+00 -9.43519846e-02 3.39378566e-01 1.98034018e-01 1.30631125e+00 4.42342907e-01 -1.60133302e+00 -2.03289449e-01 -2.52141505e-01 -3.61625284e-01 3.02558780e-01 -4.76461291e-01 -1.07031083e+00 8.50175619e-01 5.34617007e-01 -3.21984559e-01 9.98783469e-01 -5.39419472e-01 1.54139388e+00 3.58816296e-01 5.62346756e-01 -1.22047305e+00 -1.22135356e-01 4.28596944e-01 5.20805120e-01 -1.13136435e+00 1.92822903e-01 -9.31761920e-01 -1.69856921e-01 1.28696060e+00 1.00667703e+00 -2.29507253e-01 5.05145669e-01 6.79329097e-01 -3.12421054e-01 1.35932833e-01 -2.47156382e-01 7.94171467e-02 2.43905380e-01 3.77562433e-01 4.48289663e-01 -1.33936509e-01 -1.99184567e-01 3.64491403e-01 -4.44759667e-01 1.57582879e-01 3.51724535e-01 9.32365775e-01 -3.90970349e-01 -1.04505658e+00 -1.43563554e-01 4.84572113e-01 -3.07979077e-01 -2.30955824e-01 9.93269384e-02 8.51846278e-01 3.21625412e-01 6.55031741e-01 4.62533534e-01 -2.46768564e-01 4.32537735e-01 -5.86076498e-01 4.20399308e-01 -3.11619550e-01 -4.24825937e-01 1.71960279e-01 9.89398137e-02 -8.57803464e-01 1.64460205e-02 -4.43202555e-01 -1.56838334e+00 -5.98825336e-01 -4.56138134e-01 -2.87376195e-01 8.55983853e-01 6.38080537e-01 5.46953917e-01 4.92969662e-01 5.45724273e-01 -1.01127839e+00 -5.26353717e-02 -4.93102044e-01 -4.16012317e-01 -1.69966713e-01 9.47705433e-02 -4.19350058e-01 1.21042319e-01 -2.18963161e-01]	[8.40140438079834, -1.546748399734497]
2ad1532f-69d9-45ec-a818-6ff13bcb0168	semattack-natural-textual-attacks-via	null	null	https://openreview.net/forum?id=03-jwvIDYf	https://openreview.net/pdf?id=03-jwvIDYf	SemAttack: Natural Textual Attacks via Different Semantic Spaces	Recent studies show that pre-trained language models (LMs) are vulnerable to textual adversarial attacks. However, existing attack methods either suffer from low attack success rates or fail to search efﬁciently in the exponentially large perturbation space. We propose an efﬁcient and effective framework SemAttack to generate natural adversarial text by constructing different semantic perturbation functions. In particular, SemAttack optimizes the generated perturbations constrained on generic semantic spaces, including typo space, knowledge space (e.g., WordNet), contextualized semantic space (e.g., the embedding space of BERT clusterings), or the combination of these spaces. Thus, the generated adversarial texts are more semantically close to the original inputs. Extensive experiments reveal that state-of-the-art (SOTA) large-scale LMs (e.g., DeBERTa-v2) and defense strategies (e.g., FreeLB) are still vulnerable to SemAttack. We further demonstrate that SemAttack is general and able to generate natural adversarial texts for different languages (e.g., English and Chinese) with high attack success rates. Human evaluations also conﬁrm that our generated adversarial texts are natural and barely affect human performance.	['Anonymous']	2022-01-16	null	null	null	acl-arr-january-2022-1	['adversarial-text']	['adversarial']	[-4.97835055e-02 -7.99620152e-02 1.54192045e-01 7.46994764e-02 -8.53207588e-01 -1.24728727e+00 7.80714869e-01 -2.13669553e-01 -4.73277777e-01 7.60276258e-01 2.06187069e-01 -4.68559295e-01 2.96149194e-01 -1.08280873e+00 -8.35518897e-01 -6.16944432e-01 3.82468194e-01 5.72625399e-01 2.53390402e-01 -7.11438775e-01 3.94833982e-02 5.95272481e-01 -8.34504008e-01 1.24487557e-01 1.03872573e+00 3.36128861e-01 -3.02713513e-01 6.75572574e-01 -1.85639977e-01 3.06847304e-01 -1.26301765e+00 -9.95546341e-01 3.20907831e-01 -2.85629779e-01 -7.38842070e-01 -4.25410956e-01 3.13603908e-01 -2.21320406e-01 -7.68425226e-01 1.46254289e+00 7.84259975e-01 2.17109054e-01 6.40597701e-01 -1.56475616e+00 -1.10855114e+00 1.04539728e+00 -8.70300680e-02 1.05499834e-01 2.95600176e-01 6.70572281e-01 6.43506706e-01 -7.68620789e-01 4.59802985e-01 1.86751354e+00 6.04006708e-01 1.05011487e+00 -1.25333405e+00 -1.08299887e+00 1.69215366e-01 -1.00160688e-02 -1.48824167e+00 -1.34295672e-01 6.17513835e-01 -1.07553609e-01 6.08540177e-01 7.99486697e-01 -8.28185976e-02 2.17563915e+00 3.31531018e-01 7.29485989e-01 9.32586193e-01 -3.20196122e-01 4.62148011e-01 3.52034897e-01 -3.39319408e-01 2.74978399e-01 3.01118135e-01 2.56773561e-01 -2.60560781e-01 -4.57395405e-01 1.98263377e-01 -2.43159950e-01 -1.89221993e-01 1.72839999e-01 -9.62012589e-01 1.09219003e+00 3.08761954e-01 2.44604185e-01 8.54963660e-02 1.54133469e-01 7.08410144e-01 2.45419994e-01 3.06501061e-01 9.87792015e-01 -3.23549896e-01 1.41864792e-01 -4.70674038e-01 4.48896974e-01 7.39386380e-01 1.03890467e+00 2.66751885e-01 5.51664293e-01 -4.71487552e-01 6.05451822e-01 2.52300888e-01 1.09926188e+00 8.03506374e-01 -3.52994859e-01 7.93427765e-01 6.64165765e-02 -5.64564392e-02 -1.23693120e+00 -1.24568060e-01 -3.11943889e-01 -1.13068378e+00 -1.15465842e-01 3.46701384e-01 -6.61547065e-01 -8.85570347e-01 2.11260581e+00 2.42653176e-01 5.04623413e-01 5.30585408e-01 5.73537529e-01 6.79287493e-01 6.49582565e-01 3.62554789e-01 2.83494383e-01 1.09904742e+00 -8.13643157e-01 -6.02307856e-01 -5.95533371e-01 5.59084773e-01 -7.32066393e-01 1.66408002e+00 1.33055910e-01 -9.83014762e-01 -3.16019922e-01 -1.01823473e+00 5.51913202e-01 -7.37198651e-01 -4.92877603e-01 2.06414610e-01 1.12342370e+00 -6.97545826e-01 4.92393762e-01 -6.43768549e-01 -1.15312673e-01 2.56203085e-01 1.58452407e-01 -2.29667410e-01 1.18200928e-01 -2.09731817e+00 8.53735626e-01 6.38538957e-01 -3.24613571e-01 -1.12202466e+00 -6.14943624e-01 -8.99539351e-01 3.27491038e-03 4.65445995e-01 -6.26492739e-01 1.09489191e+00 -7.03123927e-01 -1.56718838e+00 6.54236495e-01 3.98874581e-01 -6.46902263e-01 6.82027459e-01 -3.39367777e-01 -6.46482944e-01 1.16790190e-01 -1.56933859e-01 3.90423119e-01 9.69083965e-01 -1.37350059e+00 -6.10374212e-02 -1.10138945e-01 2.53007382e-01 2.34501958e-01 -9.99593318e-01 4.13034946e-01 -8.31665248e-02 -1.36533034e+00 -5.23009419e-01 -1.12700832e+00 -5.63256681e-01 -4.75011140e-01 -1.09231973e+00 -1.54333813e-02 8.67946923e-01 -4.57916588e-01 1.54939306e+00 -2.23008966e+00 2.63286263e-01 4.89576966e-01 -1.66924428e-02 7.89581001e-01 -4.39818859e-01 5.24538934e-01 -1.01001464e-01 9.69375670e-01 -3.21348459e-01 -9.89661515e-02 5.31745195e-01 8.98932442e-02 -7.61305511e-01 2.97310561e-01 -1.03729837e-01 1.10844707e+00 -9.30639625e-01 -3.06416303e-01 1.65299073e-01 2.35595241e-01 -6.22911453e-01 2.17418835e-01 -3.82944912e-01 2.42091820e-01 -5.36209285e-01 2.52257407e-01 4.85065699e-01 2.09770024e-01 -1.15031876e-01 1.59346804e-01 6.55837715e-01 7.91891515e-02 -1.06287801e+00 1.22584808e+00 -4.97428894e-01 4.42393363e-01 -1.33054271e-01 -4.95909482e-01 7.90608704e-01 2.65125930e-01 -3.05503141e-02 -1.58987731e-01 2.41442189e-01 1.25299186e-01 -7.09203929e-02 -1.81862384e-01 3.42579752e-01 -1.76422179e-01 -5.51981330e-01 4.61939663e-01 -1.67027578e-01 -4.33201253e-01 -1.60867035e-01 4.31514233e-01 1.15168953e+00 -5.43465257e-01 1.67599916e-01 -1.40140399e-01 7.44967520e-01 -2.80468643e-01 3.52018386e-01 9.46543336e-01 -3.40088516e-01 4.55809146e-01 3.70409161e-01 4.77377027e-02 -9.57621813e-01 -1.38478291e+00 2.01992199e-01 9.62537289e-01 2.16044575e-01 -7.85226524e-01 -1.31344712e+00 -1.16144741e+00 -1.74184851e-02 1.36309886e+00 -4.28809166e-01 -9.65620816e-01 -6.97542489e-01 -6.22734606e-01 1.47002006e+00 4.06167775e-01 3.92367303e-01 -1.40269005e+00 1.38410226e-01 7.77300075e-02 -1.75013393e-01 -1.20032668e+00 -9.56432164e-01 -3.56100917e-01 -3.52927715e-01 -7.88796008e-01 -2.76530057e-01 -6.53431177e-01 5.67186832e-01 -1.60383701e-01 1.06937706e+00 -6.35710508e-02 -3.49197313e-02 2.62149632e-01 -5.23232996e-01 -5.25968492e-01 -1.06057096e+00 1.34915531e-01 5.13880074e-01 -2.07867622e-01 2.97092706e-01 -4.63906378e-01 -3.85849535e-01 5.62896073e-01 -1.49912214e+00 -4.24418300e-01 2.21832588e-01 8.65787089e-01 2.36432806e-01 4.33923244e-01 6.30214632e-01 -1.04696798e+00 1.17183876e+00 -5.03877461e-01 -2.39850372e-01 4.13551599e-01 -3.72669309e-01 5.70210963e-02 1.52728522e+00 -1.07773876e+00 -7.50858307e-01 -5.72159827e-01 -4.51987535e-01 -6.73451066e-01 -2.95676291e-01 2.41443902e-01 -7.27440000e-01 2.23493241e-02 1.34977949e+00 2.86311835e-01 -3.69697779e-01 -5.51878437e-02 6.96484566e-01 6.38473094e-01 7.04014838e-01 -8.72782111e-01 1.73331189e+00 1.79892793e-01 -2.82150805e-01 -5.54653466e-01 -5.90648413e-01 2.67213404e-01 -1.57379672e-01 2.16782525e-01 7.12460577e-01 -6.34773374e-01 -3.41627806e-01 6.77332282e-01 -1.03806484e+00 -3.78014833e-01 -2.95700312e-01 2.69348800e-01 -3.90009791e-01 6.24034882e-01 -7.93485105e-01 -3.96200091e-01 -7.25222051e-01 -1.26081645e+00 8.18046033e-01 4.92309267e-03 -4.32853550e-01 -1.21614313e+00 2.42206194e-02 2.18327537e-01 5.63218534e-01 5.51675141e-01 1.00186741e+00 -1.27701628e+00 -3.92884463e-02 -3.33083928e-01 3.44436586e-01 5.90220809e-01 1.04808792e-01 1.48556337e-01 -6.60325587e-01 -5.66716850e-01 -4.01579328e-02 -3.95163804e-01 2.88538933e-01 -5.95635846e-02 1.29500115e+00 -9.77668047e-01 -1.38209939e-01 8.23773921e-01 1.01624799e+00 7.70497844e-02 7.72733152e-01 4.42912281e-01 7.94794083e-01 4.22251791e-01 5.76706588e-01 2.74333775e-01 -1.70352772e-01 7.53113985e-01 4.26384926e-01 1.15051195e-01 1.92973614e-01 -5.02361953e-01 8.61009836e-01 6.58213973e-01 6.91016316e-01 -7.69515216e-01 -1.00716543e+00 2.54758388e-01 -1.46082687e+00 -1.08036506e+00 2.86194324e-01 1.92383766e+00 1.19057167e+00 5.76147139e-01 -4.84569557e-02 2.59407777e-02 9.03183281e-01 1.98110744e-01 -6.74978316e-01 -6.20449603e-01 -3.91923577e-01 5.13262689e-01 5.42155862e-01 5.44432163e-01 -1.21405888e+00 1.73146236e+00 5.76446629e+00 1.53254271e+00 -9.52670634e-01 4.32726331e-02 4.06382054e-01 -2.11712807e-01 -6.68780923e-01 -2.90716410e-01 -7.97257006e-01 7.71530151e-01 1.05201924e+00 -8.76977324e-01 6.05757773e-01 9.13847625e-01 -3.69661152e-02 9.25438881e-01 -7.30346680e-01 6.98919058e-01 1.50451303e-01 -1.07000446e+00 5.64298213e-01 -2.14327261e-01 7.69241810e-01 -2.61189759e-01 5.38404882e-01 6.25622630e-01 9.97817636e-01 -1.42830563e+00 7.69471645e-01 -3.77617069e-02 1.15492833e+00 -1.18400037e+00 6.58256471e-01 5.26595771e-01 -7.59466410e-01 1.49235027e-02 -3.26761365e-01 5.99582016e-01 1.26555428e-01 5.66450842e-02 -6.90897405e-01 3.81214201e-01 4.95273948e-01 1.48819834e-01 -7.47326612e-01 2.56907195e-01 -6.23197377e-01 8.79846692e-01 -2.24175438e-01 -1.78068146e-01 5.34025729e-01 7.95482025e-02 9.38818395e-01 1.19167304e+00 2.07847998e-01 4.62152250e-02 2.96030730e-01 8.56534541e-01 -3.83838683e-01 1.79903761e-01 -8.38575661e-01 -2.24860147e-01 8.70923102e-01 9.64983165e-01 -2.78128743e-01 -1.83427826e-01 4.63058427e-02 1.10484064e+00 1.07823424e-01 6.11431837e-01 -1.19547558e+00 -7.06264675e-01 1.08333719e+00 -6.50106743e-02 -1.80411801e-01 -8.13031569e-02 -1.77558631e-01 -1.23363900e+00 -2.51020342e-01 -1.75336134e+00 3.74877930e-01 -5.07938862e-01 -1.69370830e+00 9.21412349e-01 -4.32616957e-02 -9.54556584e-01 -3.14514786e-01 -5.36757827e-01 -8.13069999e-01 9.58937824e-01 -6.63590550e-01 -8.94468367e-01 1.34210557e-01 9.52646554e-01 5.34391880e-01 -7.25857675e-01 1.05693519e+00 -1.13488492e-02 -9.17138398e-01 1.54487371e+00 3.17201078e-01 5.09933710e-01 9.28053558e-01 -1.26987505e+00 1.08278751e+00 1.21534979e+00 1.89957246e-01 7.49533355e-01 8.22613478e-01 -8.30528319e-01 -1.02330256e+00 -1.50904143e+00 4.04446006e-01 -7.83963144e-01 9.32811141e-01 -7.98496604e-01 -8.16041172e-01 6.50243044e-01 2.71219085e-03 -2.44616985e-01 7.28005350e-01 -3.80419195e-01 -5.96356273e-01 2.03153402e-01 -1.49073553e+00 1.48947465e+00 1.04311001e+00 -7.31593907e-01 -4.48772281e-01 5.24830103e-01 1.31514108e+00 -6.43833876e-01 -6.09714925e-01 4.17421877e-01 -5.48111387e-02 -5.86214960e-01 1.30288005e+00 -1.34885287e+00 3.33158940e-01 -5.01988791e-02 -3.17122757e-01 -1.70762289e+00 -2.42901832e-01 -1.11147034e+00 -3.85548681e-01 1.23760402e+00 4.11421657e-01 -7.58114398e-01 6.47982538e-01 5.15106022e-01 -2.20010597e-02 -6.06618941e-01 -8.70521903e-01 -1.05481422e+00 7.60274410e-01 -4.80427831e-01 9.30156410e-01 1.03204417e+00 -2.19796613e-01 2.76166767e-01 -2.95031637e-01 5.04099369e-01 5.24687588e-01 -5.84035695e-01 9.66710687e-01 -6.54050052e-01 -3.30225855e-01 -5.79358339e-01 -2.88482666e-01 -4.99224305e-01 8.04201186e-01 -1.00215900e+00 -9.91018340e-02 -8.34685147e-01 -2.35492289e-01 -3.73708367e-01 -2.08529502e-01 3.37769091e-01 -7.23692656e-01 1.20489158e-01 2.98655212e-01 2.70131435e-02 -2.83511460e-01 6.80609167e-01 1.00535095e+00 -3.28515351e-01 -7.55329803e-02 -8.04508030e-02 -9.80777621e-01 8.42682540e-01 1.23315525e+00 -5.83855391e-01 -6.14112020e-01 -3.21019024e-01 1.06114909e-01 -4.34815675e-01 2.00761706e-01 -8.36586654e-01 1.51660359e-02 -5.73755085e-01 2.66548805e-02 -2.12212256e-03 -1.01681545e-01 -5.74398756e-01 -9.52509418e-02 5.88444591e-01 -5.92645526e-01 2.53589422e-01 4.73959655e-01 5.75422287e-01 5.31352460e-02 -2.80876815e-01 9.42670465e-01 -2.59069651e-02 -1.21329725e-01 5.22993743e-01 -3.32981527e-01 7.26614296e-01 1.16414952e+00 2.02502847e-01 -5.53386390e-01 -4.29633707e-01 -4.98455018e-01 1.94050208e-01 4.86346513e-01 7.76626527e-01 6.15604579e-01 -1.47977376e+00 -1.05176234e+00 5.65535463e-02 -1.37965262e-01 -9.42778140e-02 1.56784460e-01 -2.80860644e-02 -5.72498679e-01 3.12307060e-01 1.41758192e-02 -3.79714780e-02 -1.30590379e+00 9.95457113e-01 3.29214156e-01 -6.71013832e-01 -5.63973308e-01 9.72535491e-01 3.54104429e-01 -6.81639731e-01 3.40742141e-01 2.09236175e-01 3.50222401e-02 -4.88962620e-01 5.45417666e-01 3.40539455e-01 -3.44826490e-01 -7.09653556e-01 -4.43244189e-01 1.73784137e-01 -2.12329641e-01 -3.15815061e-01 6.92211211e-01 2.74497896e-01 1.28097236e-01 -1.91029951e-01 1.06526840e+00 5.09202719e-01 -7.61052012e-01 -3.64605188e-01 -1.28527641e-01 -4.49675798e-01 -5.63525319e-01 -7.42876351e-01 -8.74636114e-01 6.50394857e-01 1.93045080e-01 2.16102302e-01 9.44191039e-01 -2.84455925e-01 1.16036892e+00 5.05967319e-01 2.64186770e-01 -9.43603992e-01 4.18405533e-01 5.74901700e-01 1.08713222e+00 -7.11797237e-01 -2.37930492e-01 -3.75409305e-01 -8.77076268e-01 6.02892637e-01 1.04649734e+00 -1.03252485e-01 4.44289714e-01 3.17495197e-01 2.09525153e-01 2.38131613e-01 -6.35314226e-01 2.77988017e-01 3.06710124e-01 7.45121896e-01 -1.16441831e-01 1.95984066e-01 7.93854520e-03 8.99478912e-01 -9.05171871e-01 -1.06832969e+00 4.93057430e-01 4.87854064e-01 -6.89162314e-02 -1.19654560e+00 -7.02309787e-01 1.25485390e-01 -7.73623645e-01 -3.35296035e-01 -7.37014532e-01 6.91447854e-01 -4.64976169e-02 1.30108833e+00 -5.47650576e-01 -8.16076159e-01 5.58786094e-01 -3.56600108e-03 1.40229221e-02 -7.51594424e-01 -9.23973680e-01 -4.84650105e-01 -1.17867619e-01 -4.53555703e-01 4.78757381e-01 -2.84194082e-01 -1.15074456e+00 -8.01895261e-01 -1.80979565e-01 3.30946475e-01 4.22120214e-01 7.06128597e-01 1.46827444e-01 4.82117832e-01 9.36258674e-01 -2.95784146e-01 -1.30347478e+00 -9.22838330e-01 -3.08183610e-01 9.94576097e-01 -1.48351863e-01 -2.05517232e-01 -7.85939217e-01 -3.59102279e-01]	[6.034061908721924, 8.11994743347168]
830fd922-6cf4-4087-9e0e-e296f2153951	coreference-strategies-in-english-german	null	null	https://aclanthology.org/2020.crac-1.15	https://aclanthology.org/2020.crac-1.15.pdf	Coreference Strategies in English-German Translation	We present a study focusing on variation of coreferential devices in English original TED talks and news texts and their German translations. Using exploratory techniques we contemplate a diverse set of coreference devices as features which we assume indicate language-specific and register-based variation as well as potential translation strategies. Our findings reflect differences on both dimensions with stronger variation along the lines of register than between languages. By exposing interactions between text type and cross-linguistic variation, they can also inform multilingual NLP applications, especially machine translation.	['Christian Hardmeier', 'Marie-Pauline Krielke', 'Ekaterina Lapshinova-Koltunski']	null	null	null	null	coling-crac-2020-12	['multilingual-nlp']	['natural-language-processing']	[-2.26455182e-01 8.50868076e-02 -7.59388924e-01 -4.88267392e-01 -1.11971879e+00 -1.34044981e+00 1.07545888e+00 5.33149466e-02 -4.31840092e-01 7.63628840e-01 1.20189536e+00 -6.83500528e-01 -3.60839486e-01 -2.85011321e-01 -2.66342789e-01 -1.35598674e-01 2.64034510e-01 9.43151951e-01 2.16222499e-02 -8.08956504e-01 3.27760220e-01 3.11835319e-01 -6.44343197e-01 7.97969341e-01 7.07686663e-01 6.92023262e-02 1.50075734e-01 9.78976935e-02 -3.49743456e-01 4.49606419e-01 -6.90704703e-01 -7.34148204e-01 -8.08128789e-02 -2.77494848e-01 -1.14324474e+00 -2.99714804e-01 3.65844905e-01 5.70355892e-01 -2.66024828e-01 1.00389397e+00 5.84531665e-01 -2.88487136e-01 3.05436909e-01 -2.79822499e-01 -3.73574376e-01 1.66852641e+00 -3.09001416e-01 8.72458100e-01 8.65768552e-01 -1.54784713e-02 1.35454357e+00 -6.94989622e-01 1.50858498e+00 1.39944398e+00 8.33319187e-01 4.60082084e-01 -1.49530578e+00 -3.19333732e-01 -1.69065058e-01 -1.92692142e-03 -1.20824063e+00 -9.83140290e-01 8.02833557e-01 -6.49173856e-01 1.03593016e+00 4.34436083e-01 4.04259086e-01 1.40063965e+00 1.72319084e-01 4.91789281e-01 1.34588706e+00 -7.61649668e-01 -4.72108901e-01 4.83094484e-01 1.40092865e-01 6.95013553e-02 5.23250774e-02 5.10054342e-02 -7.62539148e-01 -2.53091842e-01 5.61546236e-02 -5.88426292e-01 -7.09819138e-01 3.36837739e-01 -1.56438196e+00 6.72057033e-01 -1.34514064e-01 1.28551185e+00 -1.13856263e-01 -4.89629865e-01 8.19437683e-01 7.79930830e-01 4.05768692e-01 7.98409343e-01 -8.02355051e-01 -6.25797570e-01 -6.97653472e-01 2.26570070e-02 9.85191226e-01 1.05545306e+00 6.17337048e-01 -4.59099889e-01 -1.28153592e-01 1.18123543e+00 1.06330164e-01 4.05308336e-01 7.12897122e-01 -6.28321767e-01 1.18965149e+00 2.32775405e-01 -5.55952825e-02 -7.89352179e-01 -5.30047297e-01 -3.61389369e-01 1.34053424e-01 -9.20191944e-01 4.97675627e-01 -3.32519382e-01 -1.68289468e-02 1.87540936e+00 6.19708821e-02 -9.29364324e-01 -7.22479522e-02 5.60292959e-01 7.42127240e-01 2.97261417e-01 -5.51757291e-02 -6.61719561e-01 1.59139204e+00 -2.95100957e-01 -9.87471819e-01 -2.80056477e-01 1.04277372e+00 -1.39030337e+00 1.08045983e+00 -4.36086841e-02 -1.39507663e+00 -1.23313591e-01 -6.15014136e-01 -3.96210365e-02 -8.32390636e-02 -1.65999502e-01 4.36728448e-01 7.52119243e-01 -9.03005898e-01 5.45890570e-01 -6.73682928e-01 -6.48973644e-01 -2.53198802e-01 2.29094058e-01 -3.52321118e-01 3.87944311e-01 -1.22576296e+00 1.15652037e+00 1.86855420e-01 -9.63393450e-02 1.09336384e-01 -7.39206135e-01 -6.29180849e-01 -4.75614965e-01 5.41322269e-02 -2.09937871e-01 1.29257321e+00 -8.57700050e-01 -1.49469507e+00 1.42653430e+00 -1.85938522e-01 1.76904630e-02 2.82780319e-01 -1.66012749e-01 -1.01504290e+00 -1.75416201e-01 2.04412133e-01 1.07738702e-02 1.34103792e-02 -7.19904780e-01 -6.50159895e-01 -4.05578554e-01 -1.90568283e-01 4.02598470e-01 6.52459189e-02 8.72121036e-01 -8.39061886e-02 -6.99390054e-01 3.17008853e-01 -1.07863986e+00 3.86859834e-01 -7.60851026e-01 -4.29213643e-01 -4.06923622e-01 4.77421701e-01 -7.64468074e-01 1.49050188e+00 -2.02924681e+00 3.10752749e-01 7.82394707e-02 -1.39196858e-01 -6.88105896e-02 4.56896089e-02 9.37175512e-01 1.42099842e-01 5.11446953e-01 2.04561025e-01 -1.38599858e-01 8.82710516e-03 3.23833823e-01 -3.35747093e-01 9.24355268e-01 -1.33210644e-02 1.13574624e+00 -8.08735490e-01 -4.74967301e-01 -7.80742243e-02 2.10330933e-01 -4.75332052e-01 -1.97940230e-01 -1.18200481e-01 6.74509585e-01 -3.22421312e-01 6.45678103e-01 8.41265768e-02 2.98229784e-01 7.65520036e-01 -2.13181332e-01 -5.93174517e-01 1.51075411e+00 -4.99241531e-01 1.96790159e+00 -6.79787278e-01 1.03350842e+00 1.52434230e-01 -6.15599453e-01 8.23811531e-01 4.97988403e-01 -7.78548568e-02 -6.88276172e-01 2.53447503e-01 5.01172781e-01 6.88983619e-01 -4.57286417e-01 8.59263003e-01 -3.90789330e-01 -4.52095449e-01 4.10105228e-01 9.56297889e-02 -2.20938668e-01 -7.81672820e-03 7.16921687e-02 8.95554185e-01 -3.58267836e-02 3.78459215e-01 -9.78705227e-01 2.08655626e-01 3.07033837e-01 7.51252234e-01 4.07967001e-01 -3.49916257e-02 2.42373288e-01 5.75607538e-01 -1.09695166e-01 -7.85803139e-01 -9.07861769e-01 -8.24259937e-01 9.85822737e-01 -1.36611626e-01 -6.17539585e-01 -3.97081167e-01 -5.28020918e-01 -3.58939499e-01 9.16292727e-01 -5.88684559e-01 2.42282465e-01 -1.18893838e+00 -5.15557349e-01 8.43823552e-01 9.04152915e-02 -2.66439199e-01 -9.51468408e-01 -4.87130359e-02 1.41530544e-01 -7.62250662e-01 -1.14867592e+00 -8.00586045e-01 7.80062154e-02 -9.03407216e-01 -7.92267621e-01 -1.12935320e-01 -7.90512145e-01 -1.42485863e-02 -1.10220656e-01 1.56923831e+00 -4.88681486e-03 2.36569896e-01 3.04180712e-01 -5.14551222e-01 -1.43854976e-01 -8.69126201e-01 4.95664835e-01 8.12981799e-02 -4.53913629e-01 7.48530090e-01 -3.89840245e-01 -9.01847705e-02 2.22038388e-01 -3.26135874e-01 -6.12452388e-01 2.46478930e-01 7.94776618e-01 1.74236223e-01 -8.02830815e-01 5.78897223e-02 -1.44346273e+00 9.54180300e-01 -7.06533968e-01 -2.10205942e-01 4.42888558e-01 -4.82506543e-01 2.60467410e-01 2.32144684e-01 -4.57261026e-01 -1.29481030e+00 -8.02570701e-01 -1.35228992e-01 3.20863247e-01 -9.88821164e-02 7.33088076e-01 -2.66090006e-01 2.63443649e-01 1.00374687e+00 -2.16449991e-01 -2.27715775e-01 -6.73148394e-01 2.93106824e-01 9.09862578e-01 4.21245545e-01 -1.09161901e+00 5.88036537e-01 1.03997633e-01 -7.63884723e-01 -9.98053491e-01 -5.67259312e-01 -5.00856042e-01 -7.48044848e-01 6.72084540e-02 6.45641565e-01 -7.32284844e-01 -2.36214995e-01 -1.67489082e-01 -1.42208147e+00 -3.12253207e-01 -3.29461664e-01 7.34225094e-01 -3.66300642e-01 1.58275351e-01 -1.01150584e+00 -1.19687326e-01 -1.63139358e-01 -1.18061733e+00 1.03090727e+00 -3.47055912e-01 -1.17491746e+00 -1.50041735e+00 7.25467443e-01 2.55665541e-01 2.39157081e-01 -1.15869030e-01 1.04238772e+00 -1.01896548e+00 -6.07905164e-02 1.62384972e-01 2.99931049e-01 -4.96335655e-01 4.12455142e-01 -4.32254560e-02 -5.03391802e-01 -2.71279484e-01 7.57552236e-02 -9.14978385e-02 1.08126007e-01 2.17918947e-01 -1.80698633e-01 -4.77832943e-01 -4.81752872e-01 6.86834395e-01 1.19538796e+00 2.41428405e-01 5.11422575e-01 7.32734680e-01 3.74141663e-01 1.07122886e+00 4.10167187e-01 1.00630405e-03 3.81954372e-01 1.15401053e+00 -4.62354720e-01 5.44428289e-01 -1.81647792e-01 -2.61425853e-01 7.24780679e-01 1.50102878e+00 -2.39765421e-02 -1.83928609e-01 -1.09242225e+00 7.90881872e-01 -1.34169006e+00 -1.26237702e+00 -4.88119245e-01 1.97226930e+00 1.20146239e+00 4.71439362e-02 2.25008562e-01 -2.94644088e-01 8.47555399e-01 3.01924139e-01 2.64021575e-01 -6.45479858e-01 -4.92836148e-01 2.31330842e-01 3.37561041e-01 8.87051344e-01 -2.88123429e-01 1.25370181e+00 7.67596340e+00 4.80208129e-01 -1.26899421e+00 2.16665626e-01 -9.89219360e-03 3.14978473e-02 -1.06328511e+00 2.34367788e-01 -9.36869740e-01 4.68496710e-01 1.10002196e+00 -1.59396663e-01 4.59849954e-01 1.86325148e-01 1.02815494e-01 4.42749918e-01 -1.19212770e+00 6.61872983e-01 -6.01006821e-02 -1.33223307e+00 -3.84022415e-01 3.66511419e-02 5.39246082e-01 6.32540226e-01 -2.03970134e-01 4.63568158e-02 4.23870027e-01 -4.82009530e-01 1.10150516e+00 -3.27582397e-02 1.00883508e+00 -3.43820602e-01 6.58888340e-01 -4.81413640e-02 -8.84446800e-01 3.40817064e-01 -1.04744077e-01 2.47412659e-02 5.22015393e-01 1.91370428e-01 -8.03700089e-01 4.17690217e-01 4.35766041e-01 7.62696028e-01 -2.69069344e-01 3.58217359e-01 -4.38171685e-01 9.76865530e-01 -1.88242510e-01 -8.39707926e-02 -3.80847268e-02 -3.68693203e-01 1.10185397e+00 1.78908789e+00 2.29969472e-01 -1.01852253e-01 -1.59825310e-01 6.39458299e-01 1.52440161e-01 4.91780072e-01 -6.67028010e-01 -1.91936389e-01 1.11225379e+00 1.04245913e+00 -6.91102207e-01 -2.62410603e-02 -5.69428205e-01 7.47987926e-01 5.08914948e-01 2.58472085e-01 -3.48795056e-01 -1.44497991e-01 9.13098633e-01 2.36481383e-01 5.92456721e-02 -3.61580253e-01 -3.28591198e-01 -1.43324018e+00 7.63641819e-02 -1.19211137e+00 4.55879778e-01 -2.62337089e-01 -1.37042773e+00 1.02527535e+00 -2.54019462e-02 -1.07171094e+00 -4.27464575e-01 -3.37501317e-01 -5.66757083e-01 8.85873020e-01 -1.06032932e+00 -1.08310390e+00 4.83738750e-01 7.13606775e-01 4.05896068e-01 -4.33515847e-01 6.74551606e-01 2.63909429e-01 -3.76568764e-01 8.88767600e-01 1.28988594e-01 2.20962465e-01 9.97274637e-01 -1.11722159e+00 4.65719402e-01 6.61364377e-01 5.94151795e-01 1.20519161e+00 9.86533701e-01 -5.52135944e-01 -1.20160842e+00 -4.82051015e-01 1.74375272e+00 -8.74838352e-01 1.21345186e+00 -3.74381363e-01 -6.33187830e-01 1.17139018e+00 8.00867498e-01 -4.96387661e-01 7.97670484e-01 1.18723893e+00 -2.98341900e-01 1.87911525e-01 -9.04897451e-01 7.84838974e-01 1.47068155e+00 -1.14537072e+00 -1.23194933e+00 2.35585049e-01 7.40746558e-01 -5.06592631e-01 -1.15305340e+00 1.44054651e-01 3.69397014e-01 -9.03933227e-01 3.81613672e-01 -5.62094569e-01 1.07716441e-01 4.00251225e-02 -3.91104639e-01 -1.61438966e+00 -4.03426766e-01 -1.17054784e+00 5.33171177e-01 1.62351787e+00 9.45020556e-01 -6.34735703e-01 1.78696096e-01 4.72327501e-01 -6.65280461e-01 -1.44684047e-01 -1.07574821e+00 -6.18049920e-01 5.34465492e-01 -5.23945689e-01 5.33334970e-01 1.52902222e+00 1.01823401e+00 8.51060092e-01 2.22198278e-01 -2.69049495e-01 -5.28432615e-02 6.62830472e-02 4.36425745e-01 -1.02874553e+00 -5.85108399e-01 -6.60664678e-01 -3.39816988e-01 -9.70921934e-01 3.78314912e-01 -1.30808854e+00 -5.79614453e-02 -8.62345994e-01 3.24172303e-02 -7.40528345e-01 2.65027344e-01 1.50136366e-01 2.61359811e-01 -6.14922196e-02 5.58672734e-02 6.60167634e-01 -2.42409766e-01 6.49541914e-02 8.94282222e-01 1.02428421e-02 -6.62922144e-01 -1.05465554e-01 -8.45423877e-01 5.38888276e-01 6.85721993e-01 -6.05404377e-01 -3.61015797e-02 -8.38347673e-01 4.60588157e-01 3.38896543e-01 -4.29775745e-01 -2.84437120e-01 7.03908354e-02 -3.45505476e-01 -4.14894789e-01 -2.36795783e-01 -1.15953408e-01 -4.80338365e-01 2.89575547e-01 2.70858258e-01 -4.65096265e-01 5.71157515e-01 2.64916390e-01 -1.31732106e-01 -4.03071344e-01 -1.88056156e-01 3.08003187e-01 -2.17505112e-01 -1.38749748e-01 -1.52994305e-01 -5.13798773e-01 7.74146616e-01 5.36635816e-01 -2.97759533e-01 -5.52658141e-01 -1.79458514e-01 -6.15035534e-01 -2.58698881e-01 6.58041060e-01 6.70672536e-01 -1.59503102e-01 -1.26799417e+00 -8.20965588e-01 7.32142776e-02 1.97939068e-01 -7.21310139e-01 -1.64833963e-01 1.17102146e+00 -2.36775562e-01 5.74018955e-01 4.92436178e-02 -5.40296972e-01 -1.21003950e+00 2.32858047e-01 3.74128461e-01 -2.30007619e-01 -4.30357367e-01 7.46654570e-01 -1.79024577e-01 -7.48988330e-01 -1.60884485e-01 -3.80894057e-02 -1.59059897e-01 3.92451525e-01 2.76801974e-01 1.83208525e-01 1.52337700e-01 -1.16652584e+00 -6.48320019e-01 4.80539262e-01 -2.18796894e-01 -5.96546650e-01 1.11065924e+00 -6.80917561e-01 -4.69059199e-01 9.82685447e-01 1.10552657e+00 1.12016094e+00 -3.49419653e-01 -4.71345216e-01 7.22557366e-01 -3.97527158e-01 -2.74910033e-01 -8.59476924e-01 -5.81714332e-01 4.12178725e-01 9.04512871e-03 1.49892285e-01 5.15994072e-01 7.40416229e-01 5.12548208e-01 2.24529669e-01 5.75608730e-01 -1.26896715e+00 -6.51368499e-01 7.58010805e-01 9.51328158e-01 -9.54772353e-01 -2.64403939e-01 -2.44900689e-01 -6.21310115e-01 1.03963375e+00 1.91122323e-01 3.05818796e-01 6.15341485e-01 4.94367570e-01 5.16678512e-01 -4.59404320e-01 -7.33129740e-01 -1.17809214e-02 3.94724280e-01 5.26951790e-01 1.46744931e+00 2.53927767e-01 -1.30807090e+00 4.72826988e-01 -8.97077620e-01 -6.23296261e-01 4.80624735e-01 4.86485392e-01 7.25031719e-02 -1.78946006e+00 -2.96555817e-01 2.45401561e-01 -9.15174901e-01 -5.88915706e-01 -6.35860324e-01 1.12025249e+00 -1.57922115e-02 1.05283332e+00 4.21636820e-01 -6.31496906e-01 3.64165038e-01 6.51356652e-02 6.37342274e-01 -9.61502731e-01 -1.09084356e+00 1.14864640e-01 1.04802763e+00 -3.38575929e-01 -7.41302192e-01 -1.50728798e+00 -8.21891010e-01 -6.14626169e-01 -7.04308033e-01 6.49790466e-01 3.88924509e-01 1.21600175e+00 2.57409483e-01 6.75403774e-02 3.35541189e-01 -3.90197515e-01 -3.46919507e-01 -1.35776877e+00 -4.08012539e-01 5.14836848e-01 1.76114514e-01 -4.20513451e-01 -3.76455814e-01 -1.34022743e-01]	[11.004838943481445, 10.04818344116211]
a8370011-6466-47c7-bb35-f0bb125b7a03	offline-experience-replay-for-continual	2305.13804	null	https://arxiv.org/abs/2305.13804v1	https://arxiv.org/pdf/2305.13804v1.pdf	Offline Experience Replay for Continual Offline Reinforcement Learning	The capability of continuously learning new skills via a sequence of pre-collected offline datasets is desired for an agent. However, consecutively learning a sequence of offline tasks likely leads to the catastrophic forgetting issue under resource-limited scenarios. In this paper, we formulate a new setting, continual offline reinforcement learning (CORL), where an agent learns a sequence of offline reinforcement learning tasks and pursues good performance on all learned tasks with a small replay buffer without exploring any of the environments of all the sequential tasks. For consistently learning on all sequential tasks, an agent requires acquiring new knowledge and meanwhile preserving old knowledge in an offline manner. To this end, we introduced continual learning algorithms and experimentally found experience replay (ER) to be the most suitable algorithm for the CORL problem. However, we observe that introducing ER into CORL encounters a new distribution shift problem: the mismatch between the experiences in the replay buffer and trajectories from the learned policy. To address such an issue, we propose a new model-based experience selection (MBES) scheme to build the replay buffer, where a transition model is learned to approximate the state distribution. This model is used to bridge the distribution bias between the replay buffer and the learned model by filtering the data from offline data that most closely resembles the learned model for storage. Moreover, in order to enhance the ability on learning new tasks, we retrofit the experience replay method with a new dual behavior cloning (DBC) architecture to avoid the disturbance of behavior-cloning loss on the Q-learning process. In general, we call our algorithm offline experience replay (OER). Extensive experiments demonstrate that our OER method outperforms SOTA baselines in widely-used Mujoco environments.	['Li He', 'Donglin Wang', 'Sibo Gai']	2023-05-23	null	null	null	null	['q-learning']	['methodology']	[-3.27697933e-01 -1.63840801e-01 -2.08112404e-01 3.44461799e-02 -5.31136453e-01 -6.68857932e-01 5.29335976e-01 1.36133194e-01 -8.13187003e-01 1.06988776e+00 -1.27032921e-01 -3.07840109e-01 -2.16687784e-01 -7.28994250e-01 -1.05213225e+00 -8.37023258e-01 -2.23643661e-01 4.83221859e-01 4.35464859e-01 -8.07555243e-02 1.23484440e-01 3.38925719e-01 -1.62892687e+00 5.68089681e-03 1.12054086e+00 7.32379258e-01 7.63474584e-01 4.53526884e-01 -1.79083049e-02 9.58376765e-01 -5.90847194e-01 -2.22829431e-01 4.32293534e-01 -4.66832221e-01 -6.08544409e-01 1.32738158e-01 -1.03587441e-01 -7.05447257e-01 -5.78018069e-01 1.00356066e+00 4.55383390e-01 5.16603351e-01 1.66412026e-01 -1.44646001e+00 -5.14226794e-01 7.89484441e-01 -3.64049762e-01 2.59995490e-01 1.41951993e-01 5.59432507e-01 3.77439857e-01 -6.71603918e-01 5.88073969e-01 9.57109630e-01 4.40324724e-01 6.78193271e-01 -8.70309055e-01 -4.95180815e-01 5.40512323e-01 3.55698824e-01 -1.08543813e+00 -2.55872399e-01 5.76302588e-01 2.78315805e-02 8.20309639e-01 -1.04726680e-01 1.00642455e+00 1.40180480e+00 5.66998422e-01 1.17439187e+00 1.48021054e+00 -2.60779351e-01 8.57616901e-01 4.55700010e-01 -1.78544223e-01 5.69770217e-01 1.65704072e-01 5.34498632e-01 -7.65276909e-01 -2.36178681e-01 6.68759823e-01 5.09843528e-01 -2.02690706e-01 -6.74923658e-01 -9.01022613e-01 3.50071400e-01 1.95986375e-01 9.27113891e-02 -5.93216062e-01 5.37864193e-02 4.70484674e-01 1.04833007e+00 1.96539387e-01 4.60943550e-01 -6.04600847e-01 -4.35432464e-01 -5.71378827e-01 4.07463223e-01 7.22429991e-01 1.14811766e+00 9.30314362e-01 1.68004483e-01 -3.16157043e-01 4.99694735e-01 -2.06471324e-01 5.70252240e-01 9.25608277e-01 -9.57078099e-01 3.92939091e-01 4.05007988e-01 5.16365945e-01 -2.52950460e-01 -6.72025681e-02 -6.03168428e-01 -4.03090954e-01 2.35020861e-01 4.50432569e-01 -2.69135058e-01 -7.72846162e-01 2.00331092e+00 5.74106932e-01 3.85145754e-01 2.46140391e-01 8.23934436e-01 -3.58291090e-01 5.84087014e-01 9.18567702e-02 -7.08002329e-01 6.78963780e-01 -1.08050394e+00 -6.66140616e-01 -1.82831839e-01 4.22619194e-01 -1.83225110e-01 1.43739939e+00 6.47400320e-01 -1.23814917e+00 -6.44868731e-01 -1.06800592e+00 4.28302437e-01 -2.64914006e-01 -2.86850095e-01 4.58685130e-01 3.88704240e-01 -9.77327943e-01 8.85851622e-01 -1.15620983e+00 -2.57112861e-01 1.65019780e-01 1.21627912e-01 1.30836461e-02 -2.21703023e-01 -1.19456291e+00 8.13932359e-01 5.45434117e-01 -1.67746544e-01 -1.70271361e+00 -6.34287000e-01 -4.57698762e-01 5.05602546e-02 1.10350621e+00 -5.92603981e-01 1.55567646e+00 -1.24468517e+00 -1.84151423e+00 1.52256221e-01 1.31760359e-01 -7.40755320e-01 7.48980999e-01 -5.09029150e-01 -3.46759409e-01 5.40124346e-03 -2.39295125e-01 1.46131590e-01 1.27784979e+00 -1.52154779e+00 -8.08942020e-01 -3.66941124e-01 1.35331810e-01 5.24056435e-01 -5.56570113e-01 -5.95648348e-01 -1.80580035e-01 -5.51786482e-01 -3.09931397e-01 -1.01013148e+00 -1.13009661e-01 -3.97029340e-01 2.58879185e-01 -2.31222317e-01 7.14776158e-01 -3.89276415e-01 1.25942290e+00 -2.35367560e+00 1.92821786e-01 1.43653810e-01 5.32918274e-02 2.80175537e-01 -4.15218830e-01 7.01088071e-01 3.96677464e-01 -3.82165492e-01 -5.36637120e-02 -5.85440814e-01 -6.23946115e-02 5.67953348e-01 -7.86567271e-01 2.12514251e-01 -3.22184265e-01 8.05053711e-01 -1.32200122e+00 -9.36449543e-02 -2.33783796e-01 -1.48181021e-01 -6.11353993e-01 6.56000078e-01 -6.63316131e-01 4.95477587e-01 -4.17418003e-01 4.35605705e-01 7.27766514e-01 -3.44909318e-02 5.38065076e-01 5.59082031e-01 -4.82981391e-02 7.07050487e-02 -1.10114670e+00 2.06756115e+00 -6.82399035e-01 -1.87626719e-01 -1.17704663e-02 -7.43094504e-01 7.50514507e-01 2.29559407e-01 3.85087639e-01 -9.48622525e-01 -1.66128278e-01 2.40752846e-01 -1.06517691e-02 -5.14826715e-01 6.87459290e-01 -1.92200392e-01 6.31317720e-02 7.74993539e-01 3.53409201e-01 1.33868411e-01 -3.28205898e-02 3.22641581e-01 1.18222058e+00 3.17019165e-01 1.86820894e-01 -1.23622119e-02 8.42377767e-02 -3.92330345e-03 9.19076681e-01 1.42137432e+00 -6.42099023e-01 -1.58864241e-02 2.94491917e-01 -4.06752646e-01 -9.38095212e-01 -1.33339632e+00 4.66751754e-01 1.34319365e+00 3.52059215e-01 -2.76615500e-01 -6.08961165e-01 -1.15793264e+00 2.03641310e-01 8.52225482e-01 -3.78814191e-01 -6.82039559e-01 -5.37225425e-01 -3.06630254e-01 2.07951427e-01 4.78168190e-01 7.94303596e-01 -1.37819397e+00 -9.85678077e-01 4.54534233e-01 8.62712711e-02 -5.02623975e-01 -7.05621064e-01 5.15398502e-01 -9.92400706e-01 -8.39497507e-01 -6.73750699e-01 -5.27318418e-01 4.80084836e-01 4.30172056e-01 8.54985774e-01 3.14442739e-02 1.49129525e-01 6.91657186e-01 -4.15198177e-01 -3.08850110e-01 -3.83513600e-01 1.39792562e-01 6.60423756e-01 -5.71716428e-02 2.82237470e-01 -6.81055188e-01 -7.29214609e-01 8.91663358e-02 -1.10754991e+00 -2.02060431e-01 6.81884944e-01 1.21032643e+00 5.38360000e-01 4.33257967e-01 1.07747328e+00 -7.79298961e-01 7.65461385e-01 -7.40428925e-01 -5.96931517e-01 5.35002887e-01 -1.04220200e+00 1.57205507e-01 1.13143206e+00 -1.00829923e+00 -1.51296115e+00 -2.06922933e-01 2.79340923e-01 -7.81020284e-01 2.09849179e-02 4.87642914e-01 -5.09138405e-02 3.58521312e-01 5.84080994e-01 7.37296760e-01 2.86538005e-01 -4.50588435e-01 3.47863138e-01 6.09375536e-01 4.54928637e-01 -1.02227819e+00 6.65152848e-01 2.69688487e-01 -4.90323484e-01 -2.06350788e-01 -8.70292842e-01 -2.02419460e-01 -1.53679073e-01 -2.77329952e-01 1.22974642e-01 -9.64389443e-01 -6.94523394e-01 9.29644704e-01 -6.76954329e-01 -1.09644377e+00 -8.19968402e-01 4.81834471e-01 -9.67302084e-01 2.02887356e-01 -7.14300394e-01 -1.07429338e+00 6.75213039e-02 -1.13444364e+00 3.72774541e-01 4.48257565e-01 3.72382402e-01 -8.06284070e-01 4.30418044e-01 -1.53512865e-01 5.26629686e-01 -3.76975298e-01 8.50331306e-01 -6.54068530e-01 -6.59157991e-01 3.71181339e-01 3.54013264e-01 3.26067805e-01 -4.60818261e-02 -7.02249348e-01 -8.23675036e-01 -1.10863066e+00 5.31736076e-01 -8.66477489e-01 8.35152447e-01 2.31071399e-03 1.22408700e+00 -4.75137383e-01 -1.56948730e-01 3.23484272e-01 1.47847247e+00 5.58051884e-01 4.74584520e-01 6.10944808e-01 1.34323105e-01 3.06167483e-01 1.00332868e+00 8.34652126e-01 3.65257680e-01 2.23450527e-01 3.32165658e-01 4.94039536e-01 3.02920751e-02 -9.33151186e-01 9.29971635e-01 8.42254698e-01 2.68736452e-01 -1.23066634e-01 -5.50312340e-01 6.96947277e-01 -2.20057464e+00 -8.65830004e-01 9.01767075e-01 2.62115288e+00 1.20590842e+00 3.02582145e-01 2.76051909e-01 -2.72157252e-01 2.90843427e-01 -1.31772518e-01 -1.20399654e+00 -1.42359629e-01 1.58516839e-01 5.93373850e-02 3.58322233e-01 3.84852290e-01 -5.34761429e-01 9.63819146e-01 5.40134239e+00 8.92899573e-01 -9.89906669e-01 3.70808512e-01 3.63599360e-01 -2.03798831e-01 -2.63728112e-01 1.66458324e-01 -6.83229566e-01 7.06002176e-01 9.49477851e-01 -3.02854091e-01 1.04559517e+00 1.05177605e+00 9.00022779e-03 -4.80268896e-01 -1.12463677e+00 7.88765728e-01 -2.11722031e-01 -7.83814311e-01 -6.35499060e-02 -1.48248717e-01 8.53123009e-01 -9.56610888e-02 3.79055232e-01 9.64093506e-01 5.87327898e-01 -4.90575045e-01 9.08036530e-01 8.13066840e-01 6.23181641e-01 -8.48958611e-01 4.64863002e-01 8.97361934e-01 -8.24487746e-01 -6.69692039e-01 -4.13316309e-01 -1.22669965e-01 -9.68131498e-02 3.02284658e-01 -6.62474096e-01 4.99830723e-01 7.42324710e-01 3.90172392e-01 -5.07591724e-01 1.03267026e+00 -1.02574930e-01 6.15781248e-01 -1.67580605e-01 -3.02859321e-02 1.60488710e-01 -1.13955766e-01 5.73784351e-01 4.85539407e-01 4.69464809e-01 -4.08089049e-02 4.37801391e-01 7.41635978e-01 3.68971750e-02 -2.82947391e-01 -8.29718590e-01 4.17001285e-02 9.26044047e-01 8.21050584e-01 -3.68742049e-01 -4.45445150e-01 -1.74276203e-01 1.24780238e+00 8.08083951e-01 6.38435185e-01 -7.62934268e-01 -1.02041043e-01 3.07437867e-01 -4.04299125e-02 2.16615364e-01 -3.86295199e-01 2.41457373e-01 -1.35681081e+00 5.51251583e-02 -1.17328608e+00 3.80150855e-01 -5.06849706e-01 -1.49031758e+00 3.07783246e-01 3.92814763e-02 -1.18985057e+00 -2.20568866e-01 -8.68403446e-03 -4.70099777e-01 4.39515650e-01 -1.64845550e+00 -5.68478286e-01 -9.66114774e-02 8.96776855e-01 7.71854520e-01 -4.26992506e-01 4.22979653e-01 2.42113192e-02 -5.00545859e-01 6.77303076e-01 5.13760507e-01 -6.41850114e-01 9.26673234e-01 -1.42610013e+00 -2.52486691e-02 6.42902553e-01 -2.36639585e-02 7.59884179e-01 6.53762281e-01 -8.67962062e-01 -1.79456353e+00 -1.10631871e+00 1.90697014e-01 -1.45158693e-01 5.85616767e-01 -3.37453246e-01 -1.18216777e+00 8.40953231e-01 2.52291024e-01 -1.84752092e-01 2.20973745e-01 -1.65052518e-01 -1.23202965e-01 -3.02219093e-01 -1.10029626e+00 6.85080409e-01 1.10212147e+00 -5.27869999e-01 -6.02293432e-01 8.84590223e-02 9.21199143e-01 -3.75016838e-01 -5.60812652e-01 2.53599137e-02 2.78215021e-01 -9.97284114e-01 5.11492908e-01 -6.98603272e-01 -1.74396373e-02 -2.33821169e-01 7.41705447e-02 -1.85361004e+00 -1.06829748e-01 -1.02570319e+00 -7.25712121e-01 1.06023073e+00 -9.57066715e-02 -8.05788338e-01 5.64345896e-01 3.34824562e-01 -6.09021559e-02 -7.24850178e-01 -8.45928431e-01 -1.27795184e+00 1.68497324e-01 -1.16975717e-01 7.60473907e-01 6.21715367e-01 2.22254187e-01 1.42268091e-02 -5.86525142e-01 -7.47875543e-03 7.15555966e-01 1.88181937e-01 7.86498308e-01 -5.87732553e-01 -7.46354222e-01 1.48715436e-01 5.01998842e-01 -1.37770021e+00 2.41526797e-01 -6.55777693e-01 2.88288593e-01 -8.43588233e-01 4.81455117e-01 -8.56990218e-01 -8.18563640e-01 3.59020621e-01 -2.81156003e-01 -7.40145028e-01 4.48791236e-01 4.16664302e-01 -1.07529438e+00 1.02613389e+00 1.45205462e+00 1.46477729e-01 -6.55146658e-01 1.14864230e-01 -3.98426831e-01 3.78300786e-01 8.30950260e-01 -5.18776834e-01 -9.11030591e-01 -3.49421203e-01 2.94899017e-01 4.41648930e-01 8.01099762e-02 -1.04401302e+00 4.36851233e-01 -4.59555864e-01 7.84224793e-02 -3.84039611e-01 -3.06037422e-02 -9.50949371e-01 4.35566530e-02 7.00438917e-01 -4.42682058e-01 2.34300196e-01 2.34863013e-02 1.05714524e+00 6.04470372e-02 -3.51846844e-01 5.55945158e-01 -3.96282673e-01 -8.50708008e-01 3.61177951e-01 -4.81301248e-01 4.91996221e-02 1.24993682e+00 1.93511143e-01 -4.47326273e-01 -3.49277586e-01 -9.11607504e-01 6.60766244e-01 6.58383548e-01 3.78866822e-01 7.61051416e-01 -1.19338107e+00 -9.66075212e-02 3.54310066e-01 5.41105792e-02 -2.24241037e-02 4.25528944e-01 6.94632709e-01 1.01882793e-01 -1.04316108e-01 -3.64072889e-01 -2.06754223e-01 -4.66967225e-01 1.02474773e+00 2.63888031e-01 -7.20668912e-01 -5.96850872e-01 3.84333313e-01 -9.17331874e-02 -4.64021415e-01 6.05930090e-01 -1.59503266e-01 1.90757617e-01 -1.35158002e-01 5.85105419e-01 4.88551259e-01 -9.18140518e-04 5.12592614e-01 7.00302422e-02 -3.81401628e-01 -5.40463209e-01 -3.50388318e-01 1.18203282e+00 -5.07196069e-01 1.90871596e-01 8.75374317e-01 6.02441251e-01 -2.29425699e-01 -2.11518383e+00 -5.12269855e-01 -9.31288376e-02 -4.70215529e-01 -2.20500469e-01 -9.93404865e-01 -7.35200584e-01 5.33987582e-01 8.08511853e-01 1.91330165e-01 1.13602185e+00 -3.49453509e-01 1.00172138e+00 5.68920016e-01 1.03124106e+00 -1.70121145e+00 7.11891651e-01 6.64106071e-01 6.50371611e-01 -1.00349367e+00 -3.47582310e-01 4.31452096e-01 -9.99628782e-01 7.62622416e-01 1.12829864e+00 -1.35609627e-01 5.29440105e-01 2.08638668e-01 -1.24307215e-01 1.24396361e-01 -1.24945915e+00 -1.19858392e-01 -6.04391694e-01 7.07729399e-01 -4.31972980e-01 7.58258700e-02 -1.81103304e-01 7.18371987e-01 2.25485742e-01 3.43579531e-01 6.14569247e-01 1.44590998e+00 -5.82715333e-01 -1.15672362e+00 -1.49777219e-01 2.29465574e-01 -2.63456311e-02 1.65326297e-01 4.46840115e-02 5.45683503e-01 3.10435072e-02 6.53254926e-01 8.52048248e-02 -3.16262245e-01 1.45955890e-01 3.83444250e-01 5.88607967e-01 -5.20945549e-01 -7.58151829e-01 5.92155308e-02 -3.79114449e-01 -6.73517823e-01 -4.88447351e-03 -5.98142564e-01 -1.23024905e+00 -1.77473724e-01 -1.75927043e-01 2.72427380e-01 2.20500663e-01 8.19677889e-01 5.75867891e-01 4.33101356e-01 1.04964995e+00 -3.42052758e-01 -1.53818595e+00 -8.68155897e-01 -1.00379121e+00 4.85039085e-01 4.62050140e-01 -8.68965745e-01 -2.93818325e-01 -1.16646498e-01]	[4.101278305053711, 2.1355297565460205]
4227fb78-9650-4fc0-bff5-d78933b5053e	planematch-patch-coplanarity-prediction-for	1803.08407	null	http://arxiv.org/abs/1803.08407v3	http://arxiv.org/pdf/1803.08407v3.pdf	PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction	We introduce a novel RGB-D patch descriptor designed for detecting coplanar surfaces in SLAM reconstruction. The core of our method is a deep convolutional neural net that takes in RGB, depth, and normal information of a planar patch in an image and outputs a descriptor that can be used to find coplanar patches from other images.We train the network on 10 million triplets of coplanar and non-coplanar patches, and evaluate on a new coplanarity benchmark created from commodity RGB-D scans. Experiments show that our learned descriptor outperforms alternatives extended for this new task by a significant margin. In addition, we demonstrate the benefits of coplanarity matching in a robust RGBD reconstruction formulation.We find that coplanarity constraints detected with our method are sufficient to get reconstruction results comparable to state-of-the-art frameworks on most scenes, but outperform other methods on standard benchmarks when combined with a simple keypoint method.	['Thomas Funkhouser', 'Szymon Rusinkiewicz', 'Matthias Niessner', 'Kai Xu', 'Yifei Shi']	2018-03-22	planematch-patch-coplanarity-prediction-for-1	http://openaccess.thecvf.com/content_ECCV_2018/html/Yifei_Shi_PlaneMatch_Patch_Coplanarity_ECCV_2018_paper.html	http://openaccess.thecvf.com/content_ECCV_2018/papers/Yifei_Shi_PlaneMatch_Patch_Coplanarity_ECCV_2018_paper.pdf	eccv-2018-9	['rgb-d-reconstruction']	['computer-vision']	[ 3.49803925e-01 -2.33732402e-01 1.17222993e-02 -3.25250238e-01 -9.31340158e-01 -6.36834204e-01 8.35670292e-01 8.55981279e-03 -4.55560565e-01 1.03224866e-01 7.37796957e-03 2.05048881e-02 -1.35688841e-01 -8.28844070e-01 -1.29654133e+00 -3.58510643e-01 -1.29218176e-01 8.24876606e-01 3.08144242e-01 -2.99945951e-01 2.91764766e-01 1.16694915e+00 -1.64086854e+00 2.59913832e-01 2.38557920e-01 1.32825267e+00 -5.99695882e-03 2.38987088e-01 2.91628242e-01 7.12805614e-02 -2.04839155e-01 -6.85419813e-02 7.88322628e-01 1.70467556e-01 -5.02407253e-01 -7.85039738e-02 1.13324726e+00 -3.26498002e-01 -3.10217768e-01 4.89636093e-01 3.70663553e-01 -1.13737844e-02 6.17939830e-01 -9.55238521e-01 -2.46871307e-01 -1.74579754e-01 -6.80644274e-01 -4.30674911e-01 1.10473180e+00 -7.66387805e-02 1.03798473e+00 -1.03221905e+00 9.72497642e-01 1.38809168e+00 1.14161837e+00 6.20753178e-03 -1.16536069e+00 -4.52230930e-01 -2.74848372e-01 -2.07216814e-01 -1.36570036e+00 -3.76884252e-01 8.72286797e-01 -1.39200166e-01 1.37183666e+00 1.36145115e-01 8.27442348e-01 1.10047543e+00 3.21693152e-01 5.24402440e-01 1.03287208e+00 -4.19188142e-01 4.04021740e-02 -4.43663031e-01 -2.97963470e-01 9.52367127e-01 1.91009477e-01 3.11205536e-01 -6.64025486e-01 -2.61885047e-01 1.04454553e+00 2.54251689e-01 -1.85593888e-01 -1.05965877e+00 -1.45936191e+00 5.39470732e-01 9.04769123e-01 -9.77019295e-02 -3.71014208e-01 5.00604331e-01 -2.27324571e-02 2.29820967e-01 3.68882507e-01 5.43137848e-01 -2.35799193e-01 4.66770232e-02 -8.13209832e-01 3.15862477e-01 8.27222824e-01 1.04946935e+00 1.26935661e+00 -4.04962987e-01 5.63435137e-01 4.73579735e-01 3.07606548e-01 1.07800245e+00 -2.86932677e-01 -1.32697093e+00 3.45730931e-01 6.67140007e-01 9.05851498e-02 -1.12568188e+00 -6.69638455e-01 -9.76895690e-02 -3.99690300e-01 3.26537728e-01 -5.49737876e-03 4.06843811e-01 -1.04841101e+00 9.81286705e-01 2.50669628e-01 6.18549846e-02 -1.18874736e-01 1.02643788e+00 8.41022670e-01 3.71351242e-01 -7.62326777e-01 4.67259169e-01 9.94491279e-01 -7.68319428e-01 9.64247957e-02 -4.50620204e-01 2.28776291e-01 -9.25297081e-01 7.89782465e-01 4.55597073e-01 -7.59563506e-01 -2.41352797e-01 -1.14710331e+00 -4.09502357e-01 -1.67828143e-01 -1.75308034e-01 6.95341408e-01 2.10195348e-01 -1.14156735e+00 6.41032517e-01 -7.19762027e-01 -4.35328394e-01 1.18556105e-01 3.66173655e-01 -8.72698009e-01 -6.02726460e-01 -5.54655850e-01 8.68487537e-01 -1.54643089e-01 -1.78074792e-01 -9.07440186e-01 -7.44296551e-01 -1.22387612e+00 -4.14324373e-01 1.33562505e-01 -6.63979948e-01 8.79223168e-01 -7.40226090e-01 -1.17100418e+00 1.23384321e+00 -8.34580585e-02 -3.06246251e-01 5.20423651e-01 -2.11079910e-01 2.46329885e-02 4.92576748e-01 3.92750263e-01 8.03915679e-01 8.04599285e-01 -1.74372482e+00 -4.30496931e-01 -4.53620762e-01 1.86156258e-02 2.25897491e-01 4.65987682e-01 -3.26564223e-01 -7.18643486e-01 -1.61263123e-01 8.30078602e-01 -1.11180723e+00 -1.20208859e-02 2.96239644e-01 -4.80122566e-01 -1.32382056e-02 7.26171672e-01 -1.82139039e-01 2.61404123e-02 -2.15593410e+00 1.11961514e-01 5.87955773e-01 -7.57101923e-02 -3.67053896e-01 -3.79496932e-01 5.59534848e-01 -2.12004762e-02 -8.66504833e-02 -2.31908560e-01 -7.17877626e-01 2.00573564e-01 4.90809172e-01 -1.00212343e-01 1.08257842e+00 2.06217289e-01 6.45150185e-01 -8.09423268e-01 -2.15701297e-01 5.76190829e-01 9.03299272e-01 -3.79736871e-01 9.37280580e-02 -6.42411411e-02 3.00682783e-01 -4.15390506e-02 1.38146925e+00 9.22439098e-01 5.05322628e-02 -1.73527718e-01 -4.25956279e-01 -2.05322608e-01 4.07951981e-01 -9.95005071e-01 2.27977252e+00 -5.32499194e-01 6.44101262e-01 1.18386246e-01 -5.59533954e-01 1.06120312e+00 -2.23801851e-01 7.31804848e-01 -1.02611256e+00 -4.55988906e-02 5.06302595e-01 -4.63076264e-01 3.75491828e-02 3.90613467e-01 9.42887440e-02 -9.26108658e-02 2.71026403e-01 1.37525322e-02 -5.64471364e-01 -3.31626892e-01 -1.70655921e-01 1.38066924e+00 4.46830362e-01 1.87482033e-02 -1.54420257e-01 6.02308698e-02 1.88410237e-01 3.95173162e-01 7.03776836e-01 2.70294547e-01 1.11904871e+00 2.51031250e-01 -9.62063313e-01 -1.10727108e+00 -1.24033260e+00 -3.98521572e-01 6.16571367e-01 5.49045861e-01 -4.43481594e-01 -1.68479487e-01 -4.23900723e-01 6.51872694e-01 1.48397252e-01 -7.08176315e-01 4.30389971e-01 -5.08198023e-01 -1.44898757e-01 3.62331510e-01 3.67970109e-01 4.79244441e-01 -7.13758767e-01 -9.43724692e-01 -6.03056364e-02 2.08456591e-01 -1.40138066e+00 7.41679892e-02 4.46120590e-01 -6.71379864e-01 -1.40586913e+00 -5.49365580e-01 -7.42962539e-01 6.85317338e-01 6.94782078e-01 1.42453384e+00 5.82021065e-02 -4.40846950e-01 8.64258230e-01 -4.68235731e-01 -1.29766598e-01 7.78266042e-02 4.57994686e-03 -4.47628833e-02 -3.01042110e-01 1.62185505e-01 -6.38757944e-01 -8.14344347e-01 5.29336452e-01 -5.93578935e-01 -8.28873590e-02 6.83214009e-01 4.72526044e-01 1.12974083e+00 -4.62429374e-01 -4.71086115e-01 -4.57608372e-01 -8.51411447e-02 -3.75502348e-01 -7.44363785e-01 1.44159300e-02 -4.40089732e-01 1.75960306e-02 1.72540918e-01 1.23960406e-01 -3.09596628e-01 6.75172985e-01 -1.10855140e-01 -6.60746276e-01 -1.77309409e-01 2.30218872e-01 2.77494993e-02 -8.91592026e-01 6.14796996e-01 1.02434672e-01 4.98092957e-02 -5.57052076e-01 2.49545649e-01 1.57869413e-01 5.21534503e-01 -7.59433568e-01 8.28385055e-01 1.07755899e+00 5.20864964e-01 -8.44021797e-01 -5.11273146e-01 -7.91411698e-01 -8.98090363e-01 -4.84613627e-02 6.24037266e-01 -1.10310698e+00 -7.64685631e-01 2.46015072e-01 -1.35123885e+00 -3.80462795e-01 -9.86133292e-02 2.71733046e-01 -7.28842199e-01 3.81740063e-01 -2.43985549e-01 -3.33835155e-01 -1.74885318e-01 -1.33121037e+00 1.97901738e+00 -1.33083209e-01 1.49101958e-01 -7.55770624e-01 3.69579881e-01 2.58667052e-01 1.34589851e-01 8.60342681e-01 4.63902384e-01 -1.12220712e-01 -1.02088964e+00 -4.11989450e-01 -3.91205937e-01 4.50213440e-02 -1.18583880e-01 6.96317526e-03 -9.91185963e-01 -2.81532496e-01 -3.83215427e-01 -3.97151470e-01 1.13198876e+00 7.03873858e-02 7.59731948e-01 1.35919377e-01 -3.88300747e-01 1.37154043e+00 1.65819800e+00 -2.49330625e-01 6.77096367e-01 9.35057342e-01 8.97136867e-01 3.70486408e-01 6.00299060e-01 3.10788244e-01 5.14476717e-01 6.82072937e-01 1.10164964e+00 -3.23259652e-01 -2.99105998e-02 -1.30979016e-01 2.27972314e-01 2.86475420e-01 -2.05554113e-01 -1.68224592e-02 -1.28420544e+00 4.23257262e-01 -1.60416889e+00 -3.57534409e-01 -1.17688067e-01 2.22542357e+00 2.54229277e-01 -2.59590950e-02 -2.72050768e-01 -2.05711231e-01 1.33509815e-01 2.58417070e-01 -5.84979355e-01 -3.54628175e-01 -5.26764631e-01 6.86046779e-01 1.12149990e+00 4.91761416e-01 -1.13226688e+00 8.50477397e-01 6.85057688e+00 1.53758034e-01 -1.11797559e+00 -1.65237308e-01 -5.97806007e-04 3.86289060e-02 -5.65133035e-01 1.32955357e-01 -5.31689763e-01 -1.00857407e-01 4.27220255e-01 5.48938215e-01 4.57486480e-01 9.49814975e-01 -3.44430089e-01 -4.10261750e-01 -1.38864934e+00 1.38826716e+00 4.81509209e-01 -1.37639296e+00 -1.82486530e-02 1.49037078e-01 8.82058620e-01 9.23658371e-01 3.89267989e-05 -1.01796068e-01 -1.07715810e-02 -1.12654126e+00 5.99350154e-01 3.91575366e-01 9.18638289e-01 -7.06888616e-01 6.33977592e-01 -3.97880785e-02 -1.05698383e+00 3.18904817e-01 -6.56969130e-01 9.52454507e-02 -1.14394486e-01 5.19002140e-01 -8.13446760e-01 6.48314655e-01 8.35417509e-01 1.05418670e+00 -5.96026301e-01 1.02451241e+00 -3.83792490e-01 -1.73005104e-01 -8.96577537e-01 4.00487781e-01 5.18849611e-01 -1.48285940e-01 4.32284117e-01 1.05931103e+00 4.72882867e-01 -4.09374714e-01 1.50465578e-01 8.25956106e-01 -1.32772744e-01 -1.49034202e-01 -1.09938157e+00 5.57335913e-01 5.53333998e-01 1.25855744e+00 -6.75329983e-01 1.53510660e-01 -4.01460797e-01 1.15998662e+00 2.31231973e-01 9.75068584e-02 -5.12406886e-01 -2.04260528e-01 6.90375030e-01 3.14834088e-01 3.73732179e-01 -5.95658362e-01 2.35953256e-02 -1.03163159e+00 1.98775351e-01 -7.39525616e-01 4.85825948e-02 -1.06380880e+00 -1.13839006e+00 4.09102917e-01 -1.74534380e-01 -1.30300617e+00 -1.48056105e-01 -1.02780998e+00 -4.57402706e-01 7.39261806e-01 -1.98353684e+00 -1.52724421e+00 -7.60960639e-01 8.37988198e-01 -2.31816527e-02 1.46166429e-01 1.02362931e+00 2.94986889e-02 1.30696580e-01 1.54947236e-01 1.86780795e-01 9.47231054e-02 9.15529251e-01 -1.22571814e+00 6.74780786e-01 5.50803423e-01 3.60119492e-01 6.65708005e-01 2.98512101e-01 -4.81329679e-01 -2.32925534e+00 -8.24880660e-01 3.02257180e-01 -6.16613030e-01 2.93010205e-01 -4.56567377e-01 -4.23037201e-01 8.00857365e-01 -4.30950336e-02 5.26719749e-01 3.31547737e-01 1.10552222e-01 -9.04129803e-01 -2.92000443e-01 -1.05423963e+00 2.51379963e-02 1.18759835e+00 -7.03766644e-01 -5.69819868e-01 5.90950191e-01 4.98744518e-01 -9.24936533e-01 -1.05291939e+00 6.35692656e-01 9.50083256e-01 -1.41644335e+00 1.50793886e+00 7.57901594e-02 3.05742025e-01 -3.13685864e-01 -6.18625224e-01 -1.23808122e+00 -8.07693005e-02 -4.34515744e-01 3.43106270e-01 4.36063439e-01 1.27267614e-01 -6.36948824e-01 8.48110199e-01 2.34417081e-01 -5.13996124e-01 -5.77091157e-01 -1.25469828e+00 -8.87420893e-01 -1.64574087e-01 -5.15498102e-01 4.96991634e-01 7.73754120e-01 -5.78103006e-01 -5.35245053e-02 -1.03245914e-01 4.48086739e-01 1.00935149e+00 5.75715423e-01 1.16458285e+00 -1.24030292e+00 4.07621451e-02 -2.06194714e-01 -8.37872505e-01 -1.05219936e+00 3.15844268e-01 -9.38237190e-01 1.96140945e-01 -1.75831187e+00 -1.75087050e-01 -7.53642857e-01 -1.00768559e-01 7.35709488e-01 6.33674800e-01 6.69707537e-01 3.74600552e-02 4.23991442e-01 -7.40572155e-01 3.24267894e-01 1.03150976e+00 -2.11848140e-01 6.28373995e-02 -5.32530844e-01 -1.50589362e-01 7.71139383e-01 4.21995550e-01 -3.60537529e-01 1.52627692e-01 -8.91058505e-01 6.74201548e-01 -1.52533039e-01 7.67611325e-01 -1.32756901e+00 1.72016814e-01 7.85825476e-02 7.01385975e-01 -9.21683133e-01 7.63571560e-01 -1.07865226e+00 3.01659018e-01 2.73363799e-01 2.84504056e-01 1.42358854e-01 1.37518957e-01 5.16111732e-01 -2.59282738e-02 2.00175166e-01 5.48907280e-01 -3.16491872e-01 -9.28482234e-01 3.80338192e-01 2.99162149e-01 -2.12201074e-01 7.37364054e-01 -3.97543997e-01 -4.69596624e-01 -2.28898585e-01 -1.66942477e-01 2.22411286e-02 1.37413990e+00 3.81902695e-01 1.06327760e+00 -1.44921303e+00 -5.24697542e-01 5.99369526e-01 5.22461474e-01 4.91307408e-01 -3.36274028e-01 7.66248465e-01 -1.35553873e+00 2.32820332e-01 -4.34538841e-01 -1.25999081e+00 -9.42599833e-01 1.72059894e-01 4.66845989e-01 3.20654720e-01 -8.62454355e-01 6.26436889e-01 -1.23608232e-01 -7.77567208e-01 1.78513095e-01 -5.90451062e-01 6.36686265e-01 -1.42356187e-01 8.56094584e-02 7.69197717e-02 5.22995472e-01 -8.82884324e-01 -9.51992452e-01 1.25716531e+00 4.10892367e-01 5.30459397e-02 1.75670767e+00 2.02566102e-01 -3.84583473e-01 3.37561399e-01 1.58727551e+00 1.86739966e-01 -1.30083549e+00 -2.09822372e-01 -3.22982401e-01 -7.15173483e-01 4.85522933e-02 -6.30434871e-01 -8.45071971e-01 6.53819561e-01 5.88432729e-01 -1.50895178e-01 7.22892761e-01 1.99731871e-01 7.40969002e-01 8.93404245e-01 9.06673431e-01 -7.01008976e-01 9.73483697e-02 7.45171607e-01 1.09273243e+00 -1.47368491e+00 4.00872141e-01 -2.27709696e-01 -1.12064324e-01 1.40196455e+00 1.49419025e-01 -7.28235006e-01 4.75742340e-01 2.88601637e-01 1.08734787e-01 -6.54659331e-01 -3.25143747e-02 -2.29602262e-01 4.89274025e-01 7.99279511e-01 4.51242439e-02 -2.25782897e-02 4.15092587e-01 -2.23587275e-01 -2.09879518e-01 -5.35396636e-01 1.11682795e-01 1.19745409e+00 -4.20898706e-01 -1.09508717e+00 -5.76391578e-01 1.05157971e-01 1.65483654e-02 5.60622700e-02 -6.44587755e-01 1.28118563e+00 2.26110831e-01 4.45812225e-01 3.27803075e-01 -5.58103204e-01 5.53993762e-01 -4.59180981e-01 8.67585003e-01 -5.62196076e-01 -3.64251524e-01 1.30546376e-01 3.54095064e-02 -1.34498155e+00 -7.33317614e-01 -6.26857042e-01 -1.15734625e+00 -2.02259853e-01 1.82322502e-01 -3.63187164e-01 1.14880598e+00 6.33590162e-01 5.26350498e-01 -1.93424582e-01 6.77258968e-01 -1.57252944e+00 -8.89748335e-02 -5.64939559e-01 -5.01676738e-01 5.09614170e-01 5.48626006e-01 -9.14920330e-01 -5.27771413e-01 -5.22987902e-01]	[7.8477630615234375, -2.7618274688720703]
22e93af1-cd5c-40dc-9984-d6ff05a174b2	adversarial-text-normalization	2206.04137	null	https://arxiv.org/abs/2206.04137v1	https://arxiv.org/pdf/2206.04137v1.pdf	Adversarial Text Normalization	Text-based adversarial attacks are becoming more commonplace and accessible to general internet users. As these attacks proliferate, the need to address the gap in model robustness becomes imminent. While retraining on adversarial data may increase performance, there remains an additional class of character-level attacks on which these models falter. Additionally, the process to retrain a model is time and resource intensive, creating a need for a lightweight, reusable defense. In this work, we propose the Adversarial Text Normalizer, a novel method that restores baseline performance on attacked content with low computational overhead. We evaluate the efficacy of the normalizer on two problem areas prone to adversarial attacks, i.e. Hate Speech and Natural Language Inference. We find that text normalization provides a task-agnostic defense against character-level attacks that can be implemented supplementary to adversarial retraining solutions, which are more suited for semantic alterations.	['Ivan Evtimov', 'Maya Pavlova', 'Joanna Bitton']	2022-06-08	null	https://aclanthology.org/2022.naacl-industry.30	https://aclanthology.org/2022.naacl-industry.30.pdf	naacl-acl-2022-7	['adversarial-text']	['adversarial']	[ 5.15051305e-01 -5.23862094e-02 9.23471004e-02 -1.69198498e-01 -7.95525789e-01 -1.22801399e+00 7.69031823e-01 3.04634243e-01 -5.42734146e-01 4.71338630e-01 3.15409064e-01 -6.32030368e-01 1.58499062e-01 -7.59992719e-01 -7.23113954e-01 -4.47649598e-01 2.59808898e-01 7.56803751e-02 2.19808966e-01 -6.73090279e-01 3.05270165e-01 8.10253799e-01 -1.18138194e+00 3.49574000e-01 8.66166353e-01 3.72194082e-01 -4.62089092e-01 7.97739744e-01 -1.11657262e-01 6.60503864e-01 -1.07660270e+00 -1.00250065e+00 4.46300238e-01 -1.59449220e-01 -8.83897066e-01 -2.99017102e-01 8.66030335e-01 -3.41685057e-01 -6.48975611e-01 1.34156215e+00 7.29770899e-01 1.69914022e-01 4.04664546e-01 -1.39631999e+00 -6.96963131e-01 6.41071081e-01 -3.60357225e-01 4.83660936e-01 3.35559994e-01 4.32171047e-01 6.08444870e-01 -4.80025679e-01 5.11922956e-01 1.52905107e+00 7.79483199e-01 8.84769320e-01 -1.25427079e+00 -7.30715454e-01 2.11085603e-01 -3.33762765e-02 -9.62892056e-01 -5.57993710e-01 5.73420227e-01 -2.43494511e-01 7.14888334e-01 6.29708529e-01 -7.34635023e-03 1.73222697e+00 2.71414608e-01 4.00019825e-01 8.82169962e-01 -5.20000994e-01 2.16802418e-01 1.81059077e-01 1.71593186e-02 2.78698385e-01 4.14683759e-01 -2.74507310e-02 -3.51910144e-01 -5.77441514e-01 2.12834761e-01 -5.87926805e-02 -1.38149872e-01 -8.23146701e-02 -6.20730340e-01 8.99028420e-01 1.11022063e-01 3.10551077e-01 -1.36193052e-01 1.32284299e-01 8.33877981e-01 4.24553365e-01 6.13008678e-01 9.09032762e-01 -4.44262594e-01 -2.53904969e-01 -8.04155767e-01 4.26431477e-01 8.84998858e-01 6.13433480e-01 4.08163041e-01 3.05424482e-01 -1.31152347e-01 7.51493335e-01 6.25339523e-02 6.66428924e-01 4.81175810e-01 -5.61533511e-01 4.93407756e-01 4.27198827e-01 -3.04184735e-01 -1.21213126e+00 -1.66728303e-01 -4.52905267e-01 -5.04436016e-01 3.86935532e-01 5.73221743e-01 -1.30227551e-01 -1.01750791e+00 1.84208345e+00 2.49205902e-01 -1.02391489e-01 2.15964243e-02 3.70833218e-01 1.66153178e-01 3.26870859e-01 6.01541281e-01 3.34838480e-01 1.25781238e+00 -5.89887738e-01 -6.34360850e-01 -4.59657609e-01 6.23035789e-01 -1.17849100e+00 1.44437587e+00 2.39691034e-01 -9.85413432e-01 -2.47055311e-02 -1.09402382e+00 -4.46870476e-02 -9.85089660e-01 -8.53301525e-01 5.16205549e-01 1.57105803e+00 -8.04442167e-01 8.24155629e-01 -7.57994294e-01 -4.96820271e-01 3.83105606e-01 3.08460206e-01 -4.67946202e-01 9.04547572e-02 -1.47650504e+00 1.29942334e+00 2.28213534e-01 -2.46186167e-01 -6.51734710e-01 -9.04579461e-01 -7.27251172e-01 7.19790719e-03 2.46986121e-01 -2.88787693e-01 1.20752954e+00 -1.09589243e+00 -1.38872027e+00 9.28966939e-01 2.42660359e-01 -6.38599217e-01 8.60288024e-01 -3.41052055e-01 -7.44235814e-01 -2.99483556e-02 -1.31737113e-01 2.31204197e-01 1.18262839e+00 -1.11908817e+00 -1.37407631e-01 -1.77309066e-01 2.43477270e-01 -1.18974999e-01 -1.08221090e+00 5.02145231e-01 -1.87657446e-01 -1.13736725e+00 -5.40194333e-01 -9.90774095e-01 -2.21726850e-01 -2.66194791e-02 -5.27390480e-01 3.14381391e-01 1.38231885e+00 -9.17685390e-01 1.42548931e+00 -2.12442517e+00 -6.29177094e-02 3.07828307e-01 1.74039602e-01 8.94119680e-01 -2.95370489e-01 4.62462097e-01 -3.70695919e-01 8.06909800e-01 -4.59797382e-01 -2.34758049e-01 1.25842690e-01 1.11364119e-01 -6.14815712e-01 4.91128057e-01 3.06866199e-01 6.95814192e-01 -6.82405770e-01 -2.14400291e-01 6.12249896e-02 4.76355344e-01 -9.06040668e-01 3.51858810e-02 -2.39200816e-01 9.42820013e-02 -2.92260617e-01 6.12707734e-01 7.44383574e-01 2.76511610e-01 -1.03489384e-01 2.53985059e-02 2.17144415e-01 1.58388659e-01 -9.40550148e-01 1.29290235e+00 -3.62585396e-01 6.79230213e-01 1.79578245e-01 -5.45846045e-01 7.06729412e-01 5.06990738e-02 5.82800321e-02 -5.12439609e-01 2.24099457e-01 2.13555619e-03 5.37627377e-03 -4.99955237e-01 6.86673462e-01 -1.01178147e-01 -4.14779425e-01 5.36501527e-01 -8.84478241e-02 -1.37067035e-01 6.20944463e-02 4.16063696e-01 1.53594196e+00 -1.24330588e-01 1.15581758e-01 -2.11747020e-01 5.68455577e-01 -1.45189822e-01 3.03081036e-01 8.06722820e-01 -3.30710024e-01 3.84457260e-01 3.38142216e-01 -4.74021345e-01 -1.26551652e+00 -1.11650646e+00 2.87527554e-02 1.34890842e+00 -2.36249819e-01 -5.37613988e-01 -1.30981636e+00 -8.80515456e-01 6.47065789e-02 9.25588787e-01 -6.24920487e-01 -8.33910525e-01 -8.31465244e-01 -8.37372661e-01 1.27322578e+00 3.11077386e-01 4.17699516e-01 -8.66070926e-01 -1.81674048e-01 1.30588546e-01 -2.33242705e-01 -1.19553304e+00 -6.53336406e-01 5.05154692e-02 -5.90014994e-01 -9.31989491e-01 -3.62253219e-01 -3.44316423e-01 6.04519844e-01 3.76313627e-02 1.05258811e+00 3.09407175e-01 -4.60373759e-01 5.51581442e-01 -4.88042265e-01 -8.00953507e-01 -1.19985032e+00 5.36410093e-01 1.23497240e-01 -6.82637244e-02 3.57646972e-01 -5.86043596e-01 -2.87800491e-01 2.62116998e-01 -1.47329819e+00 -5.05990386e-01 2.89144069e-01 4.52416718e-01 -4.79299994e-03 5.48841693e-02 6.55309379e-01 -1.20297253e+00 9.89634454e-01 -4.70649153e-01 -3.20929557e-01 1.29701942e-01 -5.08552432e-01 5.45653477e-02 1.09942091e+00 -7.28998244e-01 -1.06015718e+00 -1.35675758e-01 -4.57927644e-01 -2.67077059e-01 -2.50098556e-01 2.07856029e-01 -5.06164134e-01 -4.70740497e-01 1.29008448e+00 -2.38228202e-01 6.47349954e-02 -6.13846958e-01 5.96673369e-01 5.56108952e-01 6.57838583e-01 -6.45264328e-01 1.63686907e+00 3.86181533e-01 -2.45846406e-01 -9.53048646e-01 -6.28888130e-01 -6.47470802e-02 -3.39771628e-01 -5.01923785e-02 7.45753527e-01 -4.62993085e-01 -3.40807974e-01 6.25360131e-01 -1.10654104e+00 -2.74758518e-01 -2.28280872e-01 -9.90230814e-02 -2.26765126e-01 8.12439442e-01 -5.66612601e-01 -3.60430002e-01 -4.92751926e-01 -9.43747044e-01 5.42998552e-01 3.54094319e-02 -5.11141717e-01 -1.01710236e+00 5.96973896e-02 5.49866021e-01 8.05678785e-01 5.19264281e-01 1.09850037e+00 -1.10185039e+00 -2.61708647e-01 -5.75814486e-01 1.77406836e-02 6.36651754e-01 1.14095800e-01 2.16471836e-01 -1.25683463e+00 -5.87957978e-01 5.78533038e-02 -2.25410700e-01 4.31564480e-01 -3.98064822e-01 1.19252264e+00 -6.68374777e-01 4.34324928e-02 5.46343803e-01 1.18531382e+00 4.19015065e-02 9.36824262e-01 5.86198866e-01 7.63459623e-01 5.08879244e-01 1.22349046e-01 1.95497259e-01 -1.58358261e-01 5.47595203e-01 5.87098956e-01 -2.87472516e-01 -5.58565445e-02 -3.42289031e-01 4.11600471e-01 3.00803095e-01 1.50793046e-01 -4.59844679e-01 -1.09387159e+00 2.16108307e-01 -1.41948199e+00 -1.19173741e+00 1.49797633e-01 2.18333054e+00 9.64448810e-01 4.37408686e-01 9.28146318e-02 3.13761383e-01 7.88329899e-01 1.72334462e-01 -5.98958492e-01 -8.56152415e-01 -1.67329088e-01 4.65174019e-01 8.16746294e-01 4.15720701e-01 -1.20354915e+00 1.38975036e+00 6.85646105e+00 8.09300840e-01 -1.13400578e+00 1.07852742e-01 4.27195638e-01 -1.83070555e-01 -3.04094225e-01 -1.46701142e-01 -5.95100224e-01 5.22973359e-01 1.34469962e+00 -3.27708602e-01 6.26678228e-01 9.45792437e-01 1.40521795e-01 4.92268384e-01 -9.10216868e-01 5.56237817e-01 2.48093158e-01 -1.17459393e+00 3.84123296e-01 8.25421959e-02 4.45850909e-01 -1.48964971e-01 2.67830044e-01 3.78181309e-01 5.65086961e-01 -1.05295670e+00 6.85886264e-01 -1.61628460e-03 5.97148776e-01 -9.72016931e-01 5.68760812e-01 7.76232183e-02 -6.51620626e-01 -3.23774703e-02 -2.37672880e-01 1.44567043e-01 -3.91507484e-02 1.99408993e-01 -5.60594738e-01 1.00128651e-01 6.19522393e-01 4.66101095e-02 -1.01219988e+00 7.07871139e-01 -1.72771066e-01 6.43763244e-01 -6.64044023e-02 2.07308933e-01 1.37361288e-01 2.36333832e-01 7.00949073e-01 1.46686077e+00 -1.46902695e-01 -2.73035616e-01 6.83308989e-02 4.77112502e-01 -3.16489011e-01 1.05170496e-01 -8.55152130e-01 -3.76837790e-01 5.30532837e-01 1.09823823e+00 -7.40789831e-01 3.64509150e-02 -2.71924794e-01 1.26141000e+00 3.09233159e-01 2.26263344e-01 -1.06178463e+00 -5.31825423e-01 1.09542525e+00 2.48168141e-01 -2.50889033e-01 -2.34381661e-01 -2.62478113e-01 -1.15961277e+00 5.40120061e-03 -1.76752222e+00 4.57771987e-01 -2.41438851e-01 -1.39159989e+00 4.84133601e-01 -1.31875753e-01 -8.30325484e-01 -4.83670719e-02 -5.39015353e-01 -6.29785538e-01 7.55738437e-01 -1.20511854e+00 -1.06844413e+00 -2.81333420e-02 7.74571359e-01 3.73214155e-01 -2.05422819e-01 9.47383523e-01 5.52793622e-01 -5.71591437e-01 1.24520588e+00 -8.49115779e-04 4.23434377e-01 9.43596900e-01 -1.04205096e+00 1.06461537e+00 1.34076202e+00 -8.75842720e-02 9.03636932e-01 1.01306641e+00 -6.41184390e-01 -1.24864578e+00 -1.24556661e+00 6.72841966e-01 -7.42210031e-01 9.29467261e-01 -7.92199671e-01 -1.20389831e+00 6.56638026e-01 7.37569481e-02 -3.05799931e-01 8.38645875e-01 5.39265340e-03 -9.18128431e-01 1.43876702e-01 -1.52107584e+00 1.09250069e+00 9.55927551e-01 -9.73051310e-01 -4.92047220e-01 4.95981008e-01 9.35281932e-01 -3.39434922e-01 -6.52541399e-01 1.57272629e-02 2.09210470e-01 -6.61854148e-01 1.17142963e+00 -1.00899947e+00 1.90245286e-01 -9.04736817e-02 -1.19486533e-01 -1.21789718e+00 -1.93785042e-01 -1.17982125e+00 2.64293909e-01 1.45921803e+00 5.14778435e-01 -9.54089940e-01 8.21188450e-01 1.12792361e+00 2.85362545e-02 -7.48388097e-03 -8.34703743e-01 -9.51680660e-01 5.77893555e-01 -3.83224338e-01 6.42485380e-01 1.38452744e+00 -2.86143154e-01 6.04712181e-02 -3.32410097e-01 3.00589353e-01 4.77904439e-01 -8.16563189e-01 8.64010632e-01 -1.07564294e+00 -1.96351558e-01 -5.02869606e-01 -6.22177780e-01 -2.05170169e-01 3.19459826e-01 -8.84552181e-01 -2.99643636e-01 -8.67754161e-01 -1.45942792e-01 -1.76665619e-01 -1.57947242e-01 6.73921227e-01 -2.91875273e-01 2.90948868e-01 5.15039265e-01 4.97721210e-02 -9.57865641e-02 2.85534620e-01 7.29530632e-01 -1.91182598e-01 7.55479261e-02 -5.58225587e-02 -8.69564176e-01 9.43244636e-01 1.10500681e+00 -8.58453333e-01 -3.93325448e-01 -3.13875884e-01 2.88198203e-01 -6.65476382e-01 2.63533175e-01 -1.06763661e+00 7.20117018e-02 -9.23193693e-02 1.53031603e-01 6.93624690e-02 3.17670181e-02 -8.50980818e-01 -1.58942118e-01 4.60648954e-01 -5.11973381e-01 3.21847796e-01 6.61167741e-01 5.30008137e-01 1.93846330e-01 -3.29500765e-01 1.22550750e+00 -1.28115853e-02 -2.90009350e-01 2.08714724e-01 -6.33266449e-01 3.97926867e-01 1.04708004e+00 -1.88013777e-01 -6.72433794e-01 -3.57732058e-01 -5.10237038e-01 -1.59549087e-01 7.45673299e-01 8.31788242e-01 2.53213763e-01 -8.94546807e-01 -6.55338407e-01 1.21756420e-01 -9.94142368e-02 -6.83383703e-01 1.52341306e-01 3.34995091e-02 -5.73687375e-01 -1.50360691e-03 -4.38383847e-01 5.37427068e-02 -1.52243578e+00 9.20135021e-01 4.88155663e-01 -2.83976167e-01 -4.73427504e-01 6.79129601e-01 -1.82631910e-02 -5.76558352e-01 2.85703897e-01 1.70912400e-01 1.14004001e-01 -3.55421053e-03 7.32753277e-01 4.70377237e-01 3.42598498e-01 -5.29901564e-01 -2.95102686e-01 1.12092942e-01 -5.56933403e-01 2.83899754e-02 1.09741068e+00 1.68219477e-01 -2.35065728e-01 -1.48897842e-01 1.15293717e+00 3.80750984e-01 -9.31426942e-01 -1.39092326e-01 2.02651903e-01 -5.40658951e-01 -8.36850107e-02 -9.07593727e-01 -8.25338364e-01 7.17786014e-01 6.21760607e-01 5.96385479e-01 1.01961017e+00 -4.42098677e-01 8.67757142e-01 3.85503858e-01 3.10112182e-02 -9.91703093e-01 8.05975869e-02 5.55365682e-01 8.33906889e-01 -9.78407860e-01 2.18178462e-02 -4.72887725e-01 -3.82055461e-01 9.61265147e-01 6.14517748e-01 9.96157303e-02 3.95771980e-01 4.70589966e-01 2.66275555e-01 9.94708762e-02 -3.27198058e-01 2.28092253e-01 2.26394963e-02 8.55307460e-01 2.73356676e-01 -1.01686686e-01 -1.32577911e-01 8.40958655e-02 -4.33840483e-01 -6.58555686e-01 7.27938056e-01 1.11086595e+00 -2.15142265e-01 -1.53079128e+00 -7.60597944e-01 1.65567607e-01 -9.52092946e-01 -4.00403738e-01 -8.34203184e-01 8.26561153e-01 -2.12293431e-01 1.20725811e+00 -2.46081740e-01 -3.36907029e-01 5.29116869e-01 4.06488985e-01 1.02211088e-01 -5.72705805e-01 -1.21177924e+00 -4.11380678e-01 2.88859159e-01 -6.50222242e-01 1.71510324e-01 -5.55631578e-01 -9.01768923e-01 -1.03279686e+00 -2.03271136e-01 -1.83948502e-01 8.25116098e-01 8.05287600e-01 4.85964328e-01 4.13326412e-01 4.91863102e-01 -5.58977544e-01 -9.05317187e-01 -5.91062665e-01 -1.31586149e-01 8.40472162e-01 1.96398169e-01 -2.14780495e-01 -5.89066029e-01 1.68228269e-01]	[6.036111354827881, 8.091459274291992]
a964d5b9-d4ce-4794-93cb-03c02ed249ec	annobert-effectively-representing-multiple	2212.10405	null	https://arxiv.org/abs/2212.10405v2	https://arxiv.org/pdf/2212.10405v2.pdf	AnnoBERT: Effectively Representing Multiple Annotators' Label Choices to Improve Hate Speech Detection	Supervised approaches generally rely on majority-based labels. However, it is hard to achieve high agreement among annotators in subjective tasks such as hate speech detection. Existing neural network models principally regard labels as categorical variables, while ignoring the semantic information in diverse label texts. In this paper, we propose AnnoBERT, a first-of-its-kind architecture integrating annotator characteristics and label text with a transformer-based model to detect hate speech, with unique representations based on each annotator's characteristics via Collaborative Topic Regression (CTR) and integrate label text to enrich textual representations. During training, the model associates annotators with their label choices given a piece of text; during evaluation, when label information is not available, the model predicts the aggregated label given by the participating annotators by utilising the learnt association. The proposed approach displayed an advantage in detecting hate speech, especially in the minority class and edge cases with annotator disagreement. Improvement in the overall performance is the largest when the dataset is more label-imbalanced, suggesting its practical value in identifying real-world hate speech, as the volume of hate speech in-the-wild is extremely small on social media, when compared with normal (non-hate) speech. Through ablation studies, we show the relative contributions of annotator embeddings and label text to the model performance, and tested a range of alternative annotator embeddings and label text combinations.	['Nishanth Sastry', 'Arkaitz Zubiaga', 'Aiqi Jiang', 'Vibhor Agarwal', 'Wenjie Yin']	2022-12-20	null	null	null	null	['hate-speech-detection']	['natural-language-processing']	[-1.19650103e-01 2.86944181e-01 -6.11554384e-02 -2.52204090e-01 -5.19752502e-01 -7.43363142e-01 4.55984682e-01 5.35894632e-01 -5.31219959e-01 4.42354500e-01 3.55831206e-01 1.01325206e-01 8.50710943e-02 -2.76245594e-01 -4.66077439e-02 -8.57074678e-01 1.79748803e-01 6.23806119e-01 -1.29929110e-02 -8.95108655e-02 -2.32021324e-02 1.17786102e-01 -1.45834005e+00 2.59277076e-01 9.72961664e-01 8.39277625e-01 -2.23174781e-01 4.12124664e-01 -1.98669121e-01 1.12411892e+00 -1.17906642e+00 -7.63630688e-01 -1.98710516e-01 -3.47720891e-01 -6.58173263e-01 1.87130866e-03 5.15255690e-01 -1.99966848e-01 -1.88142315e-01 9.88489926e-01 8.40455055e-01 -3.14308070e-02 9.53455746e-01 -1.34448826e+00 -9.57965374e-01 7.95242786e-01 -4.38486278e-01 1.09001532e-01 1.16419964e-01 2.89496388e-02 1.06766510e+00 -1.00057840e+00 5.69451451e-01 1.03839040e+00 9.77645516e-01 6.96251988e-01 -1.42310905e+00 -8.17068100e-01 6.34866860e-03 2.26094738e-01 -1.37772179e+00 -1.97943181e-01 1.07571745e+00 -9.59343612e-01 7.06657767e-01 2.06311658e-01 2.61936665e-01 1.57396162e+00 -4.19826984e-01 6.29189789e-01 1.11170852e+00 -3.34629953e-01 2.92085618e-01 7.38591254e-01 3.51877898e-01 2.39404172e-01 -2.82557271e-02 -3.99578959e-01 -7.42950559e-01 -6.32275462e-01 -3.58491451e-01 -2.27202084e-02 -2.33411580e-01 -2.86010951e-02 -7.74964988e-01 1.22905719e+00 2.78305203e-01 7.32546210e-01 -2.32777610e-01 -1.52998090e-01 8.34720016e-01 2.12483421e-01 1.24494588e+00 7.15647161e-01 -2.29997888e-01 -2.51649860e-02 -1.20706916e+00 2.16070190e-01 8.59494686e-01 2.98839003e-01 6.54707551e-01 -3.74235511e-02 -4.47162569e-01 1.39885020e+00 9.26496461e-02 5.20855010e-01 6.38805032e-01 -7.13208377e-01 4.36498135e-01 6.21569335e-01 6.85224682e-02 -1.24288738e+00 -5.69442391e-01 -3.76520187e-01 -6.22675598e-01 1.19127005e-01 4.72060114e-01 -5.30296266e-01 -7.05814481e-01 1.74084377e+00 3.46139967e-01 -2.31097817e-01 -2.81991094e-01 8.48934650e-01 7.67370760e-01 6.44435167e-01 4.73339140e-01 -3.60869795e-01 1.40891838e+00 -8.21490765e-01 -1.25632620e+00 -2.55229264e-01 1.15381551e+00 -7.42422283e-01 8.54756296e-01 3.90757680e-01 -5.41624188e-01 -2.77083606e-01 -6.25378489e-01 -1.23989992e-01 -7.83170760e-01 1.60291150e-01 -8.36529129e-04 9.20943856e-01 -9.04272377e-01 3.71932477e-01 -5.20835519e-02 -2.73201704e-01 4.93403554e-01 1.86862722e-01 -4.38565522e-01 1.58219218e-01 -1.52402425e+00 1.26515973e+00 2.75216222e-01 -7.62361160e-04 -7.89300442e-01 -7.12267637e-01 -7.45872736e-01 1.51999265e-01 3.07309926e-01 1.37764839e-02 1.11063373e+00 -1.05414975e+00 -1.03238583e+00 9.38066661e-01 -2.99606062e-02 -2.43354186e-01 3.48061740e-01 -1.93532422e-01 -4.04712290e-01 -1.24622598e-01 8.36064946e-03 5.72980940e-01 9.97668624e-01 -1.30581164e+00 -1.69670179e-01 -4.80164200e-01 -2.00976267e-01 8.54843929e-02 -1.10606563e+00 4.38010454e-01 4.98510510e-01 -6.84544981e-01 -4.87821370e-01 -1.01425409e+00 3.19619715e-01 -4.52030078e-02 -4.94768351e-01 -8.54066610e-01 1.31180489e+00 -8.91294181e-01 1.68086553e+00 -2.40038610e+00 1.37849063e-01 2.47709025e-02 6.48555160e-01 7.41700172e-01 1.07058644e-01 6.22119963e-01 -1.11847464e-02 3.74585867e-01 -2.41065264e-01 -9.08213794e-01 2.77761579e-01 -8.67450535e-02 -3.35529923e-01 6.60820484e-01 2.82727897e-01 5.26272655e-01 -8.03773582e-01 -5.54064929e-01 -3.70008536e-02 6.19489193e-01 -3.48507524e-01 5.78532159e-01 -4.05416526e-02 2.31913105e-01 -1.30835297e-02 4.70331311e-01 3.44634950e-01 4.26169597e-02 1.60990939e-01 -2.50315871e-02 -6.00110227e-03 2.30709821e-01 -7.78592408e-01 1.17423272e+00 -4.87665206e-01 1.07486784e+00 1.34481817e-01 -6.03677392e-01 1.27363551e+00 7.44898260e-01 1.34571850e-01 -3.63589495e-01 3.70521575e-01 4.05281067e-01 4.72962484e-02 -7.66828179e-01 3.86554390e-01 -9.39949974e-02 -1.29012197e-01 6.32143974e-01 1.72496244e-01 1.37138769e-01 1.01900682e-01 1.64862797e-01 1.13105595e+00 -4.21920925e-01 9.75663736e-02 -1.08503632e-01 3.38858098e-01 -2.02825055e-01 2.65462428e-01 4.68793601e-01 -4.95359153e-01 4.71237987e-01 9.29572523e-01 -5.69173872e-01 -1.20192945e+00 -5.05603731e-01 -2.74651825e-01 1.67477429e+00 -4.05301690e-01 -4.72605765e-01 -8.87791276e-01 -1.07671988e+00 -7.24718049e-02 8.89377475e-01 -1.02130532e+00 -1.75306603e-01 -3.03866804e-01 -7.02760994e-01 7.73311615e-01 2.34976903e-01 -1.47920549e-02 -1.23091495e+00 -3.91423881e-01 1.34202451e-01 -1.41119003e-01 -8.48698199e-01 -3.09047818e-01 6.45190299e-01 -1.07840799e-01 -8.38745415e-01 -8.67826998e-01 -6.18815720e-01 4.76306528e-01 -1.12657517e-01 7.52740324e-01 7.99377859e-02 -8.52518827e-02 -8.35957304e-02 -6.48785770e-01 -4.28169310e-01 -6.03719711e-01 2.73243666e-01 1.24168601e-02 2.89942175e-01 5.98609984e-01 -3.34642231e-01 -2.36677393e-01 2.84805983e-01 -9.23673630e-01 -3.56310725e-01 -6.49222136e-02 9.57951009e-01 -2.77448177e-01 -3.56701389e-02 6.63235247e-01 -1.21825027e+00 7.60053813e-01 -9.31242645e-01 3.31046879e-02 -5.86113967e-02 -4.37365085e-01 -2.19495282e-01 7.70082653e-01 -9.17359889e-01 -9.09310818e-01 -2.40722343e-01 -6.96279109e-03 -5.27339101e-01 -3.79524291e-01 3.22384685e-01 1.26994282e-01 3.63613576e-01 9.02328968e-01 -2.82737702e-01 2.36883555e-02 -6.65857553e-01 1.84896991e-01 1.13351834e+00 4.70509380e-02 -2.80376792e-01 7.49853551e-01 -3.24043222e-02 -5.97611487e-01 -7.65434742e-01 -1.19305563e+00 -6.75118983e-01 -5.80466807e-01 -3.40969682e-01 1.09682941e+00 -6.96040988e-01 -5.31856000e-01 7.80555725e-01 -1.52841902e+00 -2.31738031e-01 -9.17826965e-02 3.34983081e-01 1.02515303e-01 1.10815331e-01 -5.88494241e-01 -1.45660245e+00 -3.43082219e-01 -1.16396129e+00 1.08225894e+00 -5.65451123e-02 -7.77357101e-01 -1.12467754e+00 4.25929517e-01 5.13905048e-01 6.38197541e-01 1.52053982e-01 1.13826847e+00 -1.69124448e+00 4.64687794e-01 -3.34629893e-01 -2.27885708e-01 6.01146817e-01 -9.49892327e-02 1.03346594e-01 -1.57915199e+00 -1.63717106e-01 -1.52575329e-01 -9.57795262e-01 5.99204957e-01 -1.34434342e-01 9.92930889e-01 -4.39251870e-01 -1.47798091e-01 -5.50837591e-02 1.07961154e+00 -3.33415829e-02 2.90213823e-01 1.64043039e-01 9.87209022e-01 1.13133264e+00 1.32708013e-01 5.04560769e-01 9.38599184e-02 8.71279895e-01 4.85920250e-01 -5.42768128e-02 -1.61258683e-01 -1.79825380e-01 4.52699125e-01 9.90523696e-01 2.90933192e-01 -4.96366411e-01 -1.15045738e+00 5.05137742e-01 -1.59904361e+00 -9.57862079e-01 -2.40682498e-01 1.95437527e+00 1.01464462e+00 -1.25185475e-01 4.43604887e-01 3.58001947e-01 1.12880611e+00 4.99588817e-01 -2.34331653e-01 -7.28033900e-01 -4.44603786e-02 -1.57886356e-01 1.62935033e-01 3.26299489e-01 -1.27966857e+00 6.56243980e-01 5.38711262e+00 9.99110043e-01 -1.06648147e+00 7.42828250e-01 7.96142995e-01 -2.74903923e-01 -2.16971025e-01 -3.87987226e-01 -7.98478782e-01 9.58322465e-01 1.25781333e+00 3.97120476e-01 1.66706964e-01 8.56057584e-01 4.74822707e-02 1.44454971e-01 -8.75181079e-01 7.88538754e-01 6.68404996e-01 -7.98048377e-01 -5.98876536e-01 2.30039716e-01 6.21977746e-01 -4.66598868e-02 2.30401650e-01 4.82591450e-01 1.84438586e-01 -9.28312004e-01 8.27424228e-01 1.09586217e-01 5.59988558e-01 -7.23044872e-01 1.23197985e+00 4.88934904e-01 -3.64130616e-01 -4.42457616e-01 -1.38873905e-01 1.01568371e-01 2.91693099e-02 7.31506109e-01 -1.11160076e+00 -3.00009131e-01 6.26018882e-01 3.85690063e-01 -7.98480213e-01 7.43174791e-01 -2.57732034e-01 8.63800764e-01 -2.22260624e-01 -2.13457197e-01 3.18741798e-01 2.26133093e-01 3.93725872e-01 1.51058459e+00 1.33356765e-01 -4.55372900e-01 9.86765400e-02 7.95742452e-01 -3.19183558e-01 4.51110303e-01 -8.04306924e-01 -1.84672907e-01 8.59697282e-01 1.32638443e+00 -4.78270203e-01 -8.52526501e-02 -3.07892054e-01 8.42795908e-01 8.23183715e-01 2.15051487e-01 -9.08943355e-01 -3.98649395e-01 3.57780635e-01 5.89633137e-02 6.34424910e-02 1.62443832e-01 -1.81315199e-01 -6.53528154e-01 -1.12043368e-03 -9.25346196e-01 2.53735721e-01 -6.59065008e-01 -1.61613405e+00 7.70204127e-01 -1.75891891e-01 -8.83001089e-01 -1.61218151e-01 -5.26308477e-01 -5.62409103e-01 7.64277816e-01 -1.01320744e+00 -1.19478774e+00 -1.00898653e-01 1.28851905e-01 5.23811877e-01 -1.41883075e-01 9.69367981e-01 4.65832919e-01 -8.09775949e-01 7.74128735e-01 6.23880140e-02 4.82446909e-01 1.12692094e+00 -1.36509776e+00 -2.15659961e-01 3.20276558e-01 1.57739148e-01 2.76011378e-01 8.34401369e-01 -6.01198614e-01 -4.80604231e-01 -9.94925976e-01 1.39370310e+00 -7.25774884e-01 1.03383327e+00 -7.90244818e-01 -1.27582288e+00 2.50862002e-01 4.32970613e-01 1.03179943e-02 1.20191145e+00 5.37858665e-01 -9.54468608e-01 2.45348439e-01 -1.06658554e+00 2.17768639e-01 5.28655767e-01 -9.20984685e-01 -6.08778298e-01 5.67370176e-01 7.91404486e-01 -1.05295144e-02 -8.36273849e-01 -3.49482596e-02 3.52852732e-01 -8.87550771e-01 3.58163446e-01 -4.29155409e-01 4.96972591e-01 -1.40527055e-01 2.99202336e-04 -1.66330385e+00 -2.29685411e-01 -2.88059682e-01 -1.55409738e-01 1.74245238e+00 5.88185787e-01 -3.44280571e-01 5.02140880e-01 6.86143517e-01 8.23378470e-03 -5.73202193e-01 -1.00501597e+00 -4.54280227e-01 1.76058248e-01 -1.85567394e-01 2.66162872e-01 1.52315831e+00 1.96177050e-01 5.43587506e-01 -7.68470824e-01 -6.90373704e-02 1.93293139e-01 -6.68424606e-01 4.44709599e-01 -1.54091036e+00 -3.39974500e-02 -4.26797420e-01 -4.14241374e-01 9.97291040e-03 7.47715294e-01 -8.77652168e-01 1.11740254e-01 -1.08391106e+00 3.24498564e-01 -5.45664966e-01 -5.10409176e-02 7.92112887e-01 -3.76509190e-01 6.36421919e-01 4.32827532e-01 4.75934714e-01 -6.65067971e-01 4.10382062e-01 7.10635602e-01 -4.18182582e-01 -6.02639355e-02 -3.03201228e-01 -3.73619825e-01 7.15803266e-01 6.37453496e-01 -9.69961226e-01 -2.96921313e-01 -3.02879363e-01 3.45639557e-01 -4.45103258e-01 2.84078687e-01 -8.96692276e-01 2.00838313e-01 3.27623934e-01 1.96044952e-01 -2.13493168e-01 5.04790604e-01 -9.73776221e-01 -3.25512961e-02 1.41694933e-01 -8.72509301e-01 -6.24229722e-02 -8.41509774e-02 3.30148131e-01 -2.36745179e-01 -7.67258227e-01 7.07691789e-01 2.90884584e-01 -1.14864998e-01 -3.43877748e-02 -7.06183195e-01 2.58071989e-01 9.78207827e-01 6.00510314e-02 -8.61581683e-01 -4.00403261e-01 -9.19630766e-01 -2.51250178e-01 3.95640552e-01 3.27609569e-01 5.77651151e-02 -1.25424910e+00 -9.73641455e-01 -1.22543583e-02 3.57092023e-01 -3.72567028e-01 3.63062412e-01 8.90053928e-01 -5.90555258e-02 1.12539046e-01 1.32151723e-01 -3.57838750e-01 -1.32402968e+00 6.65628970e-01 1.05816461e-01 -3.29679817e-01 -4.71972339e-02 8.18694532e-01 1.36509687e-01 -5.01650393e-01 4.15562987e-01 3.99766088e-01 -5.45782745e-01 8.84520531e-01 6.73572242e-01 5.03055930e-01 1.45214945e-01 -1.12331188e+00 -2.29357764e-01 1.80511206e-01 -1.54976696e-01 1.01645954e-01 1.11271012e+00 7.32208565e-02 -2.99681872e-01 8.63720715e-01 1.56882763e+00 1.41735449e-01 -7.80632555e-01 -2.15099469e-01 8.34182426e-02 -3.96949768e-01 1.28445193e-01 -9.14910257e-01 -8.48061979e-01 1.11220253e+00 6.60448492e-01 7.37456143e-01 6.51221275e-01 1.84331581e-01 5.63486040e-01 1.17229514e-01 -2.78701745e-02 -1.17703748e+00 2.87496060e-01 4.07239854e-01 7.46413946e-01 -1.34695292e+00 -3.09248090e-01 -2.17928916e-01 -8.83327961e-01 8.53835285e-01 7.01505959e-01 2.09000632e-01 4.81463373e-01 7.15873465e-02 4.34638172e-01 -3.08557481e-01 -7.69961357e-01 3.85530591e-02 3.29513192e-01 7.70919561e-01 7.46959865e-01 1.07200190e-01 -2.27479085e-01 4.80209023e-01 -7.41560906e-02 -6.29333377e-01 3.81423891e-01 4.66025174e-01 -5.04450917e-01 -9.45811331e-01 -5.15066683e-01 4.65109855e-01 -6.20182157e-01 -1.34143442e-01 -8.86861205e-01 5.19876897e-01 6.00846231e-01 1.12692928e+00 2.49301478e-01 -4.91523355e-01 9.17421207e-02 6.15117550e-01 -2.01386705e-01 -7.69873798e-01 -1.22900057e+00 -6.69751465e-02 3.55359524e-01 -7.76046216e-02 -2.74508357e-01 -5.04785240e-01 -5.57511508e-01 -2.73578674e-01 -6.48892939e-01 5.04703343e-01 8.29967022e-01 9.33551431e-01 2.83635348e-01 2.22673938e-01 7.64079690e-01 -7.98158824e-01 -4.58787233e-01 -1.38513970e+00 -7.07727551e-01 8.91529739e-01 4.08814251e-01 -9.01256442e-01 -9.89595711e-01 -6.95846155e-02]	[8.746495246887207, 10.562102317810059]
e9549742-703b-48ac-9557-cff06253aff3	deep-superpixel-based-network-for-blind-image	2110.06564	null	https://arxiv.org/abs/2110.06564v1	https://arxiv.org/pdf/2110.06564v1.pdf	Deep Superpixel-based Network for Blind Image Quality Assessment	The goal in a blind image quality assessment (BIQA) model is to simulate the process of evaluating images by human eyes and accurately assess the quality of the image. Although many approaches effectively identify degradation, they do not fully consider the semantic content in images resulting in distortion. In order to fill this gap, we propose a deep adaptive superpixel-based network, namely DSN-IQA, to assess the quality of image based on multi-scale and superpixel segmentation. The DSN-IQA can adaptively accept arbitrary scale images as input images, making the assessment process similar to human perception. The network uses two models to extract multi-scale semantic features and generate a superpixel adjacency map. These two elements are united together via feature fusion to accurately predict image quality. Experimental results on different benchmark databases demonstrate that our algorithm is highly competitive with other approaches when assessing challenging authentic image databases. Also, due to adaptive deep superpixel-based network, our model accurately assesses images with complicated distortion, much like the human eye.	['Yuxuan Wang', 'Yang Zhan.', 'Guangyi Yang']	2021-10-13	null	null	null	null	['blind-image-quality-assessment']	['computer-vision']	[ 2.47854337e-01 -4.25086141e-01 1.86443105e-01 -5.25288343e-01 -6.03168845e-01 -5.74590862e-01 7.49904960e-02 -3.00256222e-01 -2.37008289e-01 3.54109466e-01 2.48210192e-01 -1.52308285e-01 -4.59657842e-03 -7.88036227e-01 -4.69683230e-01 -4.24388349e-01 3.93584907e-01 1.06037757e-03 4.74860638e-01 -2.43355736e-01 4.61789906e-01 3.97282839e-01 -1.58737910e+00 4.32462156e-01 1.36712849e+00 1.12052953e+00 8.60017240e-02 7.78277934e-01 4.82853316e-02 9.02409494e-01 -6.97205603e-01 -4.29057211e-01 5.48389554e-01 -6.33141577e-01 -7.81514347e-01 4.59704816e-01 7.21197963e-01 -8.32532108e-01 -2.35280618e-01 1.77167666e+00 6.49470210e-01 -5.53952195e-02 5.45879066e-01 -1.23685873e+00 -1.05583835e+00 2.15610668e-01 -4.18932796e-01 5.19370914e-01 5.09405255e-01 4.54657704e-01 8.46729815e-01 -9.17141140e-01 1.53436244e-01 1.46174395e+00 5.02405405e-01 2.40823880e-01 -8.06518674e-01 -4.28982735e-01 -1.75492913e-02 5.38763702e-01 -1.12980425e+00 -3.33116531e-01 7.00044870e-01 -1.95170864e-01 3.85069668e-01 2.12349951e-01 7.16209292e-01 5.45237660e-01 1.08079433e-01 8.87721241e-01 1.64190042e+00 -2.18381539e-01 2.33658373e-01 -1.32633075e-01 5.33616841e-02 6.39690280e-01 1.89457923e-01 2.34959811e-01 -4.12703574e-01 2.93239951e-01 8.90445352e-01 -1.29065374e-02 -5.19206703e-01 -2.42269650e-01 -1.22644508e+00 3.19813102e-01 8.76753092e-01 1.05287030e-01 -3.91833186e-01 -9.55951959e-02 4.43076454e-02 3.90532076e-01 1.89705297e-01 2.58368552e-01 -7.47847185e-02 1.22253403e-01 -1.13132906e+00 -3.22061591e-02 3.53156537e-01 6.62684441e-01 6.85612917e-01 4.00481448e-02 -4.47176754e-01 8.93174171e-01 4.09822226e-01 5.66098571e-01 5.33648849e-01 -1.54211187e+00 2.58910298e-01 8.42514575e-01 3.83531064e-01 -1.08047760e+00 -1.40253857e-01 -5.14946282e-01 -1.04895854e+00 9.73510385e-01 4.85185295e-01 3.29081625e-01 -1.27794337e+00 1.27935469e+00 8.61916468e-02 -9.14370455e-03 -4.07989994e-02 1.51526141e+00 7.57182121e-01 7.01715946e-01 -8.30972642e-02 -1.77557737e-01 1.31281662e+00 -1.27761412e+00 -7.83303976e-01 -2.02702433e-01 -1.49515972e-01 -8.30473840e-01 1.28648949e+00 6.92217231e-01 -1.51914513e+00 -1.07847738e+00 -1.38635898e+00 -1.80141687e-01 -2.93258399e-01 5.48295826e-02 1.54966608e-01 7.54937589e-01 -1.60238576e+00 5.72328806e-01 -3.19075584e-01 -2.67739873e-02 4.96358305e-01 2.06989929e-01 -1.76539466e-01 -4.54150200e-01 -1.26114452e+00 8.30802798e-01 3.55211258e-01 2.97630250e-01 -1.18947506e+00 -3.55688781e-01 -6.35975003e-01 9.53443944e-02 3.24432030e-02 -9.19346154e-01 1.11070549e+00 -1.37331510e+00 -1.39115834e+00 8.25795174e-01 -2.03165695e-01 -3.17859471e-01 7.75113106e-01 1.40887853e-02 -5.56797206e-01 5.21344602e-01 1.24994114e-01 7.10156441e-01 1.05978906e+00 -1.59929836e+00 -7.44044006e-01 -4.22271729e-01 3.88348937e-01 4.90384430e-01 -2.75679588e-01 3.14220369e-01 -7.85117209e-01 -7.26824641e-01 2.47701749e-01 -5.30345261e-01 -1.46183029e-01 3.99915785e-01 -3.50648969e-01 -5.55586710e-04 5.31674445e-01 -9.43576336e-01 1.22585166e+00 -2.01096916e+00 -9.61630326e-03 2.56374687e-01 5.20263970e-01 6.35910153e-01 -4.60144341e-01 -1.32929206e-01 1.76851794e-01 2.99193300e-02 -5.18384099e-01 -2.21941665e-01 -3.35605140e-03 -7.11737797e-02 1.03507806e-02 3.37138325e-01 1.34888217e-01 1.03942478e+00 -9.25580978e-01 -6.23117626e-01 3.21957141e-01 3.94902110e-01 -2.45982796e-01 4.01283681e-01 4.75965589e-02 2.24002585e-01 -2.30444014e-01 8.94241452e-01 1.11907470e+00 -3.41262847e-01 -2.61631191e-01 -6.07243657e-01 1.62628233e-01 -1.77368060e-01 -1.24971187e+00 1.68640435e+00 -1.75285041e-01 6.05861366e-01 1.16058715e-01 -6.30022287e-01 7.04445004e-01 1.01290062e-01 1.31577417e-01 -1.14640641e+00 8.97004306e-02 2.84067780e-01 -2.52065659e-02 -4.84023303e-01 3.97451878e-01 2.41934046e-01 3.21428448e-01 4.58032399e-01 -3.93757522e-02 -2.79933602e-01 2.47115687e-01 1.49102524e-01 6.84379816e-01 -6.28952831e-02 -5.89781813e-03 -1.29879899e-02 9.19632316e-01 -2.93036491e-01 7.68631518e-01 6.57055318e-01 -8.54960561e-01 1.14571190e+00 2.67656356e-01 -4.83273119e-01 -1.27827752e+00 -1.42376268e+00 9.37238783e-02 7.12053299e-01 9.59500670e-01 5.11737205e-02 -1.28473353e+00 -6.19810104e-01 -1.98657364e-01 2.06049398e-01 -4.82011348e-01 -1.41175628e-01 -2.80702263e-01 -7.41008818e-01 1.99131072e-01 4.78834003e-01 1.14126241e+00 -1.09601259e+00 -1.83050126e-01 -9.37857255e-02 -4.65007454e-01 -1.14199913e+00 -8.29082847e-01 -6.40867889e-01 -5.83546698e-01 -1.17756259e+00 -9.76511121e-01 -1.00459588e+00 7.79034436e-01 6.32981956e-01 1.17760956e+00 3.35399449e-01 -2.66456425e-01 1.57103807e-01 -2.80704558e-01 -1.90661903e-02 -5.93592942e-01 -6.98726773e-01 4.34091166e-02 2.48772919e-01 2.24627063e-01 -4.08953398e-01 -1.32062888e+00 6.67638242e-01 -1.29804671e+00 4.26188074e-02 8.93860221e-01 6.14226401e-01 6.76068306e-01 5.72937965e-01 4.15419966e-01 -3.32936823e-01 9.66688573e-01 8.04525912e-02 -5.22549629e-01 6.37805283e-01 -9.70323324e-01 -1.26299396e-01 5.84627926e-01 -1.23280734e-01 -1.15767896e+00 -2.33063117e-01 -5.48575353e-03 -2.63178825e-01 -1.72619596e-01 1.37549028e-01 -5.03861308e-01 -4.68220949e-01 5.12844801e-01 3.93033713e-01 4.52548191e-02 -2.47658342e-01 4.23269212e-01 9.19805706e-01 9.24419582e-01 2.37159599e-02 8.18497837e-01 4.66630459e-01 -1.68882892e-01 -1.59448147e-01 -8.55017543e-01 -4.92480725e-01 -6.46966994e-01 -5.28147578e-01 1.02756429e+00 -1.05232203e+00 -6.81373239e-01 1.15230179e+00 -1.06043780e+00 -1.73091605e-01 -4.75361273e-02 2.54936367e-01 -4.76883382e-01 9.21913803e-01 -7.74412572e-01 -5.22193551e-01 -5.30931532e-01 -1.49798477e+00 1.02589190e+00 4.47751522e-01 4.20245051e-01 -7.64842451e-01 -3.80525082e-01 9.70288932e-01 5.41335404e-01 6.57263584e-03 5.75041711e-01 1.53316826e-01 -8.48423302e-01 -2.24892162e-02 -9.57808614e-01 1.01513791e+00 2.50391841e-01 -8.67778212e-02 -9.46803272e-01 -3.16932499e-01 4.14010100e-02 -2.34501198e-01 8.61701429e-01 4.89789009e-01 1.29725969e+00 -1.88186318e-01 3.37192744e-01 7.22539186e-01 1.56505561e+00 6.63657337e-02 9.37269211e-01 3.40316653e-01 6.07270241e-01 4.40181047e-01 7.46204913e-01 8.94759744e-02 5.55925071e-01 5.11813045e-01 7.47464538e-01 -5.20871878e-01 -7.40716100e-01 -8.23702589e-02 5.18468857e-01 8.60399902e-01 9.79266874e-03 -4.04863596e-01 -8.00671101e-01 5.75330675e-01 -1.48498154e+00 -7.80739963e-01 -2.73157120e-01 1.91994870e+00 8.36730659e-01 2.13878289e-01 4.88872975e-02 2.16456771e-01 8.82582605e-01 7.20193936e-03 -8.23700964e-01 -1.29824355e-01 -5.54959893e-01 -4.96379472e-02 4.65083688e-01 5.08647323e-01 -1.08711207e+00 7.75251985e-01 6.79340029e+00 8.53634000e-01 -7.68311918e-01 7.78837651e-02 1.01951611e+00 1.42420158e-01 -2.29194015e-01 -2.58449554e-01 -2.33454108e-01 7.07166731e-01 4.77538556e-01 -1.36675909e-01 7.66155005e-01 3.02198499e-01 5.15657961e-01 -2.77827412e-01 -7.27654696e-01 1.17641675e+00 3.82964790e-01 -9.23229992e-01 4.76612478e-01 -1.50640890e-01 1.06208968e+00 -1.56436443e-01 4.77102995e-01 -4.52160627e-01 5.08174360e-01 -1.21986330e+00 8.47383499e-01 8.42135310e-01 7.81228900e-01 -5.53975821e-01 8.61074448e-01 5.35163423e-03 -9.76800680e-01 -3.50497395e-01 -4.91637379e-01 2.43464664e-01 1.95024982e-01 5.52989066e-01 -2.44556874e-01 4.88788545e-01 1.03451908e+00 6.81636512e-01 -1.08167136e+00 1.47725689e+00 -3.91590297e-01 4.47934568e-01 1.68820292e-01 4.62358475e-01 1.60331652e-01 -3.64101976e-01 4.53329474e-01 7.69443452e-01 3.49747688e-01 5.97307794e-02 -1.14359148e-01 1.04153514e+00 -1.28628254e-01 -8.90529528e-02 4.91746627e-02 2.33945906e-01 3.41685534e-01 1.14714932e+00 -5.04774034e-01 -3.99849057e-01 -4.40690756e-01 1.55919087e+00 -8.22191089e-02 5.61391830e-01 -6.07420385e-01 -4.22697753e-01 6.84445083e-01 -1.63450226e-01 2.28036493e-02 -5.83991744e-02 -3.81755739e-01 -1.09315586e+00 3.51644993e-01 -1.16653395e+00 1.67181104e-01 -1.55963075e+00 -1.33264959e+00 7.52229571e-01 -6.32842302e-01 -1.61461258e+00 1.82085127e-01 -7.16825902e-01 -5.69534183e-01 1.02419591e+00 -1.99919736e+00 -1.15227509e+00 -9.32649016e-01 8.12618732e-01 6.35588348e-01 -4.06227298e-02 2.76635081e-01 2.97202438e-01 -4.45523113e-01 6.02215588e-01 7.72526264e-02 2.46917948e-01 8.71470273e-01 -1.44661129e+00 5.11862695e-01 1.38069224e+00 -1.42385811e-01 2.91919231e-01 5.22980273e-01 -4.29024160e-01 -8.78901601e-01 -1.19270539e+00 3.25204700e-01 -4.11519438e-01 3.66998345e-01 1.91287905e-01 -9.98398066e-01 -1.36973575e-01 4.10032302e-01 2.07336605e-01 3.81877512e-01 -6.95903182e-01 -3.74111205e-01 -4.32380080e-01 -1.27528954e+00 3.00348997e-01 1.15874684e+00 -7.18120039e-01 -5.45587778e-01 1.90210685e-01 8.54176223e-01 -1.43410683e-01 -8.94466221e-01 5.38027346e-01 4.33741957e-01 -1.54974663e+00 1.25163591e+00 -1.35084659e-01 5.17508745e-01 -9.23528850e-01 -9.47818831e-02 -1.37482667e+00 -4.72215503e-01 -1.67739451e-01 6.09954782e-02 1.09689343e+00 1.85256928e-01 -4.35188711e-01 4.88552958e-01 4.02889431e-01 -4.57418151e-02 -3.16739410e-01 -6.53296709e-01 -6.59888208e-01 -1.83020547e-01 -1.38940886e-01 9.51851547e-01 6.95117593e-01 -6.30474567e-01 -1.41698822e-01 -3.82077873e-01 5.48797548e-01 1.10266256e+00 1.79693282e-01 3.96279514e-01 -1.05509889e+00 -1.54428303e-01 -7.31002867e-01 -6.98547304e-01 -1.07057321e+00 -2.47700959e-01 -4.83532190e-01 1.21794604e-01 -1.94030130e+00 3.78823549e-01 -1.96730196e-01 -7.38467872e-01 2.70847185e-03 -6.55427158e-01 8.70129049e-01 8.23607892e-02 4.44957942e-01 -1.03796864e+00 3.42581570e-01 1.78638208e+00 -5.50750673e-01 3.85749526e-02 -1.54599324e-01 -7.79169202e-01 5.72659552e-01 7.02724457e-01 1.50328279e-01 -4.46292281e-01 -7.61635959e-01 3.13835442e-01 -2.32777689e-02 6.65645003e-01 -1.26585901e+00 3.90354604e-01 -2.56983973e-02 6.36048734e-01 -4.06095356e-01 3.13946828e-02 -7.90241361e-01 -1.41573846e-01 3.05251509e-01 -3.15175563e-01 -8.61489493e-03 -1.89609438e-01 5.39443970e-01 -8.20728540e-01 -8.11741203e-02 1.01170611e+00 -2.67603666e-01 -1.14837313e+00 5.79893351e-01 -1.09904245e-01 -1.27165064e-01 9.18160796e-01 -5.60381532e-01 -4.67245430e-01 -5.83548069e-01 -6.77202106e-01 3.87058854e-01 8.30408156e-01 3.88339579e-01 1.03816545e+00 -1.41323602e+00 -7.60115921e-01 2.88770407e-01 1.98983580e-01 -7.09641874e-02 5.85042536e-01 5.04624188e-01 -9.99665916e-01 1.02876246e-01 -4.85382527e-01 -5.44511676e-01 -1.20404196e+00 6.31626725e-01 7.61344135e-01 6.92864582e-02 -1.67923853e-01 8.70518386e-01 2.96640277e-01 -2.41293937e-01 2.12220788e-01 -3.05185378e-01 -3.82537246e-01 -2.90671498e-01 8.32626700e-01 4.10279691e-01 4.45991419e-02 -7.53179371e-01 -7.07648620e-02 7.02555835e-01 1.24119774e-01 -1.00247115e-02 9.83609915e-01 -7.55692780e-01 -5.02666652e-01 2.99845301e-02 9.74823892e-01 -2.33518556e-01 -1.51527274e+00 -3.81489515e-01 -4.24734145e-01 -8.18762124e-01 3.62584591e-01 -1.25194645e+00 -1.29769313e+00 1.03775311e+00 1.29454029e+00 2.58866936e-01 1.86391270e+00 -3.69653225e-01 9.93259132e-01 -8.49680305e-02 2.78719574e-01 -1.21705365e+00 4.61408377e-01 -5.16699068e-02 9.09431517e-01 -1.60048926e+00 -7.95163661e-02 -4.24880981e-01 -6.75149977e-01 1.04322112e+00 8.46049011e-01 -5.99200949e-02 3.43285978e-01 -2.71162480e-01 5.32251179e-01 8.39686841e-02 -2.20708877e-01 -2.07067311e-01 6.35881305e-01 7.70032644e-01 -1.11748166e-01 -4.15872841e-04 -1.66532416e-02 3.21195155e-01 -6.72185794e-02 8.45647603e-02 7.24953771e-01 2.97828168e-01 -6.59103990e-01 -8.67694795e-01 -6.21867597e-01 3.30953032e-01 -4.14772362e-01 -2.36071154e-01 -3.77840430e-01 -9.97040235e-03 2.55163074e-01 1.44840729e+00 1.12337964e-02 -4.93092626e-01 2.39981532e-01 -4.59835231e-01 3.21542054e-01 -1.20903835e-01 -3.65687430e-01 -2.49057531e-01 -4.10085768e-01 -8.95507455e-01 -7.05101073e-01 -2.93143183e-01 -8.72018933e-01 -2.45829850e-01 -8.54036510e-02 -7.67350644e-02 5.10648251e-01 7.34436035e-01 2.22113341e-01 5.92581868e-01 9.56087470e-01 -5.91037393e-01 -4.24417913e-01 -8.74602258e-01 -7.29958951e-01 7.50563622e-01 6.74761593e-01 -3.15697789e-01 -4.43840444e-01 1.90482423e-01]	[11.88250732421875, -1.8439362049102783]
5bc43591-6cb9-40d4-9181-84bcc8b20d60	biobert-a-pre-trained-biomedical-language	1901.08746	null	https://arxiv.org/abs/1901.08746v4	https://arxiv.org/pdf/1901.08746v4.pdf	BioBERT: a pre-trained biomedical language representation model for biomedical text mining	Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora. We introduce BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining), which is a domain-specific language representation model pre-trained on large-scale biomedical corpora. With almost the same architecture across tasks, BioBERT largely outperforms BERT and previous state-of-the-art models in a variety of biomedical text mining tasks when pre-trained on biomedical corpora. While BERT obtains performance comparable to that of previous state-of-the-art models, BioBERT significantly outperforms them on the following three representative biomedical text mining tasks: biomedical named entity recognition (0.62% F1 score improvement), biomedical relation extraction (2.80% F1 score improvement) and biomedical question answering (12.24% MRR improvement). Our analysis results show that pre-training BERT on biomedical corpora helps it to understand complex biomedical texts. We make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert.	['Wonjin Yoon', 'Jinhyuk Lee', 'Sunkyu Kim', 'Sungdong Kim', 'Jaewoo Kang', 'Chan Ho So', 'Donghyeon Kim']	2019-01-25	null	null	null	null	['medical-relation-extraction', 'drug-drug-interaction-extraction', 'medical-named-entity-recognition']	['medical', 'natural-language-processing', 'natural-language-processing']	[ 1.83626726e-01 2.89666921e-01 -3.63866001e-01 -3.83014381e-01 -1.04952061e+00 -7.28878230e-02 1.76765978e-01 5.29146254e-01 -8.22214186e-01 9.71138537e-01 3.21230620e-01 -4.83589083e-01 5.45527413e-03 -6.86218798e-01 -6.45424843e-01 -5.59514582e-01 -1.63384303e-01 6.94480419e-01 -1.99071243e-01 -1.28737047e-01 -2.22384691e-01 2.20527515e-01 -8.39548707e-01 5.60639143e-01 8.14200103e-01 8.32358241e-01 2.32172504e-01 6.88186049e-01 -8.69883522e-02 5.51418900e-01 -5.79212070e-01 -5.48468947e-01 -2.33169109e-01 -3.93089563e-01 -1.09682691e+00 -3.40200305e-01 -1.93289116e-01 -2.73540188e-02 -4.49349612e-01 8.38477015e-01 8.72750401e-01 -3.42984557e-01 7.08512247e-01 -8.01031232e-01 -8.00848782e-01 6.40626967e-01 -5.70363224e-01 4.70689863e-01 1.94105599e-02 -1.01247542e-01 9.83846724e-01 -8.22135746e-01 7.88388193e-01 9.70357478e-01 7.30284691e-01 8.76122773e-01 -1.14996517e+00 -9.31479335e-01 -2.18247145e-01 2.43502632e-01 -1.40919197e+00 -4.47673082e-01 3.73354435e-01 -3.85903209e-01 1.27409685e+00 1.27542123e-01 3.63310784e-01 1.40028572e+00 6.92597210e-01 8.81945848e-01 6.44650459e-01 -2.76140392e-01 -1.30609736e-01 -5.70170432e-02 1.44389689e-01 8.45524967e-01 3.47987175e-01 -8.56216252e-02 -4.84777093e-01 -3.20439845e-01 4.57398087e-01 -7.88637921e-02 -3.24689776e-01 3.23727220e-01 -1.37344933e+00 8.75878990e-01 3.41628402e-01 7.38419712e-01 -3.91276062e-01 1.26453131e-01 7.25240231e-01 2.35852689e-01 6.43198431e-01 5.81964910e-01 -8.84620130e-01 -1.04409970e-01 -8.18767011e-01 -4.30012532e-02 7.40816414e-01 8.29043031e-01 2.32193172e-01 -1.54682159e-01 -1.35682523e-01 1.17209089e+00 2.33239025e-01 2.60948330e-01 9.48024333e-01 -3.71939957e-01 3.89193684e-01 6.73259795e-01 -4.88173813e-01 -7.32242763e-01 -8.51406872e-01 -7.87017286e-01 -1.18341017e+00 -6.48674309e-01 3.90957862e-01 -3.95852029e-01 -9.04256940e-01 1.66669416e+00 2.37390757e-01 -2.02730328e-01 1.45840675e-01 5.80372632e-01 1.18773127e+00 6.10200644e-01 3.29461485e-01 -7.39525855e-02 1.84819138e+00 -5.76849043e-01 -7.83173203e-01 -1.82606786e-01 9.34543014e-01 -6.57147765e-01 6.30437076e-01 4.45831090e-01 -7.96936095e-01 -2.66343415e-01 -8.37415814e-01 -4.77686673e-01 -5.06714821e-01 3.03570986e-01 5.36993444e-01 3.47857147e-01 -8.08498979e-01 4.48403865e-01 -1.07623684e+00 -5.38834572e-01 9.10608888e-01 5.21209657e-01 -5.89657366e-01 -1.48480698e-01 -1.48062778e+00 9.61669862e-01 4.14050877e-01 3.45057398e-02 -7.92130649e-01 -1.01909268e+00 -6.85850084e-01 3.23424488e-02 1.78675279e-01 -1.04215991e+00 1.12292874e+00 -5.22122324e-01 -9.85864043e-01 1.23232019e+00 -2.06443936e-01 -5.56171417e-01 2.77686536e-01 -2.76234627e-01 -4.70951170e-01 2.70911276e-01 2.08706439e-01 7.36429870e-01 1.65400952e-01 -5.43620288e-01 -4.51862782e-01 -4.51079696e-01 -5.54052770e-01 -2.37488464e-01 -5.74877083e-01 5.66560440e-02 -3.91863167e-01 -7.31480896e-01 -4.56490278e-01 -6.59555197e-01 -3.76656026e-01 -2.21123993e-02 -4.91363227e-01 -4.33449805e-01 3.09440911e-01 -7.85960197e-01 1.10781515e+00 -1.90813076e+00 -1.55852865e-02 -2.09798306e-01 3.23844850e-01 3.05752635e-01 -2.87773788e-01 5.78172922e-01 -3.90347511e-01 3.03214937e-01 -3.88401479e-01 -9.99577567e-02 -3.25416654e-01 1.18099920e-01 1.59149840e-01 5.38982928e-01 5.19234240e-01 1.11851144e+00 -1.05669105e+00 -6.01866782e-01 -1.49724498e-01 7.19377935e-01 -5.16189039e-01 7.76047260e-02 -1.09737284e-01 4.62238938e-01 -7.10043132e-01 7.00537741e-01 3.18678290e-01 -6.21422529e-01 2.85813749e-01 -3.31765652e-01 4.56854850e-01 4.41096544e-01 -2.52048731e-01 1.86521590e+00 -3.49248916e-01 5.50041139e-01 -7.52420649e-02 -1.46849275e+00 8.40908825e-01 6.61254466e-01 9.16824698e-01 -6.45690143e-01 3.45059425e-01 1.98804706e-01 2.66994476e-01 -7.97153831e-01 -1.31792739e-01 -4.81627405e-01 3.68622914e-02 2.45327100e-01 3.76318097e-01 3.26069325e-01 3.37893337e-01 1.66494325e-01 1.49056089e+00 -9.58287194e-02 6.72604918e-01 -3.21836859e-01 6.29689574e-01 2.50041842e-01 6.08974516e-01 3.73248875e-01 -1.35474965e-01 3.89704764e-01 4.89078045e-01 -4.02843595e-01 -6.27305746e-01 -7.75433183e-01 -6.77261174e-01 1.01830447e+00 -5.11550248e-01 -5.75088084e-01 -5.65087676e-01 -7.47465074e-01 1.37645036e-01 5.57823539e-01 -8.17542255e-01 -2.73067385e-01 -5.08569896e-01 -1.42725742e+00 1.09367526e+00 4.42666739e-01 4.03089881e-01 -1.14853537e+00 -3.37905616e-01 4.97044086e-01 -3.87319863e-01 -1.14432359e+00 -3.43264461e-01 4.13652122e-01 -1.08165479e+00 -1.24385369e+00 -9.03767705e-01 -7.81697452e-01 6.24706507e-01 -3.66330624e-01 1.24121666e+00 2.14555204e-01 -8.31084251e-01 3.70302871e-02 -3.89297485e-01 -8.94230068e-01 -6.07379675e-01 5.07320046e-01 -2.15750203e-01 -3.99959654e-01 8.73538196e-01 -2.43427813e-01 -7.26191878e-01 3.86805180e-03 -9.30047870e-01 1.77546948e-01 9.05320287e-01 1.26703143e+00 5.43566346e-01 -2.97773063e-01 1.19574344e+00 -1.29584241e+00 5.46956062e-01 -7.83715427e-01 -1.24621224e-02 9.53725576e-02 -7.05000520e-01 9.70952213e-02 5.29338300e-01 -3.80148321e-01 -7.57241249e-01 -1.75566956e-01 -8.75415206e-01 -2.73563135e-02 -2.66316324e-01 9.88123357e-01 1.30616784e-01 6.32227898e-01 8.23360205e-01 1.39281228e-01 -5.87602332e-02 -5.42941630e-01 6.80315793e-02 9.14210200e-01 3.16780716e-01 -4.15181726e-01 1.27779558e-01 3.05556446e-01 -1.21239416e-01 -8.04750323e-01 -9.23504949e-01 -6.25531733e-01 -4.23323601e-01 2.86247075e-01 1.06634915e+00 -8.04275274e-01 -6.25899315e-01 8.84394348e-02 -9.90866125e-01 -3.17480803e-01 1.54988728e-02 5.25179863e-01 -2.85228699e-01 2.00524181e-01 -9.68765974e-01 -4.42538381e-01 -9.24272060e-01 -1.05555022e+00 1.15683317e+00 -2.87771583e-01 -6.38569534e-01 -1.16290128e+00 2.35272646e-02 6.34491861e-01 1.57800466e-01 2.75703132e-01 1.44441307e+00 -1.07988930e+00 1.81192875e-01 -2.38851860e-01 -2.17039108e-01 1.50532469e-01 3.89149249e-01 -5.34617782e-01 -1.00875854e+00 -2.61415362e-01 -8.31021965e-02 -2.62458980e-01 1.03988767e+00 3.80480170e-01 1.46382320e+00 -3.28874499e-01 -8.03031206e-01 6.22030497e-01 1.11390948e+00 2.55771637e-01 5.29492617e-01 3.45879763e-01 4.85027403e-01 5.56399047e-01 2.63708919e-01 1.86431780e-01 3.66696239e-01 3.72743875e-01 1.83986872e-01 -3.67540926e-01 -6.93509430e-02 -6.78126281e-03 1.25286460e-01 9.74257350e-01 4.84822914e-02 -2.05425978e-01 -1.20066881e+00 8.00923526e-01 -1.61942029e+00 -6.45047426e-01 2.73386817e-02 1.66793132e+00 1.60918570e+00 -4.35397625e-02 -2.06210352e-02 -7.72636533e-02 3.86467874e-01 -3.24539632e-01 -6.90501392e-01 -2.95213044e-01 1.35136724e-01 4.86881644e-01 3.82920861e-01 1.63075060e-01 -1.04667926e+00 7.56111324e-01 5.46616316e+00 9.01536822e-01 -1.14067554e+00 3.31027865e-01 1.13447940e+00 -1.40475377e-01 8.35414138e-03 -5.70824981e-01 -7.71466017e-01 3.79206806e-01 1.28915334e+00 -4.60234404e-01 -1.30294651e-01 5.99389076e-01 1.01868339e-01 2.97581643e-01 -1.44960368e+00 9.97830331e-01 -1.04105406e-01 -1.48629487e+00 8.44261795e-02 1.66688249e-01 3.51052076e-01 5.00259817e-01 -1.54265895e-01 4.14438218e-01 1.24281406e-01 -1.32569110e+00 9.60161984e-02 3.05275857e-01 1.06435585e+00 -5.13711631e-01 1.09313059e+00 4.34948415e-01 -7.39250958e-01 1.64559826e-01 -5.04776120e-01 4.18415248e-01 -6.66836500e-02 9.91006374e-01 -1.18417001e+00 7.14853346e-01 8.00000906e-01 9.51896846e-01 -3.49724978e-01 6.98364019e-01 -4.58953381e-02 8.97998989e-01 -4.44692075e-02 -1.73597172e-01 -2.94239130e-02 1.72318056e-01 2.52813816e-01 1.76009452e+00 1.94193393e-01 1.69467509e-01 -8.78881216e-02 8.50067496e-01 -5.18306851e-01 4.10294831e-01 -3.36570919e-01 -4.22289461e-01 1.16651393e-01 1.39991200e+00 -5.36809504e-01 -3.88932347e-01 -4.43338841e-01 5.80261171e-01 3.01542193e-01 3.28193307e-01 -6.98488891e-01 -4.29218292e-01 4.53763336e-01 9.64475647e-02 1.47382021e-02 2.52238512e-01 -2.10422650e-01 -1.08175910e+00 -4.66387630e-01 -1.20165098e+00 6.94062769e-01 -4.28276986e-01 -1.59278691e+00 7.52098083e-01 -1.21637635e-01 -8.85410547e-01 -1.05750129e-01 -9.03077245e-01 -1.38089761e-01 7.89365888e-01 -1.48870015e+00 -9.78799880e-01 1.27234593e-01 3.00125837e-01 5.73186100e-01 -3.03420395e-01 1.16696465e+00 5.83144367e-01 -6.09178960e-01 7.88516045e-01 4.25542630e-02 5.73065996e-01 1.00759923e+00 -1.01934850e+00 3.38781923e-01 2.74777174e-01 -2.42234543e-02 9.83335376e-01 3.65916640e-01 -6.42372727e-01 -1.32493901e+00 -1.28212786e+00 1.25215220e+00 -3.23919088e-01 7.67659307e-01 -3.89095396e-01 -1.03718305e+00 6.81099355e-01 1.97206050e-01 -1.26398310e-01 1.26777470e+00 2.81154662e-01 -1.95815727e-01 -5.05196936e-02 -1.05348468e+00 5.20986497e-01 9.00399148e-01 -3.52589458e-01 -6.03437126e-01 6.56286478e-01 4.08840805e-01 -2.75654346e-01 -1.34956169e+00 4.56737161e-01 6.09994411e-01 -3.47663254e-01 9.20821369e-01 -8.41860831e-01 6.65475428e-01 8.58764574e-02 1.95787698e-01 -1.19565773e+00 -2.86290944e-01 -3.27931076e-01 2.83461642e-02 8.23947489e-01 8.01411450e-01 -8.05305302e-01 7.13643253e-01 1.40829936e-01 -1.04173906e-01 -1.48189700e+00 -9.49558198e-01 -3.91200304e-01 5.85988939e-01 -3.72455567e-01 3.51899266e-01 1.07353818e+00 4.32608455e-01 8.00418496e-01 -1.04956503e-03 -2.67616361e-01 1.88779846e-01 -1.56799316e-01 3.85817915e-01 -1.15713274e+00 -3.49088371e-01 -5.04926980e-01 -2.65561700e-01 -8.90791059e-01 8.76154006e-02 -1.47801065e+00 -1.01873130e-01 -1.85155237e+00 4.81230259e-01 -2.90955484e-01 -6.25132024e-01 9.54644680e-01 -4.02566105e-01 1.91341802e-01 -1.79862902e-01 -1.38037535e-03 -1.91495538e-01 3.71910989e-01 1.20967603e+00 -4.68934089e-01 1.39715090e-01 -1.51403874e-01 -1.04361105e+00 5.34114182e-01 9.89447296e-01 -7.62285531e-01 -1.01741612e-01 -4.17814046e-01 2.68481284e-01 5.78127354e-02 3.24980952e-02 -6.79403901e-01 1.79084003e-01 2.32537031e-01 7.61020482e-01 -4.45035905e-01 1.95979789e-01 -4.51915830e-01 -1.18341394e-01 8.35227072e-01 -5.30639291e-01 -2.61586830e-02 5.80079317e-01 3.08111101e-01 -1.81145176e-01 -1.90777972e-01 6.17000699e-01 -1.71749949e-01 -1.33327022e-01 3.61921549e-01 -7.14903474e-01 2.02445090e-01 5.44687510e-01 1.50813311e-01 -4.36029047e-01 -1.31306201e-01 -7.95042336e-01 3.76481742e-01 -2.31957108e-01 3.69763911e-01 5.91473520e-01 -9.51168656e-01 -1.08913493e+00 3.73690352e-02 2.03745246e-01 -4.83772382e-02 1.47711262e-01 1.13301516e+00 -5.04046381e-01 7.40639925e-01 8.90816301e-02 -4.37283099e-01 -1.26085842e+00 4.15879637e-01 4.36408818e-01 -6.87423944e-01 -6.47312403e-01 9.82556462e-01 5.58493078e-01 -4.85906035e-01 6.60881102e-02 -5.50224960e-01 -2.40382388e-01 -7.02101216e-02 5.36964774e-01 1.46099895e-01 3.82046282e-01 -2.45511651e-01 -6.34361982e-01 1.90012872e-01 -4.86879915e-01 2.94766039e-01 1.57248986e+00 3.43020469e-01 -1.96594194e-01 3.93255115e-01 1.39537966e+00 -1.74290180e-01 -3.66395563e-01 -1.49047434e-01 3.14433724e-01 1.79922909e-01 -1.79309137e-02 -1.16304696e+00 -1.14234650e+00 9.62419271e-01 4.24879551e-01 -2.57198185e-01 1.04283714e+00 1.96235240e-01 9.35792685e-01 6.44288719e-01 1.54823110e-01 -7.72716284e-01 -1.14925817e-01 5.00581801e-01 9.83869851e-01 -1.14849186e+00 1.98864266e-01 -3.53101641e-01 -5.04318357e-01 1.08033669e+00 3.47916573e-01 1.07583039e-01 8.77187312e-01 5.59742212e-01 2.13460833e-01 -4.53666478e-01 -9.83193338e-01 3.02690342e-02 4.48505372e-01 4.66622204e-01 1.26262605e+00 -3.13788168e-02 -5.32299221e-01 1.10291600e+00 -3.16053778e-01 3.90015900e-01 1.43372327e-01 6.78257763e-01 -1.01245090e-01 -1.37257242e+00 -1.08555004e-01 9.35090005e-01 -1.18478167e+00 -3.95347297e-01 -3.62738311e-01 8.93280387e-01 3.63991223e-02 9.60063696e-01 -1.69544414e-01 -1.09347388e-01 2.10915789e-01 2.67727911e-01 4.04838204e-01 -9.09184456e-01 -7.55464613e-01 2.58815736e-01 2.82777041e-01 -2.93477118e-01 -3.16581637e-01 -4.19862658e-01 -1.65902746e+00 1.67848822e-02 -3.45362276e-01 3.38317662e-01 3.62061352e-01 9.09942269e-01 6.20746970e-01 9.17385876e-01 -1.84780717e-01 -1.59465805e-01 -3.22857708e-01 -1.28492475e+00 -3.42245638e-01 2.12962136e-01 2.57969677e-01 -4.48577404e-01 4.48236652e-02 3.88379484e-01]	[8.529837608337402, 8.70948600769043]
1ea8342d-3fa1-4b25-b06d-89582ae30d98	interrupt-me-politely-recommending-products	null	null	https://aclanthology.org/2020.ecomnlp-1.4	https://aclanthology.org/2020.ecomnlp-1.4.pdf	Interrupt me Politely: Recommending Products and Services by Joining Human Conversation	We propose a novel way of conversational recommendation, where instead of asking questions to the user to acquire their preferences; the recommender tracks their conversation with other people, including customer support agents (CSA), and joins the conversation only when it is time to introduce a recommendation. Building a recommender that joins a human conversation (RJC), we propose information extraction, discourse and argumentation analyses, as well as dialogue management techniques to compute a recommendation for a product and service that is needed by the customer, as inferred from the conversation. A special case of such conversations is considered where the customer raises his problem with CSA in an attempt to resolve it, along with receiving a recommendation for a product with features addressing this problem. We evaluate performance of RJC is in a number of human-human and human-chat bot dialogues, and demonstrate that RJC is an efficient and less intrusive way to provide high relevance and persuasive recommendations.	['Dmitry Ilvovsky', 'Boris Galitsky']	null	null	null	null	ecomnlp-coling-2020-12	['dialogue-management']	['natural-language-processing']	[ 3.71306449e-01 1.07431579e+00 6.63973158e-03 -4.98539776e-01 -3.79078597e-01 -8.51622403e-01 9.55826044e-01 3.39345485e-01 -1.16296366e-01 7.48616636e-01 7.47490227e-01 -4.64280158e-01 -1.11981817e-01 -6.69919252e-01 2.76316166e-01 -4.62179869e-01 3.06307852e-01 9.93592262e-01 3.08937103e-01 -8.07415247e-01 5.99866211e-01 3.78993899e-01 -1.14797795e+00 5.72845519e-01 5.14878809e-01 5.70738018e-01 1.91608638e-01 8.83984029e-01 -2.60312587e-01 1.15423071e+00 -9.32038844e-01 -7.30235398e-01 -1.60469919e-01 -5.71727931e-01 -1.69189370e+00 3.49628448e-01 -4.00496274e-01 -4.77506340e-01 5.12258708e-01 4.47623312e-01 3.30077201e-01 4.99740511e-01 6.71423674e-01 -1.31706882e+00 -5.99805489e-02 1.19558549e+00 -1.04560398e-01 4.75771492e-03 9.78697419e-01 -1.39485877e-02 1.16631842e+00 -1.89955547e-01 8.09783518e-01 1.15189099e+00 4.79230404e-01 9.57409501e-01 -9.67726827e-01 -4.31332700e-02 3.52420688e-01 -1.31144971e-01 -4.63396281e-01 -4.12103117e-01 6.49650514e-01 -3.12126368e-01 1.23349082e+00 7.90280938e-01 4.62495208e-01 1.21942532e+00 -2.67993480e-01 3.14176142e-01 5.87490678e-01 -3.60936522e-01 3.49498898e-01 6.95334971e-01 6.40341640e-01 1.32115573e-01 -2.42583856e-01 -4.56279457e-01 -3.47621769e-01 -9.59120214e-01 1.71456844e-01 -2.52295583e-01 -9.08429101e-02 5.45028746e-01 -9.74625111e-01 1.05960059e+00 -2.66072303e-01 4.72195894e-01 -8.11598241e-01 -4.21356887e-01 4.26198274e-01 6.02045774e-01 4.68316674e-01 1.01857281e+00 -4.18491453e-01 -6.20603263e-01 -1.81233108e-01 4.65314537e-01 1.87856531e+00 7.94295788e-01 4.89575982e-01 -5.06858230e-01 -1.03190385e-01 7.79361784e-01 3.65214169e-01 5.11930138e-02 1.74937755e-01 -1.47803104e+00 1.98213577e-01 7.09891140e-01 6.61193907e-01 -1.34055853e+00 -3.57315958e-01 1.63277965e-02 -2.59712696e-01 -6.55948222e-02 3.62427741e-01 -5.53824484e-01 3.95407826e-01 1.22166491e+00 5.90594053e-01 -7.71875158e-02 3.35167021e-01 8.10649931e-01 1.05103648e+00 5.78580916e-01 -2.75323868e-01 -9.18206155e-01 1.60059118e+00 -1.02864397e+00 -8.81217301e-01 -1.45940082e-02 8.23243141e-01 -9.49654937e-01 6.15361750e-01 6.00216210e-01 -1.01135206e+00 -1.38141975e-01 -6.23148680e-01 4.19571847e-02 -1.39416263e-01 -2.19036311e-01 5.13391018e-01 5.02036333e-01 -7.13772535e-01 6.17344379e-01 -1.32140055e-01 -8.46981943e-01 -4.68649477e-01 5.40069759e-01 -4.24219742e-02 3.92373025e-01 -1.07552755e+00 9.83774066e-01 -2.72462487e-01 6.91243559e-02 -2.90578663e-01 -1.24531120e-01 -3.23944062e-01 9.60598886e-03 7.62547135e-01 -4.95135576e-01 1.68233860e+00 -7.33201385e-01 -2.15572023e+00 6.46298409e-01 1.22229859e-01 -3.16058695e-01 3.07604939e-01 7.99900678e-04 -5.66424727e-01 8.90590101e-02 1.63372263e-01 2.44536981e-01 8.25432122e-01 -1.20600474e+00 -1.19096243e+00 -1.29834354e-01 8.40880692e-01 2.56790459e-01 1.18960977e-01 5.71303368e-01 -9.50094983e-02 -3.02025713e-02 -3.82140696e-01 -1.03229988e+00 -2.76874006e-01 -7.91434288e-01 -6.63168252e-01 -8.24590862e-01 8.47825587e-01 -4.98593986e-01 1.24147689e+00 -1.69789839e+00 1.57127768e-01 4.13582832e-01 3.17036092e-01 4.14325237e-01 -6.71574324e-02 1.01124656e+00 4.84561950e-01 3.59209985e-01 2.56404281e-01 -3.78540844e-01 2.73400903e-01 3.39468479e-01 -3.01568210e-01 5.48291355e-02 4.81905751e-02 4.81448472e-01 -8.41089427e-01 -3.72350335e-01 -1.21279575e-01 2.99455106e-01 -7.71134257e-01 5.96039236e-01 -5.35121739e-01 6.37088358e-01 -8.66859913e-01 -1.62886120e-02 2.33351931e-01 -4.40229058e-01 7.22067654e-01 -1.09978365e-02 -2.34613240e-01 9.91274476e-01 -8.97701502e-01 9.22508061e-01 -5.33176959e-01 1.49308920e-01 5.64520478e-01 -8.37110817e-01 9.80790019e-01 5.48468828e-01 1.96292490e-01 4.54160646e-02 4.68675315e-01 -9.87510085e-02 -3.96953449e-02 -7.08983779e-01 6.73309326e-01 3.53078306e-01 -9.53655615e-02 1.45410037e+00 -3.11891317e-01 8.11242163e-02 1.32243678e-01 6.78509891e-01 1.28932023e+00 -1.45710155e-01 5.97856045e-01 9.26808938e-02 8.80267203e-01 7.50682428e-02 2.27549165e-01 7.52947211e-01 1.37954473e-01 -7.66012594e-02 6.88183784e-01 -3.31690282e-01 -3.93239945e-01 2.49184249e-03 6.55189991e-01 1.46265543e+00 1.03136994e-01 -9.06312168e-01 -8.69894147e-01 -1.10624564e+00 -2.49483392e-01 1.02905726e+00 -3.75813842e-01 1.82563052e-01 -7.32948899e-01 -1.16012521e-01 8.68314877e-02 -9.90477800e-02 2.92947710e-01 -1.38340342e+00 -8.22736561e-01 5.82655728e-01 -8.30798030e-01 -1.05204535e+00 -6.99187100e-01 -1.00682981e-01 -4.56539690e-01 -1.21791255e+00 6.66571688e-03 -4.65356141e-01 5.41105568e-01 2.87715822e-01 9.07927155e-01 8.05874467e-01 2.88091809e-01 6.26065612e-01 -8.16166222e-01 7.60776028e-02 -9.56044436e-01 1.30272150e-01 -1.25533849e-01 1.53851748e-01 2.84832507e-01 -7.54615307e-01 -3.49517971e-01 9.17876244e-01 -3.84071052e-01 7.08795711e-02 -1.24308363e-01 5.91813684e-01 -3.68715256e-01 -1.23970926e-01 9.26702201e-01 -1.43694651e+00 1.22135806e+00 -6.53886080e-01 -1.23214275e-01 9.23675373e-02 -6.54889226e-01 -2.60778010e-01 6.83249056e-01 -5.32639861e-01 -1.36396658e+00 -2.64126360e-01 -3.22890103e-01 6.78005219e-01 -5.36004305e-01 4.42385823e-01 1.63073719e-01 2.45303094e-01 7.71643102e-01 -4.17311639e-01 1.43524200e-01 -6.36451483e-01 5.41891992e-01 1.22640085e+00 2.25941494e-01 -6.31326973e-01 4.17692304e-01 1.47561148e-01 -6.06881142e-01 -5.74066758e-01 -8.02386522e-01 -6.96767449e-01 -4.65829551e-01 -4.57656443e-01 6.39687777e-01 -9.59701315e-02 -1.75914419e+00 -2.72771448e-01 -1.66571081e+00 -1.33498594e-01 -2.03618735e-01 2.68450588e-01 -4.57603693e-01 3.77401233e-01 -7.19628513e-01 -1.25129414e+00 -4.81083393e-01 -9.66525137e-01 5.21692395e-01 1.16363548e-01 -1.16666234e+00 -9.52382207e-01 -1.02984957e-01 8.78531277e-01 6.73913658e-01 -1.47741526e-01 8.86908174e-01 -1.51767492e+00 -4.15660962e-02 -2.01191574e-01 9.51772034e-02 -6.82409033e-02 3.84273440e-01 1.98995769e-02 -8.11230838e-01 -6.68380782e-02 7.14157969e-02 -1.89116046e-01 -1.61839917e-01 -1.92165419e-01 1.33588865e-01 -1.12095356e+00 -4.13567007e-01 -5.58107674e-01 4.33078974e-01 5.82278907e-01 5.12654543e-01 1.55239895e-01 4.59214374e-02 1.29512334e+00 6.97663426e-01 6.45307899e-01 5.61652184e-01 1.01851749e+00 2.20313683e-01 2.50318289e-01 2.59536862e-01 -8.40004832e-02 3.88656467e-01 7.62387693e-01 -4.35793787e-01 -4.21284050e-01 -2.61845708e-01 3.52113396e-02 -2.33107090e+00 -9.34154093e-01 -1.22145399e-01 1.81686568e+00 8.30902159e-01 -1.05508706e-02 6.72040999e-01 1.04165159e-01 8.28764915e-01 -1.79326206e-01 -2.21188813e-01 -8.96251082e-01 4.29101408e-01 -2.49948546e-01 -1.43671945e-01 9.40878212e-01 -3.66434544e-01 7.77096093e-01 6.28146124e+00 2.74984837e-01 -7.62004614e-01 1.92409575e-01 5.41795015e-01 3.25686574e-01 -4.83002603e-01 2.90713221e-01 -9.44871604e-01 1.74777538e-01 1.03771162e+00 -1.30518526e-01 8.11747432e-01 6.86772525e-01 4.22500849e-01 -2.27378160e-01 -1.43016016e+00 5.28130531e-01 2.17285603e-01 -1.55763280e+00 -3.07529986e-01 2.75068581e-01 6.47157505e-02 -5.55617094e-01 -5.65891206e-01 2.78352886e-01 6.48131728e-01 -4.75001395e-01 2.58732647e-01 2.48745590e-01 -1.02795787e-01 -6.72941148e-01 8.77340496e-01 1.02597594e+00 -7.47817814e-01 -1.89602867e-01 -9.00261179e-02 -4.79104638e-01 4.12106037e-01 8.80953223e-02 -1.24525630e+00 3.57863814e-01 2.79762983e-01 5.79735279e-01 -7.76376352e-02 1.89162403e-01 -2.57893234e-01 5.60146511e-01 -1.65909499e-01 -4.62101877e-01 -1.28449038e-01 -5.75677514e-01 7.77242780e-01 1.15189350e+00 6.17607962e-03 8.53490293e-01 4.13579345e-01 6.42178655e-01 -1.67268533e-02 3.52255166e-01 -4.46270883e-01 -1.18397832e-01 5.78327596e-01 1.68464935e+00 -8.24612319e-01 -4.05813992e-01 -2.09319562e-01 9.82663929e-01 2.54002124e-01 2.60022968e-01 -3.57074082e-01 -1.31879508e-01 3.76859128e-01 1.96889356e-01 1.67667806e-01 4.13253218e-01 3.29292983e-01 -6.56897545e-01 -3.67399096e-01 -1.29235482e+00 4.05892968e-01 -6.91579878e-01 -1.28016973e+00 8.14314961e-01 -2.40575224e-01 -1.00253022e+00 -8.73714030e-01 9.79027376e-02 -1.02647030e+00 6.10915422e-01 -1.01134312e+00 -8.41018617e-01 1.79235294e-01 5.09187281e-01 5.06116033e-01 -2.46087760e-01 1.20716417e+00 1.04223542e-01 -2.84161747e-01 2.53453463e-01 -9.09284890e-01 -3.31730783e-01 6.73538446e-01 -8.90468299e-01 9.87936407e-02 1.42983779e-01 -1.85828313e-01 1.00450456e+00 1.13912845e+00 -6.58464193e-01 -1.49282372e+00 -5.18480361e-01 1.53310931e+00 -2.66768247e-01 6.14628017e-01 -2.61519074e-01 -7.35338569e-01 6.75506890e-01 6.35061622e-01 -8.09377253e-01 8.65308404e-01 3.74820471e-01 -7.02599883e-02 1.77542463e-01 -1.42840183e+00 5.82350254e-01 8.84663761e-01 -5.10635614e-01 -9.70325708e-01 6.49892569e-01 9.63458955e-01 -5.07471822e-02 -6.97754741e-01 -2.38044009e-01 3.79617810e-01 -9.00407970e-01 4.93375003e-01 -8.76210093e-01 1.24797620e-01 -2.96318978e-01 6.38978705e-02 -1.29881048e+00 -1.78775176e-01 -1.64688778e+00 -1.40030272e-02 1.50930142e+00 6.87992990e-01 -8.63333344e-01 4.83794838e-01 1.06086791e+00 -1.99675784e-02 -3.18249851e-01 -4.17666525e-01 -1.25582457e-01 -6.67847753e-01 -2.37234280e-01 6.52293205e-01 1.06037188e+00 1.05962813e+00 1.02157187e+00 -7.52783418e-01 1.25002405e-02 1.10941827e-01 2.35206231e-01 1.01953542e+00 -1.56936121e+00 -5.35957336e-01 -1.35441884e-01 3.63696247e-01 -1.33621705e+00 9.23170969e-02 -5.74858427e-01 1.87241778e-01 -1.70206535e+00 -1.73114508e-01 -2.59319901e-01 4.79001999e-01 3.89224559e-01 4.60237294e-01 -2.38645956e-01 1.82365745e-01 3.48926663e-01 -6.93253160e-01 -1.48880556e-01 9.72790182e-01 1.03647433e-01 -5.70550621e-01 8.08830082e-01 -1.28275931e+00 7.11076379e-01 6.50346041e-01 -4.81426805e-01 -3.87098402e-01 4.49705362e-01 5.31965733e-01 6.99965835e-01 -1.24106243e-01 -8.20841938e-02 6.54934227e-01 -2.77203590e-01 -6.15091145e-01 -5.18383682e-01 2.71903515e-01 -8.26060116e-01 2.97056228e-01 1.70915395e-01 -9.55952287e-01 -7.11289281e-03 -5.45606494e-01 4.60366845e-01 1.51151896e-01 -5.66914082e-01 3.03000629e-01 -6.46066368e-02 4.13916260e-02 -1.91218436e-01 -1.19980478e+00 -3.39230686e-01 8.32391441e-01 -8.51548389e-02 -8.09179187e-01 -1.14398253e+00 -1.04832828e+00 4.16093946e-01 1.16927512e-01 3.39837819e-01 4.46830153e-01 -7.01431692e-01 -6.32420540e-01 -2.48193696e-01 -2.21771076e-02 -5.63026011e-01 -2.21421629e-01 9.10154879e-01 3.29071097e-02 1.40446454e-01 1.47187978e-01 -1.51844621e-01 -1.71082544e+00 5.31591117e-01 8.63951892e-02 -3.12164545e-01 -8.40868831e-01 4.51492876e-01 -2.02056646e-01 -5.88078797e-01 5.71081460e-01 -2.54045337e-01 -1.02558553e+00 3.54707271e-01 9.10819769e-01 3.71724099e-01 -4.03514653e-02 -6.46718621e-01 -2.39702106e-01 1.51916638e-01 -2.68835634e-01 -2.83702821e-01 1.23306215e+00 -6.95833027e-01 -4.64427203e-01 3.44535053e-01 6.61631823e-01 3.57183307e-01 -5.61129808e-01 -4.31994736e-01 2.46019065e-01 -1.93942785e-01 -3.99321854e-01 -1.04517531e+00 -6.20532513e-01 1.42245755e-01 -2.10817218e-01 1.23813856e+00 5.82154512e-01 2.19978854e-01 8.65883589e-01 8.65005970e-01 3.84779543e-01 -1.20190477e+00 1.45300850e-01 5.94717085e-01 1.05987155e+00 -1.00563216e+00 2.96825375e-02 -6.74414217e-01 -1.17876422e+00 1.28990483e+00 3.10983241e-01 2.39143863e-01 8.86194289e-01 2.32563704e-01 2.47259662e-01 -4.65993673e-01 -1.40185428e+00 1.11189619e-01 -2.04735175e-01 6.25867546e-01 3.71100605e-01 1.31103839e-03 -5.92830658e-01 9.05752778e-01 -2.33661249e-01 -1.01793855e-01 8.68464231e-01 8.13280165e-01 -5.84375083e-01 -1.34902740e+00 5.97520173e-02 3.12622368e-01 -4.07587916e-01 1.42948985e-01 -1.09268808e+00 2.95274943e-01 -2.52607793e-01 2.06605530e+00 -1.17241517e-01 -4.91874665e-01 5.32096148e-01 -1.39017165e-01 -2.84648299e-01 -9.42581415e-01 -1.59597337e+00 2.73272783e-01 1.39564455e+00 -3.49546403e-01 -8.44198108e-01 -5.32856584e-01 -1.50984788e+00 -4.77017999e-01 -6.75422609e-01 1.00512874e+00 5.67031562e-01 1.39680123e+00 3.36109519e-01 7.75943026e-02 1.06966352e+00 -7.17578173e-01 -3.26836824e-01 -9.53627467e-01 -4.13633049e-01 5.24156094e-01 1.69437259e-01 -3.13073426e-01 -6.73390925e-01 -1.02946628e-02]	[12.714344024658203, 8.381360054016113]
cfffe0f0-b0e1-4015-a407-298bdf075c83	on-the-effectiveness-of-system-api-related	1805.09563	null	https://arxiv.org/abs/1805.09563v4	https://arxiv.org/pdf/1805.09563v4.pdf	On the Effectiveness of System API-Related Information for Android Ransomware Detection	Ransomware constitutes a significant threat to the Android operating system. It can either lock or encrypt the target devices, and victims are forced to pay ransoms to restore their data. Hence, the prompt detection of such attacks has a priority in comparison to other malicious threats. Previous works on Android malware detection mainly focused on Machine Learning-oriented approaches that were tailored to identifying malware families, without a clear focus on ransomware. More specifically, such approaches resorted to complex information types such as permissions, user-implemented API calls, and native calls. However, this led to significant drawbacks concerning complexity, resilience against obfuscation, and explainability. To overcome these issues, in this paper, we propose and discuss learning-based detection strategies that rely on System API information. These techniques leverage the fact that ransomware attacks heavily resort to System API to perform their actions, and allow distinguishing between generic malware, ransomware and goodware. We tested three different ways of employing System API information, i.e., through packages, classes, and methods, and we compared their performances to other, more complex state-of-the-art approaches. The attained results showed that systems based on System API could detect ransomware and generic malware with very good accuracy, comparable to systems that employed more complex information. Moreover, the proposed systems could accurately detect novel samples in the wild and showed resilience against static obfuscation attempts. Finally, to guarantee early on-device detection, we developed and released on the Android platform a complete ransomware and malware detector (R-PackDroid) that employed one of the methodologies proposed in this paper.	['Fabio Martinelli', 'Corrado Aaron Visaggio', 'Giorgio Giacinto', 'Michele Scalas', 'Francesco Mercaldo', 'Davide Maiorca']	2018-05-24	null	null	null	null	['android-malware-detection']	['miscellaneous']	[ 1.79320276e-01 -1.84917137e-01 -6.25396252e-01 1.74678236e-01 -2.32009754e-01 -1.02981699e+00 9.24241364e-01 4.10542190e-02 -1.67389899e-01 4.47025359e-01 -3.96919698e-01 -9.16042328e-01 -2.21765861e-01 -6.89163029e-01 -3.75905782e-01 -5.70425689e-01 -2.55817086e-01 1.17415629e-01 4.05865073e-01 -1.61765501e-01 6.10252500e-01 5.25149822e-01 -2.01293468e+00 1.31867766e-01 9.87465084e-01 9.70924854e-01 -2.32032850e-01 7.02928007e-01 3.74205299e-02 6.59447432e-01 -8.56659293e-01 -5.63122272e-01 7.30057731e-02 -2.68574327e-01 -4.24560815e-01 -4.54377800e-01 1.22673832e-01 -4.37567562e-01 9.71643925e-02 1.07259512e+00 6.88505322e-02 -4.87389982e-01 5.66419959e-01 -1.47863150e+00 -2.77670771e-01 4.66174185e-01 -4.08731818e-01 1.46344319e-01 8.03318918e-01 1.91230953e-01 4.37659204e-01 -4.12402660e-01 3.23407978e-01 9.64185238e-01 8.03789973e-01 6.83580101e-01 -9.25786972e-01 -8.36075902e-01 -1.77442372e-01 2.33922511e-01 -1.15519464e+00 -5.58009207e-01 7.22792506e-01 -8.07348132e-01 6.90224707e-01 7.04597294e-01 5.80971599e-01 1.53633559e+00 7.26032078e-01 1.82205334e-01 1.35662246e+00 -1.81352496e-01 4.28491056e-01 5.46933472e-01 5.36044002e-01 5.75494528e-01 8.02357972e-01 3.83270442e-01 7.65535235e-02 -8.08508396e-01 -5.93352877e-02 4.16004598e-01 -2.49314487e-01 -1.77279025e-01 -3.68236303e-01 8.64926457e-01 8.77206102e-02 7.26621628e-01 -1.34233430e-01 -4.21660841e-01 7.22611904e-01 -4.47258390e-02 1.46288037e-01 5.00456214e-01 -6.66494668e-01 -5.17847776e-01 -8.07508349e-01 -3.20236295e-01 9.93569314e-01 2.96800941e-01 7.42257774e-01 -2.36918386e-02 2.38110587e-01 2.04610005e-01 4.46474075e-01 4.96315092e-01 8.14170659e-01 -2.60256767e-01 6.73232898e-02 1.03038585e+00 -2.94878334e-01 -1.41597402e+00 -2.30278447e-01 -7.52732903e-02 -4.58366483e-01 2.57871389e-01 1.49130389e-01 -2.30159853e-02 -7.27447033e-01 1.31910384e+00 4.84642386e-01 4.48835522e-01 3.54337357e-02 3.01207215e-01 3.93520117e-01 3.35371882e-01 -1.11746572e-01 -4.15238053e-01 1.61228836e+00 -3.93901139e-01 -6.73150361e-01 1.66798070e-01 8.98863494e-01 -8.06973755e-01 1.26250601e+00 5.94178438e-01 -4.77396816e-01 -4.74363238e-01 -1.13369107e+00 6.73090637e-01 -9.68500614e-01 7.41383806e-02 4.22898889e-01 1.76118064e+00 -9.10986245e-01 5.68942606e-01 -9.66517329e-01 -4.24206495e-01 3.55943680e-01 5.09798586e-01 -1.74019754e-01 3.69247079e-01 -8.32172215e-01 8.02215576e-01 3.07885110e-01 -1.34633616e-01 -1.18922234e+00 -3.21558952e-01 -6.79422021e-01 5.04567707e-03 6.53337777e-01 -2.21515354e-02 1.00910318e+00 -7.85459816e-01 -1.67461145e+00 7.23871052e-01 1.36250138e-01 -5.01104176e-01 3.32718045e-01 -4.02046204e-01 -7.71338165e-01 1.54826595e-02 -2.65550464e-01 -4.29720640e-01 1.53562641e+00 -1.23750722e+00 -1.40851900e-01 -4.24584299e-01 3.03698778e-01 -7.36740947e-01 -8.33491981e-01 1.34574816e-01 1.53966740e-01 -2.81797349e-01 -4.70856994e-01 -1.20395148e+00 2.62874842e-01 -9.46799338e-01 -6.75439239e-01 7.35350773e-02 1.58930278e+00 -7.47572303e-01 1.61079884e+00 -2.19923067e+00 -2.40757808e-01 3.17353100e-01 3.37159872e-01 1.15979791e+00 3.76166463e-01 4.78996128e-01 1.07542694e-01 5.84421098e-01 -2.64114827e-01 -1.35854334e-01 -9.20516849e-02 1.73455328e-01 -5.91203809e-01 5.12642026e-01 -3.17707866e-01 5.17521560e-01 -6.69795990e-01 -3.37285280e-01 4.41796154e-01 7.08365679e-01 -5.85777104e-01 1.40431374e-01 -1.10905685e-01 3.53624493e-01 -4.07790691e-01 8.76220167e-01 7.10764229e-01 1.28402188e-01 4.77247149e-01 2.91701946e-02 -1.20545477e-01 3.93524021e-01 -7.23117769e-01 4.36443239e-01 -8.55341077e-01 1.65058360e-01 1.76587030e-01 -5.72060347e-01 7.68602669e-01 2.10485667e-01 2.84408838e-01 -1.29771069e-01 7.59979784e-01 6.44781470e-01 2.09927335e-01 -5.98267078e-01 3.96184236e-01 7.07513273e-01 6.30394518e-02 5.79787374e-01 -1.03956178e-01 3.05388391e-01 -1.17190838e-01 -6.26747981e-02 1.23300314e+00 -2.97274422e-02 7.88953960e-01 -9.16406959e-02 1.24353385e+00 -2.73506165e-01 3.68311442e-03 6.36681914e-01 -1.54171079e-01 -3.32257688e-01 6.13094807e-01 -1.53286025e-01 -2.63384014e-01 -7.68788755e-01 -8.55230242e-02 9.96835828e-01 7.81543627e-02 -8.72762501e-01 -1.19445467e+00 -1.45838618e+00 -2.51037717e-01 4.07980055e-01 -6.02536678e-01 -5.41179597e-01 -6.33366048e-01 -6.21402442e-01 9.67718840e-01 -7.74622783e-02 5.47611892e-01 -8.99685800e-01 -9.18833673e-01 -5.85782081e-02 4.40536916e-01 -9.73355234e-01 -2.11436316e-01 1.36324875e-02 -8.17899585e-01 -1.77932143e+00 -1.48656785e-01 -2.94783652e-01 4.67252553e-01 2.18276888e-01 5.38808465e-01 5.15541553e-01 -3.22344601e-01 4.02952909e-01 -5.35762489e-01 -1.70037284e-01 -8.51029515e-01 3.31212908e-01 3.34662616e-01 4.29327369e-01 2.93121964e-01 -4.11695391e-01 -1.18534721e-01 5.90285957e-01 -8.48281503e-01 -9.30947721e-01 7.00259507e-01 5.53565085e-01 7.58313015e-02 3.37057471e-01 1.84708461e-01 -1.12563562e+00 7.47515261e-01 -5.93119323e-01 -7.74155021e-01 8.55555683e-02 -8.71441782e-01 -2.30764255e-01 9.62986887e-01 -9.38537896e-01 -8.56600523e-01 8.45748037e-02 -5.63234389e-01 -2.02493399e-01 -3.97860944e-01 8.00058022e-02 -6.18689477e-01 -5.39072990e-01 6.71343267e-01 3.62347931e-01 6.06176108e-02 -4.40096796e-01 1.61279395e-01 9.74711299e-01 7.81736895e-02 -3.19868863e-01 1.00471842e+00 4.01287436e-01 -2.33574092e-01 -1.02450097e+00 -2.48327941e-01 -2.99678206e-01 -2.95932442e-01 -1.22451805e-01 8.75634134e-01 -2.13330194e-01 -1.32761014e+00 8.00015569e-01 -1.01601958e+00 4.38944511e-02 2.85183221e-01 2.57255107e-01 -1.30308062e-01 7.24746346e-01 -6.45815909e-01 -1.13945353e+00 -2.82093227e-01 -1.33477485e+00 8.66119206e-01 6.43694252e-02 -2.66887099e-01 -1.05450189e+00 2.59063005e-01 3.16825360e-01 7.50196159e-01 2.18045592e-01 6.46359086e-01 -1.14411139e+00 -1.72154993e-01 -4.96015310e-01 4.07945104e-02 3.87880147e-01 4.72138345e-01 4.59127337e-01 -1.12343061e+00 -3.43231618e-01 7.27159381e-01 1.22490272e-01 5.23447692e-01 -9.61510539e-02 1.00238836e+00 -9.17313874e-01 -6.83232427e-01 4.88731146e-01 1.17103541e+00 6.33822560e-01 6.56401157e-01 3.55725616e-01 7.67350256e-01 5.77377975e-01 6.00887418e-01 3.03756267e-01 9.09581855e-02 9.65724051e-01 8.66493046e-01 1.93987027e-01 4.33152825e-01 -2.76925147e-01 9.18104172e-01 4.09989208e-01 -1.88589856e-01 6.64727539e-02 -7.48410106e-01 -1.68191254e-01 -1.41521990e+00 -8.68832171e-01 -4.58570123e-01 2.45268583e+00 3.84136111e-01 5.10533035e-01 4.59116071e-01 6.29705906e-01 7.25964308e-01 2.27096334e-01 -2.85545796e-01 -7.80729115e-01 3.83047372e-01 3.60826194e-01 5.50295532e-01 5.88517845e-01 -1.17412245e+00 7.80867100e-01 5.28673172e+00 9.33657348e-01 -1.51497054e+00 6.43434167e-01 8.36219937e-02 4.93869513e-01 4.27942015e-02 6.37345016e-02 -9.84569728e-01 8.40217769e-01 1.35303891e+00 2.91188866e-01 4.85527217e-01 1.24181330e+00 2.93733682e-02 -8.16203505e-02 -6.94421768e-01 8.45635474e-01 2.67550200e-01 -9.29489017e-01 -2.45287016e-01 7.36031532e-01 2.60534823e-01 -3.17532867e-01 1.82174474e-01 4.34492052e-01 -1.57764897e-01 -7.57468879e-01 2.60487974e-01 1.11294361e-02 3.94874305e-01 -6.10738218e-01 1.00827157e+00 4.11478400e-01 -1.21287870e+00 -4.17830288e-01 7.56885558e-02 -2.95912832e-01 -4.11871597e-02 5.24961770e-01 -1.15188801e+00 5.60540676e-01 5.28894305e-01 6.02549493e-01 -9.82062042e-01 6.40408635e-01 -3.49860817e-01 8.92131448e-01 -8.87619630e-02 -2.40753993e-01 -1.85513556e-01 7.49588236e-02 4.71439213e-01 8.94830585e-01 3.05585206e-01 -5.26759982e-01 4.35424037e-02 5.28019786e-01 4.22045201e-01 2.48829886e-01 -9.88566279e-01 -2.94840097e-01 4.02371317e-01 1.44253182e+00 -7.68451512e-01 -3.12667698e-01 -1.16566814e-01 6.96502209e-01 -2.75957197e-01 -1.14076629e-01 -1.10597169e+00 -3.85623753e-01 8.23544443e-01 5.24954259e-01 4.51939180e-02 -2.31111452e-01 -1.06786355e-01 -1.15834010e+00 -2.65008658e-02 -1.21288168e+00 3.38003486e-01 1.77231580e-02 -1.04902160e+00 8.86009872e-01 6.91931881e-03 -1.21233273e+00 -4.13187891e-01 -8.33651960e-01 -8.01529109e-01 1.21813126e-01 -9.80677903e-01 -1.07318556e+00 -1.45173863e-01 6.97126210e-01 9.72608402e-02 -3.37969601e-01 7.40242481e-01 3.49972039e-01 -7.78415799e-01 6.74903214e-01 -2.66061515e-01 -4.23288308e-02 3.58264983e-01 -8.06701303e-01 1.58477396e-01 8.99962187e-01 3.83708365e-02 1.15916407e+00 3.65955323e-01 -8.54618728e-01 -1.60225499e+00 -7.50316679e-01 6.03904784e-01 -7.48487771e-01 9.08507586e-01 -6.30481541e-01 -8.89029920e-01 6.17545962e-01 -2.54320614e-02 -3.11493635e-01 8.20546806e-01 -1.21453650e-01 -5.75208008e-01 4.98879589e-02 -1.40486455e+00 3.38487267e-01 6.99411094e-01 -6.18859410e-01 -3.52184534e-01 6.61143437e-02 5.51685870e-01 -6.02376349e-02 -5.28958201e-01 4.69807535e-01 6.68599606e-01 -1.43184984e+00 9.21725690e-01 -2.56590396e-01 -8.84470046e-02 -3.67394209e-01 -6.90555722e-02 -6.04424477e-01 3.60098809e-01 -9.40511405e-01 -8.85773540e-01 1.51185572e+00 -2.26750746e-02 -1.28576922e+00 5.73039711e-01 -1.64543360e-01 -9.03620869e-02 -7.52057374e-01 -8.64343524e-01 -1.05567646e+00 -4.08890992e-01 -3.96826029e-01 7.86966324e-01 1.04343379e+00 -5.25656529e-02 1.32847384e-01 -5.16849160e-01 1.66029185e-01 3.81530225e-01 -3.67490441e-01 9.95256960e-01 -1.31364763e+00 -5.73843479e-01 -6.28661990e-01 -5.61165512e-01 -4.57208037e-01 2.97825754e-01 -5.96804798e-01 -4.21332508e-01 -4.87111688e-01 -2.15830594e-01 -4.32012737e-01 3.43234017e-02 5.55367708e-01 3.53296027e-02 6.46691084e-01 1.57970637e-01 3.26025337e-01 -2.09677786e-01 2.50888262e-02 5.60836256e-01 -8.21935534e-02 -5.80689549e-01 4.38575983e-01 -5.20870328e-01 1.03298736e+00 9.27326500e-01 -5.20717502e-01 -3.44085753e-01 4.33013648e-01 7.90347680e-02 -4.18714613e-01 4.59930748e-01 -1.17513406e+00 -2.11106658e-01 -3.22466381e-02 -1.78857848e-01 -3.77633274e-01 2.95832872e-01 -1.05452669e+00 1.96569607e-01 1.16588426e+00 3.94483030e-01 4.02221158e-02 1.23489439e-01 3.82457584e-01 1.31354809e-01 -2.70641476e-01 7.30671048e-01 1.48471832e-01 -4.17297810e-01 -8.81211758e-02 -6.88115001e-01 -3.77690315e-01 1.66908300e+00 -3.91693175e-01 -6.67215049e-01 9.06015337e-02 -4.68588203e-01 -6.13084078e-01 8.66621852e-01 4.15500909e-01 5.75204611e-01 -7.84725308e-01 7.62961954e-02 4.93629009e-01 1.98809914e-02 -1.15739989e+00 1.47348717e-02 1.17583549e+00 -3.85603040e-01 3.78897876e-01 -3.24702084e-01 -7.17267692e-01 -1.74892700e+00 1.22213006e+00 2.52203047e-01 -3.86254907e-01 -5.56164142e-03 1.08436331e-01 -2.90865481e-01 -6.19643688e-01 1.15065232e-01 -1.95399553e-01 -6.04715645e-01 1.87899753e-01 7.21888602e-01 6.84441864e-01 2.79018074e-01 -1.03193021e+00 -8.85894299e-01 8.28173876e-01 -2.05778033e-02 3.94713730e-01 6.09326601e-01 1.64311215e-01 -3.62784237e-01 1.77417308e-01 1.06942046e+00 8.77908170e-01 -5.30751646e-01 6.00674987e-01 2.55667210e-01 -5.98689735e-01 -4.32834893e-01 -6.30369365e-01 -7.51862109e-01 7.76437879e-01 8.99702966e-01 1.08450282e+00 1.09429061e+00 -5.85660711e-02 8.54623973e-01 1.14053264e-01 7.66857505e-01 -2.07729936e-01 1.56381384e-01 3.61184478e-01 1.83151484e-01 -1.01503313e+00 -1.07377961e-01 -7.34062374e-01 -8.80868062e-02 1.14037383e+00 6.80443168e-01 4.35398519e-02 8.93947065e-01 2.39247620e-01 -1.02664813e-01 -1.41990542e-01 -1.06134050e-01 -2.38052309e-02 3.22413385e-01 8.82257104e-01 1.37738094e-01 1.67475089e-01 -6.21845305e-01 6.72271073e-01 -2.21127912e-01 -1.73206285e-01 6.23023868e-01 1.00432420e+00 -3.47729683e-01 -1.51320791e+00 -7.58820474e-01 3.83441299e-01 -6.91128790e-01 1.40913114e-01 -9.13459420e-01 7.93911457e-01 5.75027168e-01 1.24773824e+00 -5.72446108e-01 -1.25491250e+00 1.16274081e-01 -2.21633822e-01 2.01166466e-01 -6.00128770e-01 -1.05852759e+00 -3.71396184e-01 -9.69457440e-03 -6.83007538e-01 -2.55504638e-01 -3.78264725e-01 -7.73243487e-01 -5.28245091e-01 -5.51567912e-01 2.04245731e-01 8.76536965e-01 1.00187922e+00 5.82658470e-01 2.34373569e-01 8.62052381e-01 -1.08522451e+00 -5.37336111e-01 -8.21963727e-01 -1.36502087e-01 5.36610410e-02 5.39925873e-01 -9.71201420e-01 -7.45236099e-01 -2.19945773e-01]	[14.414223670959473, 9.676346778869629]
142544c4-8063-448c-8705-0ca1ee0d7222	expressive-talking-head-generation-with	null	null	http://openaccess.thecvf.com//content/CVPR2022/html/Liang_Expressive_Talking_Head_Generation_With_Granular_Audio-Visual_Control_CVPR_2022_paper.html	http://openaccess.thecvf.com//content/CVPR2022/papers/Liang_Expressive_Talking_Head_Generation_With_Granular_Audio-Visual_Control_CVPR_2022_paper.pdf	Expressive Talking Head Generation With Granular Audio-Visual Control	Generating expressive talking heads is essential for creating virtual humans. However, existing one- or few-shot methods focus on lip-sync and head motion, ignoring the emotional expressions that make talking faces realistic. In this paper, we propose the Granularly Controlled Audio-Visual Talking Heads (GC-AVT), which controls lip movements, head poses, and facial expressions of a talking head in a granular manner. Our insight is to decouple the audio-visual driving sources through prior-based pre-processing designs. Detailedly, we disassemble the driving image into three complementary parts including: 1) a cropped mouth that facilitates lip-sync; 2) a masked head that implicitly learns pose; and 3) the upper face which works corporately and complementarily with a time-shifted mouth to contribute the expression. Interestingly, the encoded features from the three sources are integrally balanced through reconstruction training. Extensive experiments show that our method generates expressive faces with not only synced mouth shapes, controllable poses, but precisely animated emotional expressions as well.	['Jingdong Wang', 'Errui Ding', 'Jingtuo Liu', 'Junyu Han', 'Xiaoguang Han', 'Zhibin Hong', 'Hang Zhou', 'Zhizhi Guo', 'Yan Pan', 'Borong Liang']	2022-01-01	null	null	null	cvpr-2022-1	['talking-head-generation']	['computer-vision']	[ 3.72941457e-02 4.79522854e-01 5.10472581e-02 -5.47174454e-01 -5.45518160e-01 -4.45421875e-01 6.12229168e-01 -8.09269369e-01 2.59677559e-01 4.84962076e-01 6.27447367e-01 4.69114155e-01 4.37989324e-01 -3.50311339e-01 -6.91875517e-01 -8.89571846e-01 2.57509708e-01 -5.60574271e-02 -1.05328873e-01 -4.62701768e-01 -1.07271828e-01 5.22641957e-01 -2.11886287e+00 3.66477430e-01 6.41894519e-01 1.24241507e+00 -1.00301340e-01 6.96145773e-01 -1.18178263e-01 8.59495342e-01 -4.37998146e-01 -6.34164333e-01 -2.50743870e-02 -4.14283425e-01 -1.13014556e-01 4.63163495e-01 2.06591412e-01 -6.18661344e-01 -1.09375700e-01 7.22109675e-01 8.74099970e-01 -6.81188926e-02 5.48343301e-01 -1.51448810e+00 -5.22821128e-01 4.12497699e-01 -8.15041542e-01 -7.40538001e-01 7.51782715e-01 5.43016791e-01 6.25687718e-01 -9.50272262e-01 6.75835609e-01 1.62984324e+00 5.94569981e-01 1.02972293e+00 -1.11080623e+00 -9.29655433e-01 2.17393175e-01 -2.56285816e-01 -1.39817238e+00 -1.31452966e+00 1.17778361e+00 -4.25082088e-01 3.74712646e-01 2.52818078e-01 7.50899911e-01 1.41608500e+00 -1.67427376e-01 6.94531024e-01 7.59138525e-01 -3.42261881e-01 9.66981128e-02 3.34676713e-01 -5.04738092e-01 4.78861123e-01 -3.97250414e-01 2.90483445e-01 -7.91992307e-01 -6.41337112e-02 6.48993194e-01 -1.74970955e-01 -5.10904729e-01 -4.59016412e-01 -8.54880810e-01 7.34345078e-01 1.61689371e-01 -5.31817228e-02 -4.04092193e-01 2.65722722e-01 4.51695353e-01 -1.48899302e-01 3.56726497e-01 -3.20998654e-02 -1.08486913e-01 9.51562263e-03 -9.42249358e-01 1.80829003e-01 6.08824968e-01 1.13715279e+00 5.76425374e-01 5.23780227e-01 -5.56080163e-01 9.38255250e-01 4.82696891e-01 6.06649280e-01 2.66489655e-01 -1.12816525e+00 1.63216293e-02 2.27003515e-01 1.62885919e-01 -9.05402958e-01 -2.03822374e-01 2.12543577e-01 -6.51585937e-01 2.72697508e-01 -1.53204933e-01 -4.58559334e-01 -7.43545830e-01 2.24819040e+00 6.90317154e-01 -2.88814772e-02 -1.14050880e-01 1.03849065e+00 1.06968343e+00 6.12062693e-01 1.49536237e-01 -4.85160798e-01 1.51925445e+00 -7.35313654e-01 -1.48116767e+00 -1.51641920e-01 -1.94072537e-02 -6.18686438e-01 1.23853612e+00 1.75529554e-01 -1.37935531e+00 -6.10325575e-01 -9.63049233e-01 -2.82413453e-01 9.79280174e-02 2.05002680e-01 5.77322841e-01 6.78462207e-01 -1.17453873e+00 1.03372775e-01 -3.97035033e-01 -1.75954159e-02 1.65630236e-01 2.62908697e-01 -4.49825943e-01 4.16814834e-01 -1.07467270e+00 4.93603408e-01 -2.53349066e-01 7.70230293e-02 -7.99100518e-01 -5.82167327e-01 -1.27703547e+00 -5.58882169e-02 2.65812606e-01 -6.94516778e-01 1.36768031e+00 -1.36294711e+00 -2.45204020e+00 1.02727258e+00 -5.36294281e-01 3.11985500e-02 7.32506335e-01 -1.81435972e-01 -2.93072790e-01 3.52169126e-01 -1.14522733e-01 1.21936703e+00 1.34821999e+00 -1.81905770e+00 1.87163223e-02 -3.31576258e-01 -3.77537727e-01 1.44310489e-01 -3.22942257e-01 3.00346494e-01 -6.45467520e-01 -8.08253288e-01 -1.89308479e-01 -7.60885060e-01 1.88819975e-01 6.35286987e-01 -5.89355886e-01 8.18070769e-02 1.06333971e+00 -5.22230566e-01 1.08831310e+00 -2.38866043e+00 1.43617064e-01 -4.21831608e-02 3.20214629e-01 -1.14976214e-02 2.51196325e-03 2.92543799e-01 -2.80911177e-01 -9.89085734e-02 -3.99461761e-02 -9.47702467e-01 1.66749924e-01 5.06029129e-02 -4.71427590e-01 4.78811294e-01 3.37219238e-01 9.91536200e-01 -5.70178390e-01 -8.53355229e-01 2.50531942e-01 1.07928479e+00 -7.88631976e-01 3.97009373e-01 -1.36253044e-01 5.04403055e-01 -2.66245037e-01 8.05943787e-01 9.29943860e-01 2.97124118e-01 1.85139671e-01 -4.37380970e-01 -1.94249913e-01 -3.32703665e-02 -1.03622639e+00 1.42308354e+00 -4.40501481e-01 4.43039358e-01 9.61533785e-01 -3.00814390e-01 1.07824838e+00 6.69053257e-01 3.04951936e-01 -6.13446057e-01 5.30092716e-01 -1.71908036e-01 -5.92095077e-01 -8.57752264e-01 3.58515710e-01 -6.21878207e-01 -7.52418861e-02 1.09539703e-01 1.74335781e-02 -4.49267447e-01 -4.26140219e-01 -2.61743236e-02 1.79433703e-01 2.95477509e-01 1.45549670e-01 4.65810113e-02 5.24420321e-01 -8.50326061e-01 7.24397182e-01 -1.93855595e-02 -4.13212776e-01 9.26542938e-01 5.49928069e-01 1.83183804e-01 -7.26043463e-01 -1.02490878e+00 1.83753163e-01 1.27945924e+00 2.51742154e-01 -3.90491694e-01 -1.00645757e+00 5.01960032e-02 -1.27683878e-01 6.06033385e-01 -7.68112600e-01 -2.27593288e-01 -4.14975375e-01 1.09393023e-01 6.00632906e-01 4.92377430e-01 3.85760576e-01 -1.19618607e+00 -5.67454159e-01 -1.68686345e-01 -3.23058546e-01 -9.45907891e-01 -1.01352286e+00 -1.69468939e-01 -1.38201550e-01 -4.17000264e-01 -9.98712182e-01 -7.22931623e-01 4.93122399e-01 -1.15863222e-03 7.11432993e-01 -3.35936636e-01 -1.87510058e-01 2.93882340e-01 -8.56605694e-02 -6.13945961e-01 -3.00049692e-01 -6.16282642e-01 3.56675059e-01 6.87974632e-01 -1.03624634e-01 -8.45776498e-01 -6.68214142e-01 3.39847296e-01 -5.84701180e-01 2.70122588e-01 2.50409782e-01 5.33579290e-01 4.36447203e-01 -6.27792120e-01 5.72454393e-01 -2.86334664e-01 5.18416643e-01 -1.24620304e-01 -2.47199535e-01 2.08927854e-03 1.43586680e-01 -2.08057418e-01 4.09293532e-01 -8.61267686e-01 -1.40757549e+00 4.20807391e-01 -3.29832494e-01 -8.44541609e-01 -1.39258444e-01 -4.84172583e-01 -9.61615980e-01 1.51259294e-02 3.72426450e-01 4.30487618e-02 3.97589654e-01 -9.11600143e-02 7.61054039e-01 9.33977127e-01 7.84026504e-01 -5.71480930e-01 6.36936724e-01 7.97438025e-01 -3.18314344e-01 -1.13740909e+00 -3.15813690e-01 3.73559967e-02 -3.44198674e-01 -6.54897869e-01 9.68895793e-01 -1.03188694e+00 -1.35312474e+00 6.40022874e-01 -1.27373588e+00 -3.50570679e-01 -3.18249077e-01 1.75840363e-01 -7.75228381e-01 8.42597634e-02 -6.87669694e-01 -1.14391077e+00 -4.13596958e-01 -1.29172003e+00 1.59879386e+00 2.91764498e-01 -5.03951669e-01 -3.97816777e-01 1.32135283e-02 4.66914237e-01 4.95455503e-01 4.96782124e-01 4.07687634e-01 2.18153313e-01 -1.73556238e-01 -5.07158227e-02 -3.63514237e-02 1.56860664e-01 1.52862176e-01 4.75110650e-01 -1.74188972e+00 -1.26884937e-01 -4.29163948e-02 -5.97222447e-01 4.60036457e-01 6.41555369e-01 8.90676677e-01 -6.04177713e-01 -2.83536524e-01 9.06838894e-01 7.49813259e-01 2.59650022e-01 7.19173193e-01 -4.48483855e-01 5.43359101e-01 1.17589366e+00 3.88357282e-01 6.81048036e-01 2.88638473e-01 7.69399524e-01 4.13644940e-01 -3.10089111e-01 -2.07118720e-01 -6.93535388e-01 5.43479860e-01 6.35273337e-01 1.21413972e-02 -1.80197105e-01 -2.62023330e-01 2.14737296e-01 -1.34887075e+00 -9.30340707e-01 3.41084749e-01 1.78563619e+00 1.02663505e+00 -2.49948829e-01 2.41446450e-01 1.16363987e-01 8.70476723e-01 3.27897310e-01 -7.39600599e-01 -4.96686757e-01 -1.25475705e-01 6.20368421e-02 -1.98774859e-01 5.63702166e-01 -8.74259710e-01 9.56192255e-01 6.21381474e+00 6.62693620e-01 -1.53653538e+00 -1.08798712e-01 5.84896684e-01 -5.19779086e-01 -6.86413407e-01 -2.65901774e-01 -6.36780143e-01 4.12976295e-01 4.32226628e-01 -1.55597195e-01 1.81471109e-01 9.83748198e-01 5.05052447e-01 3.24716508e-01 -9.63536322e-01 1.24044681e+00 2.83024371e-01 -1.03612757e+00 2.49246940e-01 1.26134828e-02 3.12491983e-01 -7.61989832e-01 3.01214755e-01 1.71001464e-01 -3.93847004e-02 -1.07110476e+00 1.43707454e+00 6.00139260e-01 1.49941266e+00 -7.43669212e-01 -3.07404362e-02 6.50717393e-02 -1.40091336e+00 -4.61545289e-02 2.58296430e-01 1.06241688e-01 6.23013020e-01 1.89063206e-01 -3.18795770e-01 1.21673115e-01 7.27755427e-01 3.53337944e-01 1.34690329e-01 3.49014133e-01 -3.63837421e-01 2.36992285e-01 -6.60223663e-02 1.31055936e-01 -3.51296455e-01 6.24929108e-02 6.13742471e-01 1.00659585e+00 1.38610303e-01 3.47604692e-01 -2.22772717e-01 1.16875446e+00 -9.21656564e-02 -1.09856911e-01 -8.26726496e-01 8.67377669e-02 5.77060640e-01 1.31173992e+00 -2.29453877e-01 -4.28028889e-02 -7.16400519e-02 1.11178577e+00 -1.23528078e-01 4.82782662e-01 -1.07123041e+00 -5.38144112e-01 1.10525596e+00 5.17044365e-01 2.60726690e-01 1.33798495e-01 -6.51495717e-03 -9.66223896e-01 1.00609355e-01 -7.71093488e-01 -2.91558415e-01 -1.27702725e+00 -9.78345871e-01 7.10244238e-01 -1.84296221e-01 -1.11654723e+00 -3.87253225e-01 -2.98978657e-01 -8.00255239e-01 8.27438831e-01 -1.37698138e+00 -1.46574616e+00 -5.89059472e-01 7.37074316e-01 4.54121232e-01 3.03820133e-01 5.93333602e-01 2.62369871e-01 -6.27281725e-01 9.40594435e-01 -6.84544623e-01 3.24600078e-02 9.89794493e-01 -6.10299885e-01 4.42659855e-02 3.82265240e-01 -6.14903569e-01 6.94233179e-01 8.89374197e-01 -2.47052282e-01 -1.41537094e+00 -7.69114375e-01 5.71259737e-01 -1.11769646e-01 2.28712797e-01 -8.17340493e-01 -7.49246061e-01 5.24036527e-01 2.20081449e-01 4.73314850e-03 6.86276317e-01 -5.15803516e-01 -3.72739434e-01 -3.29652160e-01 -1.37849975e+00 7.26697922e-01 9.57286060e-01 -7.15776920e-01 -4.15660143e-01 -1.49637371e-01 1.01267457e+00 -3.37010443e-01 -2.91646421e-01 3.56529921e-01 8.80306780e-01 -1.26669681e+00 1.00703299e+00 -1.48846135e-01 4.68734711e-01 -2.29013324e-01 -6.44638762e-02 -9.67697084e-01 2.62303669e-02 -1.29719090e+00 4.87386808e-02 1.82843816e+00 -1.04730405e-01 -5.30256212e-01 5.75513422e-01 5.83430707e-01 -7.99851641e-02 -6.49992764e-01 -6.90080523e-01 -4.02646303e-01 -7.24311993e-02 -4.20686662e-01 7.43966103e-01 9.16642249e-01 2.73571759e-01 3.51532608e-01 -6.66350901e-01 -5.52303828e-02 4.38836604e-01 -8.38961676e-02 1.00819981e+00 -1.01171577e+00 -3.39650474e-02 -3.21789503e-01 -3.83108594e-02 -1.10659039e+00 2.59116024e-01 -3.63304764e-01 3.99388790e-01 -1.02068329e+00 9.32194665e-02 3.44523229e-02 5.86878240e-01 3.97960722e-01 6.48038015e-02 -4.78444286e-02 1.00289233e-01 -9.84980240e-02 -3.16746943e-02 1.08867443e+00 1.45845056e+00 1.96116880e-01 -4.09753382e-01 -1.37038931e-01 -8.73327792e-01 9.88657534e-01 3.45528811e-01 1.52144745e-01 -7.06271350e-01 -1.13923080e-01 -9.27984565e-02 5.17081141e-01 3.97695005e-01 -6.26321316e-01 1.33311927e-01 -1.44126669e-01 2.71654099e-01 -3.52420956e-01 1.03579831e+00 -4.59424943e-01 9.69347954e-02 1.28487207e-03 -3.35718602e-01 -3.19523722e-01 2.62005687e-01 3.42072308e-01 -1.84994936e-01 4.18633312e-01 1.19816673e+00 -2.75793057e-02 -2.02369601e-01 3.97131979e-01 -3.40668440e-01 -3.69363651e-02 1.10987210e+00 -4.97913867e-01 3.37363929e-02 -1.07183087e+00 -6.73065186e-01 2.22505152e-01 5.64809442e-01 3.52561951e-01 7.04059541e-01 -1.39792645e+00 -4.73437071e-01 6.04822218e-01 6.01752698e-02 5.66079877e-02 6.14113152e-01 6.91395044e-01 -2.28547662e-01 6.12341166e-02 -1.40433729e-01 -6.31731629e-01 -1.47959507e+00 6.29912317e-01 5.26111364e-01 5.43149352e-01 -5.78895986e-01 1.10167062e+00 6.89296007e-01 -3.07103425e-01 5.95935464e-01 -2.39352714e-02 -1.88692629e-01 3.81069481e-01 6.34184062e-01 8.61059129e-02 -4.60208029e-01 -9.77537572e-01 -3.17127883e-01 9.35144603e-01 2.28741065e-01 -3.60574156e-01 1.06966686e+00 -3.95940781e-01 1.39827624e-01 3.72334898e-01 1.19738245e+00 3.76209855e-01 -1.67919612e+00 2.50283062e-01 -6.83795571e-01 -3.50210071e-01 -1.45235598e-01 -3.85412782e-01 -1.23772991e+00 1.17962301e+00 3.13651890e-01 -2.45879039e-01 1.30769360e+00 1.06159322e-01 8.32541883e-01 -2.31601417e-01 2.66587824e-01 -9.62067544e-01 5.33095777e-01 -4.02624207e-03 1.32577896e+00 -8.69636714e-01 -4.52042252e-01 -6.98770642e-01 -1.17894602e+00 8.14032257e-01 6.12946153e-01 4.24182773e-01 5.97250700e-01 8.07991326e-01 2.64833987e-01 -1.34232044e-01 -8.38332474e-01 -5.00525795e-02 8.05094838e-02 9.07549083e-01 3.95414263e-01 -4.06308733e-02 2.47485429e-01 1.15246308e+00 -4.62847054e-01 1.80593595e-01 1.31951049e-01 8.09734941e-01 -3.59219402e-01 -4.28743869e-01 -5.12469769e-01 -3.34636807e-01 -2.13056803e-01 2.93084071e-03 -6.95865989e-01 6.69378638e-01 2.56956697e-01 9.67080534e-01 6.28272891e-02 -4.88034546e-01 5.57043552e-01 1.95857480e-01 3.54745686e-01 -2.56461382e-01 -2.95125872e-01 4.07563031e-01 -1.92888737e-01 -7.72001445e-01 -9.58016664e-02 -3.77697319e-01 -1.37920225e+00 -3.88913959e-01 -1.81166574e-01 -2.13473350e-01 5.36723912e-01 5.38663983e-01 5.50913334e-01 4.27852720e-01 8.45718324e-01 -1.74681377e+00 -2.85947114e-01 -9.04545963e-01 -6.51081324e-01 3.74595433e-01 7.31286168e-01 -9.20278132e-01 -8.36387038e-01 2.94975281e-01]	[13.225805282592773, -0.46099555492401123]
36ea9a51-913e-4b91-b1ab-efaac42e6c85	twitter-geolocation-using-knowledge-based	null	null	https://aclanthology.org/W18-6102	https://aclanthology.org/W18-6102.pdf	Twitter Geolocation using Knowledge-Based Methods	Automatic geolocation of microblog posts from their text content is particularly difficult because many location-indicative terms are rare terms, notably entity names such as locations, people or local organisations. Their low frequency means that key terms observed in testing are often unseen in training, such that standard classifiers are unable to learn weights for them. We propose a method for reasoning over such terms using a knowledge base, through exploiting their relations with other entities. Our technique uses a graph embedding over the knowledge base, which we couple with a text representation to learn a geolocation classifier, trained end-to-end. We show that our method improves over purely text-based methods, which we ascribe to more robust treatment of low-count and out-of-vocabulary entities.	['Timothy Baldwin', 'Taro Miyazaki', 'Afshin Rahimi', 'Trevor Cohn']	2018-11-01	null	null	null	ws-2018-11	['stock-market-prediction']	['time-series']	[-0.3552089 0.4883299 -0.41551867 -0.3866793 -0.5735259 -0.8787422 1.0879765 0.88318735 -0.81284493 0.79484403 0.7498671 -0.34456882 -0.29033965 -1.209563 -0.64525557 -0.3948548 -0.55624056 0.63947046 0.37306297 -0.38211495 0.1327938 0.3790643 -1.2451452 0.02328859 0.4269011 0.68526995 -0.32312936 0.4558135 -0.36256996 1.0395058 -0.66273785 -0.799868 -0.31544238 0.12508695 -1.1176133 -0.46151853 0.41645902 -0.09150088 -0.8069278 0.8252434 0.2838029 0.36942387 1.0766201 -1.3529474 -0.84271514 1.0097353 -0.3213846 0.5538338 0.47897074 -0.6143644 1.6968341 -0.946763 0.7412822 0.8967668 1.0927619 0.06271476 -1.0188748 -0.3734268 0.32894072 0.03036043 -1.7138922 -0.38465637 0.40258548 -0.40744138 1.3543593 0.38802886 0.28834358 1.0137577 -0.04820642 0.45569944 0.42745724 -0.5464479 0.01935089 0.2630755 0.17058736 0.820226 0.9126543 -0.43848935 -0.41692767 -0.5885196 0.35561475 0.02896658 -0.22023433 -0.5644097 -1.2044544 0.8871295 0.780952 0.69795215 -0.4116214 0.35605413 0.23108836 0.04660889 0.974267 0.63148135 -0.59784156 0.06465659 -0.8462718 0.18134896 1.3184968 1.0460528 0.96026444 -0.66670805 0.08479237 0.6576913 0.44686142 0.2571254 0.7999363 -0.15384199 0.51450914 0.64908135 0.24308693 -1.3340197 -0.6389931 -0.36000732 -0.35665286 -0.58149415 0.31128204 -0.2984894 -0.6659958 1.6889011 0.4040752 0.42801464 0.07477229 0.25142443 0.8439256 0.33353794 0.39652002 0.2378134 1.5925977 -0.6608865 -0.4464252 -0.55815136 1.3230027 -0.2612117 0.5575864 -0.40638316 -0.43306443 0.17564183 -0.6983206 -0.06257971 -1.3692584 -0.26805928 0.91791207 0.6407963 -1.0351273 0.62469596 -0.63194096 -0.7923518 0.31755626 0.31188264 -0.6417538 0.16053897 -1.4947953 1.0972048 0.746004 -0.3254248 -0.1060134 -0.6092554 -1.265632 0.15549341 0.18212561 -0.6683855 1.0792465 -0.46206528 -0.6406596 1.1094234 -0.18240447 -0.5195317 0.01749659 0.1091336 -0.79779947 0.01462393 0.45221853 0.13320667 0.6357138 -0.8798769 -0.96848536 -0.09220961 0.4030801 0.08520499 -0.87600875 -0.24177507 -0.26112047 -0.63825536 0.18172376 -0.7567349 -0.09244721 -0.3980322 -0.563685 -0.5325056 0.5282261 -0.36084303 1.5359924 -1.9239104 -0.4349637 0.55613893 0.6153359 -0.22056894 0.09151491 1.0864156 -0.11955386 0.32883433 0.30151552 -0.13612153 0.23699495 0.24039789 -0.43649498 0.5435021 0.18366165 1.0486894 -1.4021262 -0.61829454 -0.16480803 0.30300033 -0.33470553 -0.2616231 -0.03677524 -0.4568068 -0.74617356 0.5241568 0.2561916 -0.64242256 0.2503325 -0.103039 0.18682392 0.5148871 -1.003066 1.0934446 -0.65371716 0.77777827 -0.33430314 -0.88095593 0.38184914 0.302598 0.37290877 -0.09353014 0.10105209 0.12229438 -0.55817604 -0.6048761 0.74769306 0.05410568 -0.2325692 0.41277507 0.26932544 0.3117217 0.31308883 0.70110434 1.5299264 -0.35205266 0.62760335 -0.39444733 0.38121104 0.03222 0.05662096 0.94198745 0.10187309 0.17504336 0.48153326 -0.17584954 -0.8203876 -0.83892584 -0.2700027 1.5098891 0.09740651 -0.887283 -0.31841338 -1.1247251 0.55875874 0.7089311 -0.86862636 -0.20782387 -0.2614542 -0.6359158 0.61090285 0.5654482 -0.12408302 -0.5761686 0.0831418 0.36081967 -0.02974047 -1.2246088 -0.27595434 0.2672784 -0.63344634 -1.0989362 -0.7153157 -0.9499524 0.81443775 0.35507903 1.4564532 0.4724414 0.10185926 0.7442862 -0.5304578 -0.38607666 -0.12590623 0.47546175 0.3386961 0.10265588 0.7498225 -0.6101275 -0.5369628 0.13058065 -0.8417828 -0.5966408 0.4199707 0.93795246 0.03452377 0.17467813 0.5331705 -1.4013342 0.6493934 -1.118605 -0.27817482 0.34871435 -0.6833698 0.1809081 0.35535505 -0.5828253 -0.62051475 -0.21624076 0.06664196 0.11334559 0.0164 1.0983086 0.19939357 -0.34616733 1.0192871 -0.07807387 -0.645958 -0.31031987 0.6556974 0.74961954 0.2415205 -0.49425015 1.1198592 0.51374406 -0.09815507 -1.0136226 -1.100207 -1.1086215 -0.56034666 0.2823499 0.49809808 -1.1383177 -0.5191528 0.02382215 -0.813807 -0.05029807 -0.23539606 0.67249286 -0.10224097 0.2820562 -0.60251683 -0.8101113 0.06523304 -0.12958467 1.0989264 0.12213654 -0.4466605 -1.8256458 0.28949106 -0.15726623 0.47697124 0.10778012 0.95166844 -1.5620114 -0.23844993 -0.82111835 -0.32454902 -0.39195567 0.30710497 -0.13651802 -1.0920668 -0.2846245 -0.5886362 -0.17015086 0.9558885 -0.09234003 0.7690118 -0.6514832 -1.1758072 0.47622997 1.3741668 -0.6481018 0.30525568 0.70998967 0.9075121 0.614079 0.2785227 0.48231852 0.7401351 0.4227291 0.24467067 -0.05317201 0.25783584 -0.5866322 -0.04870924 0.56752294 0.10505684 -0.7748809 -1.1881745 1.0142672 -1.5794728 -1.130444 -0.09548815 2.077687 0.8314774 0.25845203 0.14211264 -0.07253288 0.70600456 0.38316303 -0.12731458 0.24388689 -0.14423405 0.11592147 1.131393 0.60571367 -1.3822517 0.9200603 6.5419774 0.6222864 -0.81623876 0.10765826 0.14437312 0.31584796 -0.5806649 0.13980597 -0.98773885 0.3598958 1.0775828 -0.6395697 0.0490633 0.9315994 -0.50169843 0.13420989 -1.2807066 0.8385096 0.18400408 -1.3924906 -0.10956656 0.1141779 0.61551344 0.3671463 -0.19463515 0.56177634 0.7306763 -0.8268655 0.51262915 0.32479933 0.5904977 -0.49150473 0.8319382 0.25100386 -1.2906908 -0.10310365 -0.36358023 0.14398907 -0.02072415 0.7106483 -1.2633325 0.49468753 0.39453864 0.7167591 -0.8254962 1.0955559 -0.47530228 0.6517166 -0.52214277 -0.4148589 0.359194 0.36153653 0.37917164 1.4808189 0.30640104 -0.01761435 -0.01537922 0.32453486 -0.5352426 0.2986719 -1.0377735 -0.397815 0.6982291 1.4422553 -0.8968255 -0.38108155 -0.61944616 0.85214615 0.67481726 0.47011182 -0.5644546 -0.84935075 0.6342103 0.21120714 0.3847811 -0.17504528 0.44179708 -1.3939706 -0.02656857 -0.15925084 0.71372503 -0.63703793 -1.6971501 0.40421352 0.12161602 -1.075412 -0.5489115 -0.748677 -0.5355865 0.70673585 -1.666128 -1.2566605 -0.14464888 0.49629572 -0.17744419 -0.07416801 0.9520022 0.41891587 -0.31687313 0.83506763 0.4223299 0.6966378 0.78815925 -1.5603913 0.77649516 0.54366624 0.72267336 0.87040275 0.75626135 -0.617869 -1.1360271 -1.0785317 1.6622072 -1.0670046 1.4352913 -0.49529508 -0.8448823 1.1615491 -0.1123521 0.40539587 0.8996431 0.9159304 -0.64731747 0.20990354 -0.97574264 0.6128468 1.1173444 -1.0166618 -0.8615351 0.8884714 0.7663604 -0.21761827 -0.9012016 -0.07835517 0.29944474 -0.16364582 1.1516719 -1.025287 -0.06901438 0.02076828 0.05340747 -1.4449896 -0.46085432 -0.38455224 -0.49834073 1.4433604 0.8425763 -1.0650134 0.93910366 0.73393446 0.3766029 -0.3245877 -0.8498845 -0.970974 -0.02649198 -0.11046444 0.6910818 1.58756 0.5083 0.51156116 -0.0527606 0.4041541 0.38454488 -0.26003924 0.35478866 -1.738807 0.03254054 -0.2704357 -1.0826156 -0.8340253 0.45901525 -1.1337975 -0.12097287 -1.5299954 -0.12227965 -0.8990672 -0.49327776 0.5181914 -0.08303054 0.36949363 -0.49956468 0.1807644 -0.8458027 0.1713394 0.493637 -0.30328745 0.05461432 -0.08756802 -0.9009358 0.8070869 0.4902655 -1.0012205 -0.2878755 -0.3767191 0.90047526 -0.351418 0.3501803 -0.7924232 0.6543276 0.06538584 0.2880138 -0.1822197 0.27400216 -0.9647597 -0.32887366 -0.03644921 -0.46692544 -0.07374165 -0.21657291 0.9776945 -0.24814916 -0.52601486 -0.04584429 -0.0206488 -0.8558017 0.3541267 -0.3074786 0.5614971 0.82296026 -0.08647741 -0.4107969 -0.6389295 -0.68469584 0.20694396 0.46711317 0.3769764 0.16418031 -1.3790449 -0.5589528 -0.18043572 0.6932308 -0.2415928 -0.13065109 0.76015174 -0.39890227 0.38514853 0.41940004 -0.12772097 -1.0394171 0.63113326 0.27800882 -0.1924034 -0.5449219 1.1163411 0.04699605 -0.4679601 0.21895885 -0.15290496 -0.47485587 0.6008754 0.5982967 -0.04129493 0.30834806 -0.7275868 -0.6163813 0.25941014 -0.11853328 -0.10411831 1.4218718 -0.20871484 -0.16625561 0.50214905 1.4696115 0.53996706 -0.34278345 -0.6134186 0.6321482 -0.43836448 0.02963785 -0.33065283 -0.4799621 0.32862097 0.05591357 0.8813394 0.49475816 0.38700345 0.54710686 1.0502902 0.4611593 -0.98661214 -0.36842242 0.8267144 0.31873703 -1.1631978 0.13818315 -0.4170449 -0.2871202 1.046474 0.06275731 0.04720256 1.1266621 0.00961136 -0.02618538 -0.5690067 -0.6867966 -0.6388879 0.50311077 0.68871665 0.49112505 -0.1281869 -0.03545628 0.33176544 -0.28499463 -0.42632672 0.41955915 1.1481252 -0.45724192 -0.92989117 0.02855368 0.8273396 -0.7573296 -0.47178265 -0.35369927 0.9345197 -0.04850611 0.8504471 0.26053557 -0.37463358 0.15009889 0.30439416 0.09986096 -0.7867794 -0.4002467 -0.8017778 0.6015454 -0.28172183 -0.30164367 -0.54450876 -0.9131962 -0.3996815 -0.70689195 0.48858312 0.5767193 0.8525879 0.37811822 0.20416667 0.5515138 -0.56754017 -0.26689625 -0.8702492 -0.78477305 0.6236923 0.4764254 -0.7459828 -0.67203504 -0.20114845]	[9.284517288208008, 8.392631530761719]
311596bf-115b-4bff-b6da-1156e7c46086	from-synsets-to-videos-enriching-italwordnet	null	null	https://aclanthology.org/L14-1559	https://aclanthology.org/L14-1559.pdf	From Synsets to Videos: Enriching ItalWordNet Multimodally	The paper describes the multimodal enrichment of ItalWordNet action verbsÂ’ entries by means of an automatic mapping with an ontology of action types instantiated by video scenes (ImagAct). The two resources present important differences as well as interesting complementary features, such that a mapping of these two resources can lead to a an enrichment of IWN, through the connection between synsets and videos apt to illustrate the meaning described by glosses. Here, we describe an approach inspired by ontology matching methods for the automatic mapping of ImagAct video scened onto ItalWordNet sense. The experiments described in the paper are conducted on Italian, but the same methodology can be extended to other languages for which WordNets have been created, since ImagAct is done also for English, Chinese and Spanish. This source of multimodal information can be exploited to design second language learning tools, as well as for language grounding in video action recognition and potentially for robotics.	['Valeria Quochi', 'Monica Monachini', 'Irene Russo', 'Irene De Felice', 'Roberto Bartolini']	2014-05-01	null	null	null	lrec-2014-5	['ontology-matching']	['knowledge-base']	[ 1.92861110e-01 4.46466118e-01 -1.63417697e-01 -1.60940602e-01 -1.80128217e-01 -5.56828797e-01 1.25656271e+00 2.42621765e-01 -8.67375553e-01 8.47398818e-01 5.35113096e-01 2.67095536e-01 -5.28750002e-01 -8.17529380e-01 -4.28456485e-01 -5.22416711e-01 -2.02831533e-02 4.37855124e-01 5.66063762e-01 -7.48595476e-01 -1.68835092e-02 5.52800536e-01 -2.09341979e+00 8.30483079e-01 1.33640900e-01 6.32506907e-01 5.87946236e-01 2.93828756e-01 -6.53377175e-01 9.52282012e-01 -5.05685449e-01 -6.57503068e-01 -5.75134568e-02 -4.50115055e-01 -1.15804660e+00 1.48585021e-01 4.27534878e-01 2.27024421e-01 -2.22880796e-01 1.07398415e+00 -1.85169117e-03 2.28760943e-01 6.36736631e-01 -1.25332940e+00 -2.34194212e-02 9.55563903e-01 3.61748427e-01 -2.55368412e-01 1.00835025e+00 -7.70538449e-02 8.67480814e-01 -4.91789639e-01 1.48744261e+00 1.47996581e+00 5.01771808e-01 5.12217104e-01 -8.24412823e-01 -6.12891689e-02 -1.05245840e-02 6.34926558e-01 -1.14257979e+00 1.66355949e-02 3.86009216e-01 -5.34270525e-01 9.09927368e-01 2.32897416e-01 1.24503994e+00 1.48485649e+00 -2.02811956e-01 8.44633877e-01 9.85541344e-01 -7.49090791e-01 1.42787993e-01 5.33158720e-01 1.32388156e-02 6.33979857e-01 2.75379151e-01 -3.51076990e-01 -6.97396934e-01 4.34237123e-01 6.18423641e-01 -1.99127808e-01 -1.42709076e-01 -4.26798075e-01 -1.50254631e+00 6.17824197e-01 2.01306641e-01 1.33857727e+00 -2.60499299e-01 1.14732705e-01 7.88165629e-01 2.94110656e-01 -1.11110769e-01 6.94283843e-01 -3.30086231e-01 -4.74350452e-01 -2.69017011e-01 3.21297348e-01 8.99716318e-01 1.07818556e+00 8.39182079e-01 -2.21680909e-01 2.39319596e-02 5.10541379e-01 2.69331425e-01 4.51613158e-01 7.52048731e-01 -8.81262243e-01 2.74828404e-01 1.00057328e+00 5.50214536e-02 -9.57354128e-01 -4.15291816e-01 4.37285453e-01 -7.75240660e-02 1.75167039e-01 6.00033760e-01 7.62793645e-02 -3.40748876e-01 1.46893990e+00 1.64356276e-01 -9.32151824e-02 5.81139207e-01 7.46558666e-01 9.96293306e-01 3.77787441e-01 3.63562942e-01 -6.01830333e-02 1.80074084e+00 -3.72815311e-01 -9.60334182e-01 2.14242041e-01 9.08696532e-01 -8.45985651e-01 1.07215583e+00 6.05157971e-01 -8.40843499e-01 -5.70236206e-01 -9.59973097e-01 1.28471246e-02 -1.10400677e+00 2.83800334e-01 6.27015889e-01 5.23580730e-01 -9.06731248e-01 5.45030117e-01 -4.41428125e-01 -1.30490255e+00 4.13818331e-03 1.61815435e-01 -7.54428804e-01 1.15467265e-01 -1.35981095e+00 1.23766029e+00 1.24727309e+00 -2.14984268e-01 -4.97697532e-01 3.19311656e-02 -9.34481859e-01 -3.42881054e-01 5.83701015e-01 -1.98846146e-01 7.77649879e-01 -1.48356950e+00 -1.59482038e+00 1.44412470e+00 3.44253898e-01 -5.90079129e-01 5.76196849e-01 -1.96101576e-01 -6.65722609e-01 5.33736467e-01 2.56322250e-02 8.46712649e-01 4.66949373e-01 -1.05064845e+00 -8.74208748e-01 -7.70822912e-02 8.13005149e-01 1.28592357e-01 -8.33168924e-01 2.32804909e-01 -4.90525424e-01 -7.01373577e-01 -2.20643699e-01 -5.88110566e-01 1.63443178e-01 -1.76630706e-01 1.68692693e-01 -2.42650494e-01 5.68868577e-01 -5.26098430e-01 1.07605624e+00 -2.12379789e+00 6.37383461e-01 3.16337436e-01 -1.56726316e-01 1.06007501e-01 -1.83372661e-01 9.43630159e-01 -7.09243342e-02 -1.07738242e-01 9.45192128e-02 3.16219598e-01 3.47378820e-01 6.61315918e-01 -4.63109463e-03 1.67003404e-02 -3.94825265e-02 4.25285250e-01 -1.14041173e+00 -7.13195145e-01 4.38687682e-01 2.98918486e-01 -3.42266560e-01 -1.31779149e-01 -5.10556579e-01 1.90851003e-01 -5.74043751e-01 1.80289030e-01 3.70733552e-02 3.37137520e-01 7.28759825e-01 -3.29026431e-01 -4.35881197e-01 -2.27265581e-01 -1.34139419e+00 1.95703530e+00 -5.42234242e-01 6.25243008e-01 -2.92152375e-01 -1.09304810e+00 1.07667625e+00 6.76470876e-01 8.54923964e-01 -4.37128603e-01 3.03777963e-01 4.07287121e-01 -3.05488646e-01 -1.03976834e+00 5.86036861e-01 -6.12081774e-02 -7.33385459e-02 1.55482113e-01 5.04766166e-01 -2.01951608e-01 8.35443795e-01 -1.09770380e-01 8.31757963e-01 9.33387280e-01 5.83982706e-01 -3.70300382e-01 1.17260623e+00 3.82669896e-01 -1.70462832e-01 3.52449059e-01 3.32987368e-01 -6.85411319e-02 6.49440110e-01 -5.47823966e-01 -7.65875578e-01 -8.07328880e-01 -1.49189502e-01 9.00646627e-01 1.74464732e-01 -8.47917616e-01 -9.69605982e-01 -5.30171573e-01 -5.50918519e-01 4.20413733e-01 -4.12618488e-01 1.27626374e-01 -4.96222228e-01 -1.11866646e-01 6.21823430e-01 1.36966661e-01 5.66571414e-01 -1.53945434e+00 -1.07648933e+00 2.18061790e-01 -2.48549238e-01 -1.64209759e+00 4.33808804e-01 3.76545228e-02 -5.43946207e-01 -1.23876631e+00 -5.18781066e-01 -8.34821999e-01 2.13488683e-01 -1.72757372e-01 1.17185354e+00 2.14539796e-01 -3.72245222e-01 1.02355385e+00 -1.09211969e+00 -6.62471175e-01 -7.69347072e-01 -5.36810979e-03 6.78474307e-02 9.98297259e-02 5.89376211e-01 -2.71449357e-01 9.83575284e-02 2.10914046e-01 -1.37335753e+00 -1.62457526e-01 3.58233601e-01 3.21382493e-01 2.76355296e-01 -3.28732401e-01 5.35305068e-02 -7.74974167e-01 2.41122648e-01 -7.91940391e-02 -7.56665647e-01 3.91611129e-01 2.17533767e-01 4.93062893e-03 3.88758630e-01 -4.14957345e-01 -1.08006203e+00 1.28633648e-01 -2.65198588e-01 -1.39247403e-01 -6.96465254e-01 4.52037662e-01 -5.65588117e-01 -2.05507547e-01 6.78671300e-01 -1.19477555e-01 -1.75824746e-01 -3.98284018e-01 5.80389619e-01 4.72650319e-01 1.98868200e-01 -6.14443302e-01 5.54009259e-01 4.45609957e-01 3.16542089e-01 -1.36710310e+00 -2.16967344e-01 -6.11498892e-01 -1.02541482e+00 -6.71533406e-01 1.64472830e+00 -6.08594298e-01 -8.38352382e-01 1.01017058e-01 -1.33382654e+00 -1.63095593e-01 -8.11239362e-01 9.74604189e-01 -1.04693186e+00 3.70027870e-01 -1.88872188e-01 -6.10455513e-01 4.34120595e-01 -1.04753923e+00 8.91138792e-01 -7.25546107e-02 -4.34353530e-01 -1.14135528e+00 -8.24011676e-03 1.21014409e-01 -2.76425898e-01 2.04528853e-01 9.86464977e-01 -8.88152599e-01 -5.51649392e-01 -2.47152209e-01 1.75730929e-01 2.59133190e-01 -1.31803840e-01 -1.92569107e-01 -6.40729189e-01 2.63016492e-01 -2.49868885e-01 -3.84330422e-01 4.38290536e-01 -2.22854570e-01 5.52755117e-01 -3.90529111e-02 -3.15960854e-01 9.83807817e-02 1.75812352e+00 4.09661323e-01 9.62314844e-01 7.07826495e-01 2.63700843e-01 9.43267643e-01 1.10945070e+00 4.31242853e-01 -1.44041985e-01 1.17771709e+00 4.03127581e-01 2.21761078e-01 -2.06403077e-01 -8.29726532e-02 6.33193493e-01 6.70270741e-01 -6.31455600e-01 -1.56131983e-01 -9.25012290e-01 3.81424963e-01 -1.83628130e+00 -1.36848092e+00 -4.08716202e-01 2.12917757e+00 3.33714932e-01 -6.20734170e-02 3.79781306e-01 6.99980035e-02 4.50377375e-01 1.28731951e-01 6.31497085e-01 -4.02129710e-01 -3.03191692e-01 3.87070268e-01 1.73652589e-01 5.22135079e-01 -1.06778252e+00 1.18512201e+00 5.75242567e+00 9.65887010e-01 -7.63797700e-01 3.37097526e-01 -3.50917399e-01 3.06211144e-01 -2.60335803e-01 -5.33282459e-02 -6.92392230e-01 1.05209105e-01 6.93649232e-01 1.74498990e-01 4.01458979e-01 6.31052613e-01 1.13153927e-01 -2.25320026e-01 -9.72984731e-01 1.12494779e+00 4.83403236e-01 -1.47346437e+00 3.37099373e-01 -9.33505446e-02 2.99304903e-01 -3.39197099e-01 -8.11853468e-01 1.32799551e-01 -8.06291401e-02 -5.57467461e-01 9.32421148e-01 9.11368906e-01 5.13419449e-01 -5.49154162e-01 7.74408698e-01 -8.21990371e-02 -1.28924346e+00 -1.30215466e-01 -3.94442707e-01 2.58537512e-02 1.35096207e-01 -2.48623893e-01 -3.65756094e-01 9.79434073e-01 7.26498067e-01 8.86485815e-01 -5.40971458e-01 7.97179520e-01 -3.97341937e-01 2.31444016e-02 -2.82345921e-01 -7.51069427e-01 3.83024126e-01 -5.99139452e-01 9.29972410e-01 1.35719097e+00 4.38689083e-01 -1.81511045e-01 6.72492087e-02 4.80559766e-01 3.51644874e-01 8.52277696e-01 -9.83773768e-01 -2.30600417e-01 -9.92495790e-02 1.12858891e+00 -1.19950223e+00 -5.23704708e-01 -5.32414138e-01 1.06272852e+00 -1.29258096e-01 1.27750576e-01 -8.28153551e-01 -4.94740874e-01 4.86463755e-01 1.23516805e-01 1.73313349e-01 -2.12048188e-01 4.15511340e-01 -1.10956383e+00 -1.14736974e-01 -8.75377238e-01 3.45151156e-01 -1.03150880e+00 -9.06267524e-01 8.53873551e-01 7.88044035e-01 -1.51331592e+00 -3.78790110e-01 -1.42734289e+00 -2.12934683e-03 1.72727868e-01 -7.39340782e-01 -1.35973322e+00 -3.32735181e-01 8.59133124e-01 4.95266199e-01 -6.24778748e-01 1.13842380e+00 2.65858680e-01 1.79744139e-01 -2.45451584e-01 -2.14278609e-01 1.32679625e-03 4.33487594e-01 -1.26390755e+00 -3.74208242e-01 6.16907358e-01 6.27612233e-01 1.49624810e-01 8.13649952e-01 -4.34266359e-01 -1.07483327e+00 -4.44603264e-01 1.18733668e+00 -4.57536995e-01 1.00448310e+00 -1.89879850e-01 -4.18550938e-01 5.99846959e-01 8.04720283e-01 -5.92940450e-01 5.11906981e-01 -1.46767631e-01 -1.37084007e-01 -8.73454288e-02 -7.70361304e-01 9.22162473e-01 1.46539176e+00 -4.14696634e-01 -9.81787801e-01 7.73691714e-01 4.17406887e-01 -4.85228226e-02 -1.17328680e+00 -7.64374388e-03 5.17821372e-01 -1.07646167e+00 8.90244186e-01 -8.40633631e-01 3.48547786e-01 -1.25976324e-01 -3.27946752e-01 -8.68761122e-01 4.54350740e-01 -6.49139225e-01 5.24921119e-01 1.28676438e+00 1.29552796e-01 -5.70264161e-01 3.15379232e-01 -1.75515220e-01 -1.68953747e-01 -1.83312278e-02 -1.11456311e+00 -8.76326382e-01 -3.57957840e-01 -8.16338420e-01 5.36464095e-01 8.81713808e-01 4.87608284e-01 2.09649831e-01 -9.31903571e-02 -5.00358343e-01 -1.23899169e-01 -3.30542922e-01 8.49210203e-01 -1.32270157e+00 -2.03156695e-01 -5.91289341e-01 -1.19671059e+00 -4.98392701e-01 4.95079517e-01 -9.18121815e-01 -1.45874307e-01 -1.41220915e+00 -3.24694097e-01 4.65199910e-02 5.47815897e-02 5.02622485e-01 6.41886711e-01 5.09747744e-01 6.45829856e-01 -5.70970513e-02 -6.06725872e-01 1.74665958e-01 1.02279782e+00 -4.45608161e-02 8.84800553e-02 -4.50535804e-01 1.38025746e-01 1.20146847e+00 4.45448488e-01 -3.09480190e-01 -3.86154085e-01 -1.95426196e-01 7.87215769e-01 -2.12336302e-01 3.98446143e-01 -1.40387356e+00 -2.31793672e-01 -1.16371498e-01 -1.22180089e-01 2.44741067e-02 4.89497244e-01 -1.57327569e+00 2.47306332e-01 5.97101092e-01 -2.95726627e-01 1.49650186e-01 1.51071548e-01 2.64494777e-01 -5.30602217e-01 -1.06665754e+00 4.76532191e-01 -5.98227799e-01 -1.47472656e+00 -3.97508025e-01 -1.01489270e+00 -8.87329876e-03 1.31971753e+00 -6.64960146e-01 1.20522864e-01 -3.69081289e-01 -1.14979744e+00 -3.13863814e-01 4.17783767e-01 5.30279458e-01 3.30706000e-01 -1.42796850e+00 -2.01167166e-01 -4.95266095e-02 5.87303340e-01 -9.13926125e-01 2.56624430e-01 8.06239426e-01 -9.69573796e-01 4.94763762e-01 -8.14335167e-01 -4.02573436e-01 -1.51060879e+00 6.23551726e-01 2.54720479e-01 -2.07043529e-01 -5.91805339e-01 1.60418108e-01 -2.55058706e-01 -1.68120369e-01 2.46554077e-01 -4.72097367e-01 -1.02690887e+00 6.78071022e-01 3.05022091e-01 2.65959769e-01 -1.29381627e-01 -1.19824004e+00 -3.33020478e-01 7.98732817e-01 8.27064931e-01 -4.36889321e-01 1.07861137e+00 9.38275922e-03 -3.45750511e-01 6.23285174e-01 8.89773726e-01 2.09039241e-01 -4.48667496e-01 2.99194545e-01 4.76888508e-01 -2.40010634e-01 -5.63595474e-01 -6.12039864e-01 -6.32619143e-01 6.84420645e-01 7.72797763e-01 3.60662937e-01 9.69081402e-01 1.80714026e-01 2.45159224e-01 8.08072507e-01 7.00592697e-01 -1.23106909e+00 2.45048299e-01 6.95592344e-01 1.15761256e+00 -6.14488184e-01 -1.22733377e-01 -5.59376419e-01 -7.81121016e-01 1.82107902e+00 2.71508753e-01 1.51196480e-01 5.37874818e-01 6.83485568e-02 8.32625628e-02 -3.76994312e-01 -2.11607873e-01 -1.00520396e+00 1.76413938e-01 9.56513762e-01 3.96870404e-01 -1.08386599e-01 -1.16943192e+00 3.52754235e-01 9.09363953e-05 3.52254957e-01 6.86288416e-01 9.42079961e-01 -1.86156064e-01 -1.61076713e+00 -4.91418809e-01 -1.76477730e-01 -2.49809191e-01 1.11165069e-01 -7.06770539e-01 1.76531816e+00 8.49041820e-01 4.95420247e-01 2.71653265e-01 -2.65524447e-01 7.36236870e-01 3.43092173e-01 9.32349682e-01 -6.05097115e-01 -8.40424299e-01 -3.66380587e-02 5.65489471e-01 -6.51903749e-01 -1.36409771e+00 -6.74224257e-01 -1.21339440e+00 2.38606006e-01 2.77544439e-01 1.40183628e-01 5.55529833e-01 1.37899685e+00 -3.42115283e-01 3.87916356e-01 -2.27508202e-01 -8.37798238e-01 1.21827848e-01 -8.09647441e-01 -6.38513863e-01 7.42300808e-01 -4.85929608e-01 -8.86606932e-01 1.31130412e-01 4.90225047e-01]	[10.44688892364502, 0.5905734896659851]
1fdafd2c-306d-4771-b7be-bf340ec9d582	exploring-structure-wise-uncertainty-for-3d	2211.00303	null	https://arxiv.org/abs/2211.00303v1	https://arxiv.org/pdf/2211.00303v1.pdf	Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation	When applying a Deep Learning model to medical images, it is crucial to estimate the model uncertainty. Voxel-wise uncertainty is a useful visual marker for human experts and could be used to improve the model's voxel-wise output, such as segmentation. Moreover, uncertainty provides a solid foundation for out-of-distribution (OOD) detection, improving the model performance on the image-wise level. However, one of the frequent tasks in medical imaging is the segmentation of distinct, local structures such as tumors or lesions. Here, the structure-wise uncertainty allows more precise operations than image-wise and more semantic-aware than voxel-wise. The way to produce uncertainty for individual structures remains poorly explored. We propose a framework to measure the structure-wise uncertainty and evaluate the impact of OOD data on the model performance. Thus, we identify the best UE method to improve the segmentation quality. The proposed framework is tested on three datasets with the tumor segmentation task: LIDC-IDRI, LiTS, and a private one with multiple brain metastases cases.	['Boris Shirokikh', 'Mikhail Belyaev', 'Daria Frolova', 'Anton Vasiliuk']	2022-11-01	null	null	null	null	['tumor-segmentation']	['computer-vision']	[-1.59877576e-02 5.01781225e-01 -1.91707700e-01 -5.44501603e-01 -1.09515202e+00 -2.24990293e-01 4.83047903e-01 4.63481903e-01 -4.59239990e-01 7.54646778e-01 6.63014948e-02 -2.68037766e-01 -2.89717108e-01 -6.99367225e-01 -7.10332155e-01 -9.23425555e-01 -5.95680363e-02 7.48414040e-01 3.02989542e-01 4.36199695e-01 1.38711557e-01 7.28897035e-01 -1.12595165e+00 4.54655081e-01 1.12726748e+00 1.29055858e+00 5.35499990e-01 1.92662373e-01 -4.31922764e-01 4.65237528e-01 -5.75436413e-01 -1.45205021e-01 1.15466215e-01 -3.97186950e-02 -7.11433053e-01 -3.00885718e-02 1.85157850e-01 -1.04605846e-01 2.34521136e-01 1.62128210e+00 2.23095372e-01 -3.97144794e-01 1.26914537e+00 -1.12880552e+00 -1.14828482e-01 9.19774413e-01 -8.33694041e-01 2.84187645e-01 -2.88524300e-01 2.10046783e-01 6.66884780e-01 -5.11766493e-01 7.28190780e-01 1.25065196e+00 3.82919371e-01 1.63081929e-01 -8.21889222e-01 -4.10910964e-01 4.73702885e-02 2.95705199e-01 -1.40769911e+00 6.33673668e-02 6.65829301e-01 -6.47069871e-01 2.20617503e-01 2.34302953e-01 4.79464352e-01 8.38058174e-01 7.71375120e-01 1.00151992e+00 1.32543933e+00 -2.68055439e-01 5.24013221e-01 3.15181911e-01 5.67111224e-02 5.60514688e-01 3.81421059e-01 -1.33786844e-02 -7.85626024e-02 1.67586312e-01 7.22572088e-01 -8.98582339e-02 -4.46356803e-01 -4.81075406e-01 -9.36939299e-01 6.85781181e-01 1.06306291e+00 5.08758605e-01 -3.01155150e-01 3.42940539e-01 3.05284768e-01 -4.12144184e-01 5.29906631e-01 3.47678900e-01 -1.03104606e-01 8.69724602e-02 -1.17954504e+00 -1.16913438e-01 3.27537179e-01 4.04306144e-01 3.30185652e-01 -2.15227976e-01 -6.78616405e-01 4.54636663e-01 5.12706876e-01 1.93084002e-01 6.04531169e-01 -5.02941906e-01 1.79669544e-01 5.97881973e-01 -4.71317805e-02 -7.84850299e-01 -7.61619091e-01 -8.09353828e-01 -1.07602596e+00 7.02412248e-01 7.04136491e-01 4.87737618e-02 -1.60317457e+00 1.38618183e+00 3.58993679e-01 1.26783460e-01 -2.80378461e-01 1.08188879e+00 1.05156457e+00 4.38816965e-01 2.25688264e-01 -1.39381483e-01 1.48136115e+00 -9.04936016e-01 -7.47949183e-01 -2.57272661e-01 7.16182411e-01 -5.35727143e-01 7.22200811e-01 3.90566111e-01 -9.41312253e-01 -2.60532707e-01 -9.78629112e-01 3.93241823e-01 -1.65092304e-01 3.56961817e-01 4.35273349e-01 6.74052536e-01 -8.26672018e-01 5.16761363e-01 -8.69129002e-01 2.49925647e-02 8.49598110e-01 1.14378244e-01 -1.68699086e-01 -1.87391676e-02 -1.08803904e+00 1.21118701e+00 7.59135723e-01 1.00539424e-01 -1.18404448e+00 -9.14047539e-01 -7.56511450e-01 3.53913121e-02 3.96670729e-01 -5.38903832e-01 9.25522327e-01 -7.74087548e-01 -8.79063249e-01 8.17749023e-01 1.61774710e-01 -6.44751191e-01 1.20797348e+00 3.23759764e-01 -5.49823269e-02 1.36867553e-01 4.52039838e-02 8.18045795e-01 9.42830443e-01 -1.59858334e+00 -5.97373664e-01 -7.06227005e-01 -1.95432365e-01 1.80799469e-01 1.65012851e-01 -5.08583009e-01 -5.08751035e-01 -4.82326478e-01 2.94462591e-01 -6.63051724e-01 -4.90600646e-01 2.96868116e-01 -7.60605991e-01 4.96824719e-02 5.55174947e-01 -7.32637584e-01 9.17340279e-01 -2.09652090e+00 5.03426464e-03 6.00727379e-01 4.55033213e-01 -6.62219822e-02 3.40624720e-01 -4.89173174e-01 -8.08069296e-03 3.08931082e-01 -6.81787372e-01 -2.67589897e-01 -1.19895667e-01 1.30765349e-01 4.56581593e-01 4.81651515e-01 1.17108479e-01 8.63513410e-01 -6.68159842e-01 -1.06913495e+00 3.91723454e-01 4.41018283e-01 -1.98384315e-01 1.31247133e-01 -3.38753909e-01 7.37985909e-01 -5.75391233e-01 6.48452878e-01 8.84422958e-01 -2.32480377e-01 -1.17902532e-01 -6.00005507e-01 1.06800117e-01 -3.47990155e-01 -1.22506416e+00 1.45985794e+00 -4.75731134e-01 4.86637324e-01 1.83371231e-01 -7.70448446e-01 8.34439933e-01 1.25927925e-02 5.31296074e-01 -5.80717087e-01 4.86419261e-01 2.83505321e-01 2.68670470e-01 -4.24509913e-01 3.64780836e-02 -5.58991060e-02 1.36670396e-01 -2.62184236e-02 -3.07275802e-01 -4.80162442e-01 8.40257853e-02 1.44478321e-01 8.24263573e-01 -1.46408632e-01 4.48243767e-01 -5.86291671e-01 4.47153717e-01 1.98933929e-02 5.60202539e-01 5.84408998e-01 -4.73732769e-01 8.17711353e-01 9.08492386e-01 -7.14266375e-02 -5.20295024e-01 -1.18764961e+00 -8.03094923e-01 2.36217931e-01 3.60333323e-01 1.39780238e-01 -9.64461982e-01 -9.51978862e-01 8.36145952e-02 9.53062534e-01 -9.34730053e-01 -1.59868866e-01 -2.66158562e-02 -8.38955581e-01 1.62076518e-01 5.92668533e-01 4.74163026e-01 -8.45443726e-01 -8.69783223e-01 2.20880397e-02 -2.18235731e-01 -1.03170800e+00 -1.81540713e-01 4.44010556e-01 -1.00204992e+00 -1.07366300e+00 -1.11971629e+00 -3.20458800e-01 9.36943471e-01 -4.00676489e-01 1.21546328e+00 -4.64129150e-02 -6.98341966e-01 2.78807227e-02 -1.65660828e-01 -6.87846661e-01 -5.90996444e-01 -2.18912885e-01 -4.85397816e-01 -1.33229628e-01 -1.95025504e-01 -3.22232954e-02 -6.75955772e-01 4.10936236e-01 -9.99315321e-01 1.74162969e-01 1.00879729e+00 8.55987787e-01 1.04959619e+00 5.06328642e-01 1.97731405e-01 -9.79455233e-01 5.07678688e-01 -2.84587741e-01 -5.85520387e-01 5.02201676e-01 -4.90226984e-01 3.10595512e-01 2.69021958e-01 -3.37444395e-02 -1.27488863e+00 1.58491567e-01 -1.66468665e-01 -2.38513663e-01 -2.47825652e-01 5.80157578e-01 -1.85640782e-01 -1.18532486e-01 7.18865931e-01 -2.83539653e-01 -1.24242604e-01 -1.74345776e-01 2.36789823e-01 5.21797240e-01 3.34724605e-01 -4.83897924e-01 2.28517771e-01 6.30491853e-01 2.60500968e-01 -6.44947112e-01 -6.47393227e-01 -3.41611117e-01 -5.69406927e-01 -4.82620746e-01 1.19356239e+00 -5.23849785e-01 -3.23791653e-01 2.93515176e-01 -1.14034283e+00 -2.41228342e-01 -2.94263631e-01 5.68240404e-01 -3.73959988e-01 2.80152082e-01 -3.11481833e-01 -6.65615618e-01 -3.95743340e-01 -2.00013065e+00 1.21850932e+00 4.46322501e-01 -5.24114519e-02 -8.85968626e-01 -2.55439997e-01 2.50661075e-01 2.84237325e-01 3.90666008e-01 1.21875370e+00 -5.90128839e-01 -6.46227956e-01 4.01078425e-02 -6.97105289e-01 2.09730625e-01 -2.10688055e-01 1.74124345e-01 -1.04442477e+00 1.26608998e-01 -3.02301962e-02 -2.99313646e-02 9.79006052e-01 1.12805831e+00 1.70663309e+00 3.15549344e-01 -7.22201765e-01 6.81910932e-01 1.37537575e+00 9.83005166e-02 6.21790886e-01 2.09805354e-01 6.34788156e-01 4.94177431e-01 8.29459190e-01 5.01288712e-01 2.71777771e-02 5.71680427e-01 1.21415210e+00 -2.82799572e-01 -3.91764849e-01 1.12678543e-01 -1.69968098e-01 1.31666034e-01 1.12550631e-01 -2.69721568e-01 -1.17015207e+00 4.59908456e-01 -1.61817360e+00 -2.94072539e-01 -2.84613997e-01 2.02137494e+00 6.48545682e-01 3.99561942e-01 -3.88264924e-01 1.32666854e-03 7.67714500e-01 4.65136953e-02 -6.17869437e-01 -1.52993858e-01 2.50377059e-01 -8.30135345e-02 6.83734059e-01 4.43676591e-01 -1.10167861e+00 5.91106176e-01 5.61429882e+00 1.43874753e+00 -1.15404129e+00 7.45098814e-02 1.37665141e+00 1.85872793e-01 -6.16680205e-01 -4.97653186e-01 -6.81994498e-01 5.62410772e-01 3.07920367e-01 6.16380125e-02 -2.11270943e-01 9.60689247e-01 2.46661901e-01 -7.66401470e-01 -1.19204867e+00 1.16893542e+00 -1.48052335e-01 -1.43573451e+00 -1.27580836e-01 1.13484643e-01 8.03274691e-01 -2.44799316e-01 5.54246865e-02 9.12426934e-02 6.94413483e-03 -1.44852078e+00 6.42562509e-01 8.29942465e-01 6.68883145e-01 -7.50464201e-01 1.19712627e+00 3.99528503e-01 -8.83240521e-01 2.01184347e-01 -4.10540074e-01 8.49342704e-01 2.48715803e-01 1.17455328e+00 -1.23046303e+00 5.95905960e-01 8.43566895e-01 2.73811519e-01 -7.45281875e-01 1.44642794e+00 -1.98690668e-01 2.46760607e-01 -3.94514292e-01 1.90068465e-02 2.69262373e-01 -7.85455629e-02 4.90144938e-01 1.11071396e+00 4.57909763e-01 -1.52262881e-01 3.16493474e-02 1.20459580e+00 6.14689626e-02 -2.69549480e-03 -1.35422364e-01 1.44862711e-01 2.10400373e-01 1.47143781e+00 -1.21815836e+00 -2.11981475e-01 2.53041178e-01 7.36065865e-01 1.58151641e-01 2.02656940e-01 -1.03944182e+00 1.53008536e-01 2.12579608e-01 2.62186557e-01 -1.61904752e-01 1.65106535e-01 -8.34633827e-01 -5.75357735e-01 -1.29450560e-01 -5.99476457e-01 4.93699074e-01 -8.63514125e-01 -1.17521811e+00 8.56726825e-01 2.04281151e-01 -1.00170577e+00 -2.10619882e-01 -8.73587191e-01 -6.56856775e-01 8.06812346e-01 -1.42130291e+00 -9.54670787e-01 -5.92791915e-01 2.59380162e-01 4.35803950e-01 2.03584433e-01 5.14299989e-01 4.70025241e-02 -3.44462305e-01 5.06014943e-01 9.58555713e-02 -7.61485249e-02 5.96468687e-01 -1.49314690e+00 -3.09598237e-01 7.70956457e-01 -7.11776316e-02 -7.45557249e-02 7.68792510e-01 -7.44341135e-01 -6.91082537e-01 -8.85475516e-01 6.86512962e-02 -3.50132227e-01 3.70180100e-01 9.64223221e-02 -7.84297168e-01 1.55321568e-01 -8.04363936e-02 3.01746875e-01 2.21405417e-01 -3.07607979e-01 2.67629176e-01 -1.12094805e-01 -1.73985481e+00 4.23022062e-01 5.63583493e-01 -1.84780478e-01 -4.19379413e-01 2.40300074e-01 5.44161499e-01 -7.78324664e-01 -1.03838336e+00 7.03440309e-01 3.50462645e-01 -1.20170665e+00 1.00198841e+00 -8.64443108e-02 4.48460340e-01 -3.78455728e-01 1.19808182e-01 -1.65150607e+00 -2.51800492e-02 3.66529077e-01 1.69820935e-01 8.80948067e-01 6.30972385e-01 -3.30551326e-01 8.19082856e-01 8.60149503e-01 -4.86470193e-01 -9.92573619e-01 -1.13868797e+00 -6.59821033e-01 1.27409548e-01 -6.32534087e-01 5.83675802e-01 6.05634332e-01 -4.93826896e-01 -5.05048335e-01 1.72032416e-01 3.21465403e-01 8.03982735e-01 -2.26555899e-01 2.29967594e-01 -1.18527639e+00 -1.49824724e-01 -8.13867867e-01 -7.43133843e-01 -5.68198740e-01 -1.89026758e-01 -8.02483201e-01 2.60205567e-01 -1.99950230e+00 3.16250443e-01 -6.57085299e-01 -4.93983269e-01 1.07859053e-01 -3.92001159e-02 -2.62152813e-02 9.47488621e-02 1.21823940e-02 -3.13545555e-01 3.90004992e-01 1.75024390e+00 -5.22950768e-01 1.88013703e-01 1.98944397e-02 -2.86337823e-01 1.02531254e+00 6.56225741e-01 -5.10277450e-01 -3.03285748e-01 -1.71321407e-01 -1.93897069e-01 1.11120559e-01 4.82569754e-01 -1.09840047e+00 1.66947335e-01 -2.08589897e-01 6.36109352e-01 -9.19984281e-01 1.41494229e-01 -1.16655862e+00 1.41732529e-01 5.42871356e-01 -2.95799196e-01 -4.84005362e-01 2.32045248e-01 4.80519444e-01 -2.76430905e-01 -6.91922128e-01 1.09067523e+00 -3.44748497e-01 -8.91628206e-01 3.52822572e-01 3.77951264e-02 1.28103673e-01 1.41656661e+00 -6.62376210e-02 -1.92621604e-01 -1.61401853e-01 -9.57828820e-01 2.94308782e-01 1.90861180e-01 6.68011531e-02 6.05161011e-01 -1.08751643e+00 -6.80874109e-01 -5.81193566e-02 2.94192582e-01 3.52048934e-01 5.75677812e-01 1.02365315e+00 -7.50563979e-01 3.49516153e-01 -2.36700684e-01 -1.17885673e+00 -1.12065101e+00 3.02349150e-01 7.27747858e-01 -5.66288650e-01 -4.11077201e-01 1.16987956e+00 6.45686984e-01 -6.80276752e-02 6.04663670e-01 -8.16406965e-01 -4.21020359e-01 -3.37961912e-02 4.48988795e-01 1.75725386e-01 1.82355389e-01 -4.14078146e-01 -4.79237139e-01 4.01307136e-01 -1.03960363e-02 -5.27080446e-02 8.77621233e-01 -5.02534956e-02 -6.40632659e-02 2.74078161e-01 9.95626867e-01 -4.38918680e-01 -1.33215129e+00 -5.47813531e-03 2.15111095e-02 -4.76768851e-01 6.85859025e-01 -1.16400933e+00 -1.34971237e+00 1.10948849e+00 1.19044471e+00 -1.00038953e-01 8.57645631e-01 1.99063763e-01 2.84498006e-01 -2.35254258e-01 3.85278314e-01 -1.12342048e+00 -7.56645128e-02 -1.65201440e-01 1.03133345e+00 -1.68223584e+00 8.40222389e-02 -5.82180977e-01 -8.53003263e-01 1.12999082e+00 6.67729437e-01 2.65688747e-01 8.39487255e-01 5.88683248e-01 1.49129897e-01 -3.47445905e-01 -3.46767232e-02 -2.56370604e-01 8.14991057e-01 6.87057495e-01 3.92731637e-01 5.36872029e-01 -1.97016820e-01 7.32487738e-01 1.80190653e-01 -4.67466787e-02 2.64802158e-01 4.03606296e-01 -6.68867886e-01 -7.29510427e-01 -6.36237264e-01 6.88077271e-01 -3.66653234e-01 5.61988838e-02 -7.07937554e-02 8.31095636e-01 2.85644233e-01 4.54047978e-01 1.15637101e-01 1.01851612e-01 -2.55868640e-02 -1.77866712e-01 4.33378190e-01 -4.07163531e-01 -1.82341069e-01 2.42826827e-02 -3.50539153e-03 -5.71150243e-01 1.71192233e-02 -4.00111854e-01 -1.63287330e+00 1.97090715e-01 -3.36608052e-01 1.93863530e-02 1.05664206e+00 1.04815102e+00 -1.11739717e-01 1.00724256e+00 2.34115243e-01 -5.13696432e-01 -4.33353096e-01 -8.15088689e-01 -6.73616767e-01 3.21243793e-01 -8.29964727e-02 -9.39842463e-01 -3.88873488e-01 -4.38355207e-01]	[14.415485382080078, -2.0882089138031006]
1351cc8e-92fe-42ff-818a-b7ca5bbcada7	text-based-rl-agents-with-commonsense-1	null	null	https://openreview.net/forum?id=Aws7Sgnej4G	https://openreview.net/pdf?id=Aws7Sgnej4G	Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Approaches	Text-based games have emerged as an important test-bed for Reinforcement Learning (RL) research, requiring RL agents to combine grounded language understanding with sequential decision making. In this paper, we examine the problem of infusing RL agents with commonsense knowledge. This allows agents to efficiently act in the world by pruning out implausible actions, and to perform look-ahead planning to determine how current actions might affect future world states. We design a new text-based gaming environment called TextWorld Commonsense (TWC) for training and evaluating RL agents with a specific kind of commonsense knowledge about objects, their attributes, and affordances. We introduce a number of RL agents that combine the sequential context with a dynamic graph representation of their beliefs of the world and commonsense knowledge from ConceptNet in different ways. We show that our agents act efficiently (fewer moves) and achieve better scores, and that learned policies can be transferred to other instances in TWC.	['Murray Campbell', 'Mrinmaya Sachan', 'Kartik Talamadupula', 'Gerald Tesauro', 'Sadhana Kumaravel', 'Pushkar Shukla', 'Pavan Kapanipathi', 'Mattia Atzeni', 'Keerthiram Murugesan']	2020-07-12	null	null	null	null	['text-based-games']	['playing-games']	[ 1.59125865e-01 4.02925432e-01 1.64817438e-01 -8.12684670e-02 -7.25507736e-02 -8.23664248e-01 7.95193493e-01 2.51842868e-02 -8.45353246e-01 1.06908453e+00 3.61960828e-01 -4.61642593e-01 -1.01000227e-01 -1.40930271e+00 -6.02572501e-01 -3.21464092e-01 -3.59955907e-01 1.10145926e+00 5.62975407e-01 -8.52859020e-01 2.64319062e-01 4.11857277e-01 -1.54741144e+00 2.19859451e-01 8.94662440e-01 2.67519683e-01 4.16393787e-01 8.72903407e-01 6.77081943e-02 1.80339336e+00 -6.35419786e-01 -4.57668155e-01 1.81997165e-01 -8.38651180e-01 -1.25139236e+00 -1.40600815e-01 -1.93981484e-01 -6.40790701e-01 -3.12276155e-01 1.15333450e+00 2.99448520e-02 7.41661251e-01 3.79625261e-01 -1.37693930e+00 -5.80094755e-01 1.12401867e+00 3.17415893e-01 1.39381168e-02 6.81889653e-01 8.78545225e-01 1.00450373e+00 2.31731802e-01 9.28812563e-01 1.62184405e+00 8.63924250e-02 1.15338671e+00 -1.02506769e+00 -4.84390795e-01 3.92696112e-01 6.16589367e-01 -7.06113219e-01 -1.78005338e-01 5.96420825e-01 -7.49322623e-02 1.62143397e+00 1.51207432e-01 1.28599930e+00 1.06106901e+00 1.44702807e-01 8.08012426e-01 1.27009523e+00 -6.11186028e-01 8.30587506e-01 -2.81691015e-01 -3.29850107e-01 1.12124383e+00 2.76560962e-01 7.92307258e-01 -5.84858894e-01 -1.08955383e-01 1.01640272e+00 -2.02693820e-01 2.89015830e-01 -5.16974807e-01 -1.30093300e+00 9.29597199e-01 3.84274989e-01 3.04595500e-01 -4.03925627e-01 8.27628791e-01 4.25497234e-01 5.49640715e-01 -1.82541281e-01 1.37121940e+00 -3.65793258e-01 -4.32645351e-01 6.16365112e-02 5.66416264e-01 9.85366642e-01 8.45162153e-01 6.53488338e-01 2.60664880e-01 1.28327519e-01 3.30488592e-01 1.88859642e-01 8.36767435e-01 5.90701401e-01 -1.62946498e+00 2.71153212e-01 4.40659106e-01 2.46064961e-01 -7.42918909e-01 -5.34400403e-01 1.13077193e-01 3.23046893e-02 5.19977272e-01 7.99157619e-02 -5.07903278e-01 -8.71052921e-01 2.21969366e+00 2.67551690e-01 4.20135975e-01 5.69587648e-01 6.52597249e-01 3.04932952e-01 5.41813076e-01 4.78696644e-01 -1.47722527e-01 1.02401054e+00 -5.54585695e-01 -3.65942419e-01 -6.36394858e-01 9.72638965e-01 3.20097268e-01 1.14356220e+00 4.48941022e-01 -1.07436109e+00 -1.69560537e-01 -1.00429821e+00 -9.18526724e-02 -6.02731943e-01 -7.79415429e-01 1.26715577e+00 4.56526846e-01 -1.36116505e+00 7.20803499e-01 -9.56885397e-01 -4.87988830e-01 4.73831803e-01 3.57834816e-01 5.21958247e-03 -1.27669170e-01 -1.44051993e+00 1.59750032e+00 1.01213288e+00 -3.88731927e-01 -1.50416923e+00 8.02347735e-02 -1.20256186e+00 -8.58492926e-02 1.05323553e+00 -9.21140194e-01 1.54161406e+00 -8.06446254e-01 -1.95638001e+00 7.25637317e-01 4.69013005e-01 -6.81703568e-01 2.75853962e-01 -6.62995502e-02 -1.53991938e-01 1.22606717e-01 1.35555208e-01 8.83255959e-01 4.22872514e-01 -1.22721624e+00 -9.04339135e-01 -4.99004871e-01 1.07615697e+00 7.13610232e-01 3.80363375e-01 -2.99915373e-01 2.66697351e-02 -2.62629449e-01 -4.41384874e-02 -1.05392766e+00 -4.14563924e-01 -2.35334039e-01 -3.22813332e-01 -3.57131422e-01 1.66059732e-01 4.19072323e-02 5.27651429e-01 -1.64858532e+00 3.92229617e-01 1.80073962e-01 2.87471294e-01 -9.70200226e-02 -4.10698175e-01 3.76986355e-01 2.46767715e-01 1.16375305e-01 1.84984192e-01 2.01012880e-01 3.69366705e-01 8.82386327e-01 -2.20160648e-01 -2.95993872e-02 -8.94662291e-02 1.26632977e+00 -1.55447173e+00 -4.79170650e-01 5.27504623e-01 -3.61889124e-01 -8.87179375e-01 1.29932150e-01 -9.51070905e-01 7.40376785e-02 -8.97208273e-01 4.31776010e-02 -5.83528653e-02 8.16396028e-02 6.66374445e-01 6.13230348e-01 2.16393977e-01 5.89954674e-01 -1.05644977e+00 1.61142302e+00 -5.52740574e-01 3.84162635e-01 -4.42418456e-01 -6.08917892e-01 3.27310890e-01 8.39662775e-02 -2.01099906e-02 -8.71970594e-01 1.65777594e-01 -1.62139669e-01 3.85828853e-01 -6.20358169e-01 3.23650420e-01 -8.88194144e-01 -3.31406265e-01 7.44503438e-01 1.53331459e-01 -9.24308240e-01 3.40024889e-01 4.40532893e-01 1.25234139e+00 4.95804310e-01 5.89114308e-01 -1.53348204e-02 8.12577605e-02 6.14518762e-01 3.57407093e-01 1.24923754e+00 -1.48846239e-01 -3.26013356e-01 5.55888236e-01 -6.26173675e-01 -6.97074652e-01 -1.05013216e+00 8.73537540e-01 1.58708525e+00 2.52511382e-01 -2.71469116e-01 -5.21033585e-01 -4.95548457e-01 -3.02295178e-01 1.74430597e+00 -7.70125329e-01 -5.80172837e-01 -6.94441795e-01 -1.33002698e-01 6.16514385e-01 5.87679744e-01 6.70392394e-01 -1.88940585e+00 -1.58666074e+00 3.13472122e-01 -1.08024657e-01 -8.86719406e-01 2.53608171e-02 4.43249881e-01 -9.04155314e-01 -1.32574594e+00 2.28267908e-01 -5.54296255e-01 2.60543197e-01 -5.99810109e-02 1.39507520e+00 4.25972134e-01 -5.10014817e-02 7.97284603e-01 -5.23263097e-01 -6.05244994e-01 -7.32579350e-01 -4.38088953e-01 9.00130253e-03 -9.17024672e-01 2.24185988e-01 -6.94160044e-01 -1.26392245e-01 -1.42134622e-01 -8.07917178e-01 4.99755085e-01 1.62997201e-01 6.56389058e-01 2.76412573e-02 3.66036713e-01 1.92427009e-01 -9.65513587e-01 9.81059730e-01 -2.57926345e-01 -7.52599180e-01 3.51498723e-01 -2.95423150e-01 4.82475609e-01 7.08414614e-01 -2.99995899e-01 -1.23111522e+00 -1.96356580e-01 2.15564132e-01 4.36829142e-02 -2.56038517e-01 5.02356589e-01 -2.63814390e-01 2.69785017e-01 9.24427152e-01 4.59651113e-01 -6.45928234e-02 2.39523038e-01 8.43059719e-01 -1.62465364e-01 3.84330511e-01 -1.35648358e+00 6.32896900e-01 2.55979985e-01 9.96595831e-04 -3.25174540e-01 -8.45776558e-01 -9.82676223e-02 -2.96094120e-01 -7.94996098e-02 9.60066676e-01 -5.12366652e-01 -1.24883151e+00 1.76511228e-01 -9.58517194e-01 -1.12541175e+00 -7.56398797e-01 3.89110714e-01 -1.35361671e+00 -1.61956474e-01 -5.05506217e-01 -9.18707132e-01 2.88997859e-01 -1.01577127e+00 5.84502101e-01 7.14811981e-02 -1.84857890e-01 -1.01317513e+00 2.88389176e-01 -1.63602382e-02 1.83485523e-01 8.76368135e-02 1.27665079e+00 -9.20544028e-01 -5.06536961e-01 3.70035768e-01 1.59261867e-01 -1.56543538e-01 -2.83589847e-02 -3.23117197e-01 -6.93869650e-01 3.30188647e-02 -4.97575067e-02 -9.51707363e-01 5.19598186e-01 2.16867059e-01 1.03245723e+00 -5.14340639e-01 -2.26485714e-01 1.80917293e-01 1.37189221e+00 7.22515225e-01 9.54067290e-01 5.88103950e-01 1.91557229e-01 3.73757273e-01 5.65589666e-01 5.02977729e-01 6.66747332e-01 3.12624454e-01 6.10168874e-01 5.86466074e-01 1.01088643e-01 -6.96517646e-01 4.04485315e-01 7.95110594e-04 -6.54003561e-01 -3.60554367e-01 -9.35603499e-01 3.92516971e-01 -1.96132767e+00 -1.57553089e+00 7.25303650e-01 1.72905171e+00 1.12512684e+00 2.54201591e-01 1.28451049e-01 -3.34802836e-01 3.22842926e-01 9.09523144e-02 -9.36388850e-01 -3.72200042e-01 1.00772977e-01 4.44740146e-01 1.47472158e-01 9.36372757e-01 -6.86253369e-01 1.67313600e+00 6.70610046e+00 5.64877510e-01 -5.96720874e-01 -7.03721568e-02 3.06622475e-01 -5.27948700e-02 -4.00120676e-01 1.18239097e-01 -1.64237961e-01 -9.82587934e-02 7.51966178e-01 -2.12417245e-01 1.09903526e+00 7.95914352e-01 -3.03128045e-02 -4.45125550e-01 -1.30859721e+00 5.93516588e-01 -1.55778408e-01 -1.38683748e+00 2.46086478e-01 -5.39378226e-02 5.07067800e-01 7.20730945e-02 -1.47101074e-01 1.06995273e+00 1.66920924e+00 -1.12245440e+00 7.68331707e-01 2.89103031e-01 5.02058327e-01 -8.07788193e-01 4.85501170e-01 7.52912700e-01 -6.54927969e-01 -3.60311687e-01 -5.10349214e-01 -6.16432190e-01 -2.68586040e-01 -4.31317240e-01 -1.01322901e+00 1.53855950e-01 1.57764107e-01 4.63676780e-01 -3.84429306e-01 5.34025311e-01 -8.08760524e-01 2.44881183e-01 -4.20068085e-01 -8.18766594e-01 4.44779456e-01 -2.34205231e-01 4.43323106e-01 5.66485584e-01 5.28897308e-02 1.03531957e+00 4.74353760e-01 1.06285501e+00 3.95455696e-02 -4.00582999e-01 -8.05010378e-01 -4.43273783e-02 5.16877174e-01 5.23662925e-01 -8.82033050e-01 -7.50195503e-01 8.09932202e-02 8.34594548e-01 6.13064766e-01 3.43730032e-01 -7.53451109e-01 8.32447782e-02 6.16438508e-01 -2.58527130e-01 -5.44427708e-03 -2.80005515e-01 8.65593925e-02 -1.32066655e+00 -6.06210232e-01 -1.13448572e+00 4.91086274e-01 -1.34372389e+00 -8.68678093e-01 3.32428694e-01 4.02396917e-01 -5.28926909e-01 -6.82273090e-01 -8.27440739e-01 -6.25057697e-01 2.90263295e-01 -1.21120656e+00 -9.05590653e-01 2.02785749e-02 9.70059752e-01 7.03867495e-01 -1.60295978e-01 1.17937708e+00 -1.05553138e+00 -5.81573602e-03 -1.98920727e-01 -4.40295100e-01 1.90147012e-01 -9.53791291e-02 -1.44961989e+00 4.45145279e-01 5.26620924e-01 3.17137837e-01 7.22822845e-01 9.15626049e-01 -8.03663909e-01 -1.35053587e+00 -7.11622596e-01 2.00594008e-01 -6.43167078e-01 7.96202600e-01 -9.71096009e-02 -3.47841173e-01 1.07621825e+00 2.63475865e-01 -2.54840970e-01 5.64305782e-01 4.79015470e-01 -4.73370612e-01 3.12203765e-01 -1.23848760e+00 1.21748900e+00 1.58723366e+00 -5.66850960e-01 -1.40469408e+00 3.76256555e-01 8.01369607e-01 -4.13461834e-01 -2.49281034e-01 -2.43111044e-01 2.64494061e-01 -1.00702929e+00 8.06206167e-01 -1.38357639e+00 4.69440103e-01 -3.00790936e-01 -3.23997974e-01 -1.81214666e+00 -4.99737859e-01 -6.97272182e-01 1.68865144e-01 2.00547725e-01 3.06014329e-01 -8.47022593e-01 6.55993879e-01 9.57825184e-01 7.36794993e-03 -1.70857817e-01 -9.33017075e-01 -6.83402836e-01 2.43714049e-01 -8.28163207e-01 6.86860681e-01 8.13138962e-01 6.62140191e-01 5.20750046e-01 1.62426885e-02 -7.06007034e-02 4.13526863e-01 2.17664495e-01 4.21449840e-01 -1.10194218e+00 -5.33079028e-01 -4.22146589e-01 -2.50266254e-01 -9.35198426e-01 3.98239732e-01 -8.16771030e-01 4.38808441e-01 -1.66162741e+00 3.25964361e-01 -5.00741243e-01 -1.65095687e-01 9.61295426e-01 1.17561668e-02 -4.06698316e-01 6.83271289e-01 -1.12142049e-01 -1.17793560e+00 4.53731269e-01 1.71181059e+00 -1.81862175e-01 -1.84116200e-01 -3.00167561e-01 -7.11790800e-01 1.04990101e+00 1.08060718e+00 -3.40033531e-01 -9.89456475e-01 -5.04430532e-01 8.19878936e-01 3.44507426e-01 5.88596940e-01 -1.01809895e+00 3.58582199e-01 -1.04604161e+00 2.74292529e-01 -3.96152120e-03 3.91494751e-01 -7.19766438e-01 -1.87860742e-01 7.67497420e-01 -8.54221284e-01 9.66542065e-02 3.90004158e-01 5.70653498e-01 3.60995710e-01 -3.36728662e-01 5.32445252e-01 -9.09941554e-01 -1.28715944e+00 -8.41069594e-02 -7.13740766e-01 5.20445287e-01 1.08712184e+00 -2.29202777e-01 -3.51255983e-01 -7.50111401e-01 -1.02083552e+00 3.62361699e-01 5.78882694e-01 -5.82713000e-02 9.26037610e-01 -9.17016745e-01 -4.66787487e-01 -1.00746430e-01 3.77993546e-02 -6.67432547e-02 -6.98832572e-02 5.24128973e-02 -6.53183699e-01 1.77295700e-01 -6.41513944e-01 2.48635948e-01 -8.25618684e-01 7.60845244e-01 8.06330681e-01 -2.75776744e-01 -5.92942357e-01 1.06271756e+00 2.95482010e-01 -6.73294127e-01 -7.75222704e-02 -6.58931971e-01 -3.23762089e-01 -5.59778988e-01 5.68051577e-01 9.22002792e-02 -4.99662459e-01 -2.05127168e-02 -3.33712161e-01 4.86618653e-02 1.30658105e-01 -6.08738899e-01 1.45475912e+00 1.19623251e-01 -1.44244418e-01 2.63273150e-01 2.77267009e-01 -2.70421147e-01 -1.25397015e+00 -7.03542233e-02 -1.45379439e-01 -3.01282287e-01 -1.83439493e-01 -1.27222431e+00 -5.14026999e-01 5.01849055e-01 -3.02540623e-02 3.45173120e-01 8.86785150e-01 2.23150805e-01 1.02564871e-01 1.29824543e+00 1.16371584e+00 -1.35794067e+00 4.80709732e-01 1.00747097e+00 8.68915677e-01 -1.05494797e+00 1.55549884e-01 6.08760910e-03 -1.06973946e+00 1.02160537e+00 8.29747617e-01 -3.54919046e-01 9.85543057e-02 1.33407325e-01 -2.79920965e-01 -4.31779265e-01 -1.23560631e+00 -7.45365262e-01 -4.06818181e-01 1.37410676e+00 -1.83083132e-01 3.91178519e-01 4.14014995e-01 2.16040820e-01 -6.22588456e-01 5.32885343e-02 7.46668220e-01 1.10745823e+00 -8.70311677e-01 -7.92103648e-01 -1.48757949e-01 3.39773148e-01 1.37514412e-01 -2.73830503e-01 -6.92454398e-01 1.01336169e+00 2.70337611e-01 1.03631568e+00 -1.48094624e-01 -2.91329682e-01 2.28164122e-01 1.02262087e-01 1.13923335e+00 -1.05225611e+00 -3.27810794e-01 -5.09397924e-01 5.14271319e-01 -1.13763273e+00 -4.07388300e-01 -6.53513968e-01 -1.92207205e+00 -4.89951104e-01 -4.77375053e-02 1.35518298e-01 9.63267088e-02 1.27780282e+00 8.12725909e-03 5.61132252e-01 6.08278960e-02 -5.17113268e-01 -6.23229980e-01 -6.59537971e-01 -4.39594537e-01 4.17344660e-01 2.01480508e-01 -8.21722269e-01 -6.87924922e-02 -4.23900224e-02]	[3.886899471282959, 1.221832275390625]
57624eb1-5721-47b3-a6b2-5e9dc654059c	preservation-of-anomalous-subgroups-on	1911.03674	null	https://arxiv.org/abs/1911.03674v1	https://arxiv.org/pdf/1911.03674v1.pdf	Preservation of Anomalous Subgroups On Machine Learning Transformed Data	In this paper, we investigate the effect of machine learning based anonymization on anomalous subgroup preservation. In particular, we train a binary classifier to discover the most anomalous subgroup in a dataset by maximizing the bias between the group's predicted odds ratio from the model and observed odds ratio from the data. We then perform anonymization using a variational autoencoder (VAE) to synthesize an entirely new dataset that would ideally be drawn from the distribution of the original data. We repeat the anomalous subgroup discovery task on the new data and compare it to what was identified pre-anonymization. We evaluated our approach using publicly available datasets from the financial industry. Our evaluation confirmed that the approach was able to produce synthetic datasets that preserved a high level of subgroup differentiation as identified initially in the original dataset. Such a distinction was maintained while having distinctly different records between the synthetic and original dataset. Finally, we packed the above end to end process into what we call Utility Guaranteed Deep Privacy (UGDP) system. UGDP can be easily extended to onboard alternative generative approaches such as GANs to synthesize tabular data.	['Robert-Florian Samoilescu', 'Reginald E. Bryant', 'Kush R. Varshney', 'William O. Goal', 'Samuel C. Maina', 'Komminist Weldemariam']	2019-11-09	null	null	null	null	['subgroup-discovery']	['methodology']	[ 3.28687578e-01 7.56212115e-01 1.17270444e-02 -6.19064867e-01 -8.85471642e-01 -7.62830138e-01 7.70788193e-01 2.65361965e-01 -2.31697068e-01 1.10522854e+00 4.28168386e-01 -2.17554778e-01 4.75939922e-02 -9.73243535e-01 -1.04473984e+00 -7.92095363e-01 1.34150729e-01 7.83061922e-01 -2.98964381e-01 1.28571570e-01 1.43486947e-01 5.83891928e-01 -1.33371961e+00 4.85060543e-01 7.82758534e-01 8.47176671e-01 -6.29863024e-01 5.69994688e-01 1.18843339e-01 6.18439913e-01 -8.47459674e-01 -8.28359902e-01 8.96991909e-01 -6.79578781e-01 -8.15107882e-01 5.08483425e-02 4.22255933e-01 -3.42321068e-01 -3.61434400e-01 1.03122175e+00 3.31730396e-01 -9.02388841e-02 7.60834813e-01 -1.54096723e+00 -5.53411841e-01 8.38262618e-01 -3.49164128e-01 -1.44445404e-01 1.44133925e-01 3.07206482e-01 1.09013176e+00 -2.46594444e-01 1.01074290e+00 8.47221732e-01 7.98245549e-01 4.74004418e-01 -1.81870317e+00 -7.08895385e-01 -2.92976797e-01 -3.00565004e-01 -1.27968037e+00 -4.86972183e-01 7.15431988e-01 -5.56536376e-01 3.94996107e-01 5.11591315e-01 7.09742248e-01 1.43307757e+00 1.53689221e-01 3.78718644e-01 8.54141951e-01 -1.09730482e-01 4.71810877e-01 4.51073796e-01 -1.59622848e-01 3.89017910e-01 3.23259920e-01 1.61246061e-01 -3.03303897e-01 -6.81981742e-01 3.54742646e-01 -1.31277397e-01 -2.22129792e-01 -6.66452348e-01 -1.22653806e+00 1.00289917e+00 3.19171906e-01 3.44983041e-02 -6.78875327e-01 4.82270271e-02 4.17188376e-01 4.43967402e-01 5.43207228e-01 7.11818457e-01 -3.05990607e-01 1.34721547e-01 -1.11009789e+00 6.40688896e-01 9.34060574e-01 7.10013270e-01 7.61389792e-01 4.12313156e-02 -3.48123223e-01 3.27558577e-01 -4.88193482e-02 8.41152947e-03 5.40719926e-01 -1.19994497e+00 2.67396390e-01 5.13367951e-01 7.34393820e-02 -9.21252906e-01 6.58793077e-02 -3.74806732e-01 -8.66991758e-01 2.50694335e-01 5.23943841e-01 -4.43833351e-01 -7.31908023e-01 1.90306747e+00 3.36843520e-01 -7.07200691e-02 4.05752957e-01 4.48605984e-01 2.65842825e-01 5.81437469e-01 -1.07276686e-01 4.07359451e-02 9.47158933e-01 -3.32066238e-01 -5.08842289e-01 2.20759854e-01 6.00854576e-01 -2.77385950e-01 8.60423207e-01 1.81389615e-01 -7.93815255e-01 -3.41306537e-01 -1.10822237e+00 1.81885421e-01 -2.56046355e-01 -1.69148460e-01 5.13311565e-01 9.58419502e-01 -1.05517030e+00 9.84586537e-01 -6.77431464e-01 -2.40976676e-01 8.31016123e-01 4.77020681e-01 -5.95351875e-01 4.57616508e-01 -1.06796944e+00 3.40671450e-01 8.23458910e-01 -3.78947765e-01 -7.79062629e-01 -1.02641463e+00 -7.34197259e-01 1.01262599e-01 2.50716507e-01 -9.87911761e-01 1.04382515e+00 -1.41613770e+00 -1.17158604e+00 9.80011046e-01 6.00429736e-02 -1.10025561e+00 9.84247863e-01 1.75183401e-01 -4.31266129e-01 -3.10717613e-01 1.21400505e-01 6.80574298e-01 8.56798887e-01 -1.48580098e+00 -6.70924485e-01 -4.38737601e-01 -4.40777212e-01 -2.27821991e-01 4.90471981e-02 -4.06607509e-01 8.31409842e-02 -8.08213770e-01 -9.24731791e-02 -9.98306572e-01 -9.63269323e-02 -1.54862940e-01 -1.00501466e+00 1.75479531e-01 6.30007505e-01 -9.43333924e-01 1.10936618e+00 -2.07590246e+00 -1.90308467e-02 6.45526588e-01 3.39125395e-01 -3.59638445e-02 3.22285205e-01 4.92371678e-01 -4.83157188e-01 3.13443542e-01 -7.62149274e-01 -4.36705917e-01 1.97065011e-01 2.47653082e-01 -7.56024003e-01 7.49567807e-01 1.61238343e-01 7.61836708e-01 -5.39385676e-01 -9.47160497e-02 -2.50103027e-01 1.19513087e-01 -9.33858454e-01 4.31959122e-01 -4.42580491e-01 5.74419081e-01 -2.42856164e-02 3.51753861e-01 8.13197970e-01 1.30803376e-01 3.04700196e-01 7.99435824e-02 2.05544427e-01 6.04003519e-02 -9.71530259e-01 1.31982708e+00 -7.96358958e-02 7.49044240e-01 -3.48220199e-01 -8.52034688e-01 1.15613699e+00 1.46059081e-01 6.02226198e-01 -3.93618375e-01 1.76127534e-02 8.72636363e-02 7.60569200e-02 -1.24402761e-01 7.78659165e-01 -3.69381398e-01 -2.20795825e-01 7.01810420e-01 2.33740546e-02 1.79660723e-01 -2.65229881e-01 1.28562808e-01 8.08982372e-01 -7.86966234e-02 2.77658731e-01 -2.17302695e-01 3.22103709e-01 -1.45270200e-02 7.50138164e-01 8.96002233e-01 1.11956462e-01 8.44974577e-01 1.17079949e+00 -6.27806902e-01 -1.51174891e+00 -1.26839077e+00 -1.37285352e-01 4.06760007e-01 -4.77500707e-01 -3.64693820e-01 -1.02382612e+00 -1.11162400e+00 2.86678135e-01 1.25786066e+00 -9.73209202e-01 -4.93016124e-01 -3.03385437e-01 -9.08077478e-01 9.72867966e-01 1.17457688e-01 3.97091419e-01 -1.07144296e+00 -4.02346849e-01 5.05016297e-02 -1.24783143e-02 -7.29118764e-01 -3.12282860e-01 3.08759715e-02 -5.31503618e-01 -1.05484200e+00 -2.51533091e-01 -3.34736079e-01 6.40377283e-01 -9.04303074e-01 1.04611337e+00 -3.55676264e-01 2.02864353e-02 -9.22037214e-02 2.26493012e-02 -5.56465626e-01 -1.07450688e+00 2.54987955e-01 1.80159628e-01 6.74875200e-01 3.58140320e-01 -7.17890263e-01 -4.16618943e-01 3.25421356e-02 -1.18046248e+00 -2.01457530e-01 1.36644945e-01 7.57204890e-01 6.64802730e-01 2.68021315e-01 6.52322114e-01 -1.38070261e+00 6.26814008e-01 -7.82894671e-01 -6.97969735e-01 3.98021415e-02 -7.16144741e-01 4.24687088e-01 8.87203455e-01 -1.98309019e-01 -9.37682509e-01 7.33138248e-02 -1.82583496e-01 -4.54591930e-01 -3.15100431e-01 9.42642540e-02 -4.80219930e-01 4.85792100e-01 5.59847474e-01 3.06507915e-01 3.26132536e-01 -4.54429686e-01 3.91394258e-01 8.86251390e-01 9.10327792e-01 -5.13766229e-01 7.33477712e-01 5.08650064e-01 -1.18722752e-01 -4.08756405e-01 -4.98720199e-01 3.35602552e-01 -6.84994936e-01 2.65795380e-01 9.25786197e-01 -6.66304350e-01 -6.83392107e-01 4.64282840e-01 -9.53571677e-01 -3.37824404e-01 -1.00139618e+00 1.25642195e-01 -6.81851029e-01 1.84625581e-01 -3.58256465e-03 -5.60728073e-01 -4.12872046e-01 -9.78552580e-01 9.95058358e-01 -9.59155113e-02 -6.44770741e-01 -9.72998679e-01 4.08163637e-01 1.57537535e-01 1.89926624e-01 9.88325119e-01 1.21104336e+00 -1.42023754e+00 -3.15359920e-01 -4.14348006e-01 1.24005049e-01 4.14766848e-01 3.44115764e-01 2.33294442e-01 -1.06731117e+00 -3.49916875e-01 1.74727701e-02 1.30567744e-01 7.05381811e-01 2.63761580e-01 1.39342821e+00 -7.80818880e-01 -1.62946746e-01 1.08957279e+00 1.27955997e+00 2.77556986e-01 7.20308185e-01 4.52653527e-01 7.32069731e-01 6.62852168e-01 1.25075758e-01 4.98982608e-01 1.19420663e-01 6.93307817e-01 4.43627506e-01 -6.97560143e-04 2.57956117e-01 -7.77723134e-01 2.39029363e-01 1.70094818e-02 4.38466042e-01 -4.25967485e-01 -7.83443749e-01 5.57885587e-01 -1.62991393e+00 -1.10995889e+00 2.41680264e-01 2.43283057e+00 6.19542181e-01 1.25268906e-01 4.39809918e-01 2.50694640e-02 7.25857735e-01 1.52281255e-01 -7.40087628e-01 -8.36084843e-01 -1.82069108e-01 1.02010272e-01 7.68367708e-01 3.65434825e-01 -1.08492255e+00 5.78903556e-01 6.07408142e+00 4.73920405e-01 -9.29167032e-01 -2.54487723e-01 1.10479891e+00 -2.35100374e-01 -7.09513962e-01 1.14846922e-01 -4.68549222e-01 7.92729020e-01 1.39434004e+00 -7.42410839e-01 4.23786253e-01 6.88338816e-01 -9.77080762e-02 3.15631926e-01 -1.54205489e+00 6.61429882e-01 -1.54428288e-01 -1.57839072e+00 3.78099114e-01 5.91509461e-01 7.27278769e-01 -2.45525673e-01 2.19079435e-01 1.67027414e-01 6.35043263e-01 -1.21605980e+00 7.37500429e-01 6.86186850e-01 8.96411955e-01 -1.20543826e+00 8.32306385e-01 2.26152882e-01 -3.46699417e-01 -1.08401783e-01 -2.41299897e-01 2.92109817e-01 -1.65713847e-01 6.68040395e-01 -1.37624598e+00 7.01230407e-01 5.24221420e-01 5.66679835e-01 -6.62172079e-01 5.76573372e-01 2.24959657e-01 5.38344979e-01 -2.20263064e-01 5.01810133e-01 2.11774986e-02 -5.68256676e-01 8.70275795e-01 7.54507184e-01 4.01468575e-01 -3.63176733e-01 -2.70029247e-01 1.24225819e+00 -6.48706257e-01 -1.09060287e-01 -9.32644963e-01 -5.60753122e-02 4.12180871e-01 6.53835177e-01 -3.69675428e-01 -3.40585142e-01 5.77862710e-02 1.14796603e+00 1.68007582e-01 9.86307338e-02 -7.82538533e-01 -3.35067332e-01 1.04284132e+00 1.79868400e-01 3.57949257e-01 5.68133354e-01 -2.65831620e-01 -1.11094069e+00 1.04194924e-01 -1.22215366e+00 5.97756863e-01 -5.32442272e-01 -1.31853092e+00 9.08405185e-01 -6.58376589e-02 -1.09355199e+00 -6.51230931e-01 4.11817282e-02 -6.75128758e-01 9.29901242e-01 -5.44194937e-01 -7.88660228e-01 6.64777234e-02 2.37418234e-01 1.59320146e-01 -5.02393305e-01 8.91715109e-01 -3.21751423e-02 -7.42472529e-01 1.00848401e+00 5.04857600e-01 2.49665886e-01 6.35332704e-01 -1.54747570e+00 8.96983922e-01 1.01094520e+00 1.84940740e-01 3.99961114e-01 8.11360657e-01 -8.67413342e-01 -8.37068141e-01 -1.50416994e+00 7.36826360e-01 -6.73339546e-01 4.76736128e-01 -5.13207734e-01 -1.08147931e+00 1.28949988e+00 3.06611806e-01 -1.68678626e-01 6.41853154e-01 -3.70648235e-01 -3.27770919e-01 -3.01667694e-02 -1.72430086e+00 5.11261284e-01 8.29858601e-01 -4.31620181e-01 -5.73464155e-01 1.41750440e-01 8.38615060e-01 -3.30883890e-01 -1.03893971e+00 2.99908873e-02 4.94967550e-01 -1.18315756e+00 7.09813774e-01 -1.08119833e+00 6.60373807e-01 -1.69345826e-01 -3.55043918e-01 -1.52899992e+00 -2.16629282e-02 -9.54552174e-01 -1.57535449e-02 1.69047368e+00 5.83545327e-01 -9.74309683e-01 1.07708347e+00 8.17434251e-01 2.18563437e-01 -6.86569691e-01 -9.24707472e-01 -5.25707603e-01 3.31106663e-01 7.15925882e-04 1.39722729e+00 1.13343728e+00 -6.29869223e-01 -1.88100889e-01 -4.43149865e-01 3.39306623e-01 8.16049278e-01 2.38536566e-01 1.09334862e+00 -1.27159178e+00 -4.09001768e-01 -2.15904102e-01 -4.37814504e-01 -1.43219233e-01 4.86638993e-01 -1.30053186e+00 -4.52231109e-01 -8.65252197e-01 1.04667991e-02 -2.95189112e-01 -1.48095950e-01 3.31799179e-01 -5.37403487e-03 5.54522276e-02 8.66412371e-02 2.35508922e-02 8.42907429e-02 5.92301130e-01 5.43933570e-01 -5.68152368e-02 -3.89791161e-01 1.23949781e-01 -1.20568669e+00 4.23790872e-01 9.81553495e-01 -9.11452293e-01 -2.07806110e-01 3.46642546e-02 -1.05238356e-01 2.91548632e-02 4.57070917e-01 -9.41716790e-01 -1.63155511e-01 1.20712020e-01 6.08507156e-01 -3.40138108e-01 -6.93746135e-02 -9.04009283e-01 9.11626339e-01 4.86042082e-01 -7.48555660e-01 1.81232139e-01 1.59105197e-01 6.85961068e-01 -1.32798061e-01 7.29057193e-02 6.61072075e-01 1.14960819e-01 -2.38310620e-01 3.21134210e-01 -1.87309563e-01 1.87641725e-01 1.22495711e+00 -2.49075457e-01 -2.30458185e-01 -4.66323406e-01 -7.60633469e-01 5.91895590e-03 1.14322543e+00 2.70173281e-01 1.36372194e-01 -1.23099709e+00 -9.38465893e-01 7.37394571e-01 5.01284711e-02 2.10083984e-02 6.03214046e-03 3.43518049e-01 -6.17449224e-01 1.17135011e-01 -3.92428964e-01 -2.68226087e-01 -1.02511883e+00 6.57108724e-01 5.55160344e-01 -3.07311118e-01 -8.43038380e-01 3.35465223e-01 2.00418252e-02 -7.85908163e-01 -4.31843027e-02 -1.86746478e-01 3.17901969e-01 1.87975839e-01 1.42476052e-01 3.07796180e-01 1.33394718e-01 -6.19579852e-01 -1.45759687e-01 -2.85402630e-02 -4.07168604e-02 -1.00327395e-01 1.62471688e+00 1.35711417e-01 -1.80246234e-01 3.07419091e-01 1.63676274e+00 3.21793139e-01 -1.31903160e+00 1.10779099e-01 7.42179295e-03 -6.25842273e-01 -2.13821828e-01 -6.22096717e-01 -1.17175078e+00 2.07513854e-01 4.56296206e-01 5.05246222e-01 9.84598815e-01 -1.63391531e-01 7.33522713e-01 1.53660446e-01 -1.71154439e-02 -6.52290523e-01 -7.15388656e-01 -2.11317971e-01 8.15931559e-01 -9.35590446e-01 7.43343905e-02 -3.24111581e-02 -9.66069877e-01 7.53264070e-01 2.11904764e-01 -3.47224265e-01 4.06548381e-01 -5.90519868e-02 1.48412827e-02 -6.50397465e-02 -6.14580572e-01 4.22418326e-01 1.40395150e-01 7.05543458e-01 -1.36270881e-01 1.50460973e-01 1.65231943e-01 6.45460248e-01 -9.54155862e-01 -2.25071639e-01 8.79539847e-01 4.92020607e-01 3.44325840e-01 -1.16403592e+00 -3.12581450e-01 8.50951970e-01 -6.86311126e-01 7.78659284e-02 -7.07612932e-01 9.70091939e-01 1.01120062e-01 4.26580489e-01 6.28834367e-01 -4.85481799e-01 3.55785459e-01 3.69080484e-01 -8.68904889e-02 -2.69236147e-01 -7.73743570e-01 -6.54171646e-01 1.98842302e-01 -6.50568247e-01 2.48614132e-01 -1.05545390e+00 -8.04102719e-01 -5.07910490e-01 3.50752592e-01 2.72124439e-01 5.20692527e-01 4.94259059e-01 5.94489694e-01 4.97161567e-01 8.12268496e-01 -5.22247374e-01 -6.61276340e-01 -5.11054575e-01 -6.95747972e-01 8.37128699e-01 5.96019864e-01 -1.21811815e-01 -5.31818688e-01 4.50485572e-02]	[6.190451145172119, 6.8487420082092285]
c9f9f2af-9070-4699-9d44-d8c2a52a3595	optimal-multi-agent-path-finding-for	2202.10449	null	https://arxiv.org/abs/2202.10449v1	https://arxiv.org/pdf/2202.10449v1.pdf	Optimal Multi-Agent Path Finding for Precedence Constrained Planning Tasks	Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple agents from their start locations to end locations. We consider an extension to this problem, Precedence Constrained Multi-Agent Path Finding (PC-MAPF), wherein agents are assigned a sequence of planning tasks that contain precedence constraints between them. PC-MAPF has various applications, for example in multi-agent pickup and delivery problems where some objects might require multiple agents to collaboratively pickup and move them in unison. Precedence constraints also arise in warehouse assembly problems where before a manufacturing task can begin, its input resources must be manufactured and delivered. We propose a novel algorithm, Precedence Constrained Conflict Based Search (PC-CBS), which finds makespan-optimal solutions for this class of problems. PC-CBS utilizes a Precedence-Constrained Task-Graph to define valid intervals for each planning task and updates them when precedence conflicts are encountered. We benchmark the performance of this algorithm over various warehouse assembly, and multi-agent pickup and delivery tasks, and use it to evaluate the sub-optimality of a recently proposed efficient baseline.	['Partha Pratim Chakrabarti', 'Aritra Hazra', 'Rajat Kumar Jenamani', 'Kushal Kedia']	2022-02-08	null	null	null	null	['multi-agent-path-finding']	['playing-games']	[ 3.20571840e-01 1.95357725e-02 -9.46803913e-02 -1.30782038e-01 -4.35693979e-01 -1.02483320e+00 2.29420245e-01 7.27344334e-01 -3.99744958e-01 1.10654628e+00 -1.03968017e-01 -2.28822619e-01 -1.14934146e+00 -8.75247896e-01 -4.73013401e-01 -5.57835162e-01 -9.97139394e-01 1.43025637e+00 6.54179096e-01 -4.41449612e-01 3.27703267e-01 8.52547109e-01 -7.98598468e-01 1.59275696e-01 5.49529731e-01 5.01380026e-01 1.01756155e+00 7.67528057e-01 -1.05681606e-01 1.30784035e-01 -8.99399817e-01 1.03965327e-01 5.53172708e-01 2.93208044e-02 -1.17274213e+00 3.01157773e-01 -7.16009259e-01 -3.94386172e-01 2.93899536e-01 6.80468380e-01 -6.61545433e-03 5.86764514e-01 5.42248130e-01 -2.35946178e+00 -1.73613012e-01 7.93338180e-01 -1.03055644e+00 3.66528898e-01 6.31042063e-01 -9.25777107e-02 7.68709660e-01 -1.98772371e-01 8.55733097e-01 1.34178150e+00 1.20231427e-01 8.33275914e-02 -9.24199402e-01 -8.27413276e-02 7.00317979e-01 2.03231841e-01 -7.86421597e-01 1.39458001e-01 2.23878443e-01 -1.57186195e-01 1.36999273e+00 3.24962854e-01 2.12887213e-01 1.94037899e-01 9.02160883e-01 4.51940775e-01 7.22229004e-01 -5.73168218e-01 4.01847094e-01 -4.88261461e-01 1.79787800e-01 3.36980462e-01 4.94796425e-01 -7.37563372e-02 -1.25888154e-01 -3.50224465e-01 5.25366008e-01 1.84012324e-01 -9.41768959e-02 -3.26302886e-01 -1.64125896e+00 8.50223303e-01 5.54631054e-02 1.57825992e-01 -8.63991916e-01 1.44507170e-01 3.89303416e-01 3.75128865e-01 -6.13900870e-02 6.78899527e-01 -6.70940161e-01 1.07535481e-01 -1.76943421e-01 7.36700773e-01 9.77436543e-01 1.52651775e+00 5.02685666e-01 -4.68343824e-01 -1.40694663e-01 4.78756338e-01 2.56132409e-02 2.80525506e-01 -4.93883520e-01 -1.35266864e+00 6.46635354e-01 3.03677440e-01 7.87607253e-01 -8.73209417e-01 -9.56452370e-01 3.18535715e-01 -3.50230962e-01 4.66116071e-01 2.94157326e-01 -2.68142879e-01 -6.76153064e-01 1.36838174e+00 6.58850014e-01 -1.17555842e-01 2.50307053e-01 1.10926020e+00 -1.13683753e-01 1.07677984e+00 -1.20054252e-01 -9.19786692e-01 1.36655772e+00 -1.49539483e+00 -8.74685526e-01 -1.75093964e-01 4.34044421e-01 -1.00159931e+00 9.83609632e-02 4.23211396e-01 -1.42917025e+00 3.21140327e-02 -9.65301335e-01 5.91643751e-01 -4.62709993e-01 -6.93527639e-01 6.64308488e-01 -2.41775643e-02 -9.73448396e-01 5.39124846e-01 -7.89834201e-01 -3.38228971e-01 -3.38672757e-01 4.75011647e-01 -4.40693170e-01 -6.91865504e-01 -7.94896245e-01 1.00657737e+00 5.00852704e-01 2.87145168e-01 -1.08946133e+00 -3.59410465e-01 -7.22271681e-01 -9.68972519e-02 1.38459861e+00 -4.94719148e-01 1.62660003e+00 -1.08899921e-01 -1.10973883e+00 -1.28086448e-01 -7.19179884e-02 3.63264084e-02 2.18317751e-02 3.32331866e-01 -4.43802655e-01 -5.26758246e-02 6.68038189e-01 1.88741088e-01 2.52370089e-01 -1.60161281e+00 -1.45737493e+00 -1.32752970e-01 6.28809571e-01 3.26607317e-01 5.73387384e-01 3.19165647e-01 -2.84245431e-01 -1.31029621e-01 7.54535347e-02 -1.31637418e+00 -9.61605489e-01 -7.85404265e-01 -6.60853207e-01 -5.76454282e-01 3.99814397e-01 -4.19667549e-02 8.83821428e-01 -1.67136419e+00 3.83904546e-01 4.16141152e-01 4.77746986e-02 -3.81199449e-01 -6.67466223e-01 1.41679835e+00 2.57650673e-01 -1.88785180e-01 1.47900516e-02 -2.05515176e-02 4.83199418e-01 6.92391634e-01 1.45375758e-01 3.40617329e-01 -1.01877905e-01 4.66144443e-01 -1.27667391e+00 -1.13427170e-01 -9.70370173e-02 -4.66127902e-01 -2.09523916e-01 -3.09248995e-02 -5.15661418e-01 -1.63592979e-01 -5.39175510e-01 6.31546736e-01 9.46162283e-01 2.11614072e-01 5.41381717e-01 3.19005787e-01 -6.48438156e-01 -2.09861305e-02 -1.47277141e+00 1.64103496e+00 -2.35641733e-01 9.87083688e-02 5.15496314e-01 -7.08601594e-01 5.57862282e-01 -4.83372202e-03 9.00510311e-01 -6.08021438e-01 -1.13843687e-01 1.47033662e-01 2.23391578e-01 -3.53861243e-01 9.69779372e-01 1.88381135e-01 -4.18587208e-01 8.81898403e-01 -5.99849105e-01 1.02805905e-01 1.03781903e+00 3.74725074e-01 1.61581612e+00 -2.22912297e-01 2.34314144e-01 -2.99535662e-01 3.11783433e-01 7.28618801e-01 7.68483222e-01 8.24502349e-01 -1.75116301e-01 -2.24788204e-01 4.10014212e-01 -4.70248967e-01 -4.90391225e-01 -1.09975493e+00 6.10568821e-01 1.32145953e+00 8.00756037e-01 -2.87343949e-01 -2.43702859e-01 -5.90015173e-01 2.31176212e-01 6.58230186e-01 -2.91803390e-01 4.17490512e-01 -8.40158880e-01 -4.62925941e-01 -6.23571634e-01 3.37904871e-01 -8.02574754e-02 -1.00809634e+00 -1.19157159e+00 1.01581073e+00 -4.12877165e-02 -1.23290682e+00 -9.90087152e-01 3.85449201e-01 -2.67587006e-01 -1.56860459e+00 -4.90746468e-01 -1.09376180e+00 1.00573897e+00 8.83169949e-01 7.99334705e-01 9.22628678e-03 -9.62900221e-02 3.10830683e-01 -6.51775718e-01 -7.08177447e-01 -3.16982239e-01 5.48256226e-02 1.59669861e-01 -5.28859437e-01 -2.10669741e-01 -1.41390264e-01 -3.88717055e-01 8.77987981e-01 -7.30058849e-01 -3.92168947e-02 5.46267569e-01 4.31514621e-01 8.37516129e-01 1.05649579e+00 9.42255914e-01 -6.02098405e-01 1.10552990e+00 -6.45895720e-01 -7.72183478e-01 6.74432039e-01 -3.05627316e-01 -5.02223551e-01 6.35222316e-01 -2.71471113e-01 -7.83074737e-01 -1.07221715e-01 7.62133539e-01 -6.41438514e-02 -1.31141067e-01 9.83319759e-01 -8.13106894e-02 9.59780812e-02 -4.24660444e-01 -3.36553931e-01 -1.61877409e-01 -1.23720810e-01 -1.19532794e-02 -7.53566995e-02 5.91846645e-01 -6.25493169e-01 5.40291846e-01 6.62892982e-02 6.07511997e-01 -6.10494390e-02 9.55329686e-02 -5.48214436e-01 -4.01402950e-01 -3.60342652e-01 5.99674582e-01 -8.94976929e-02 -1.26411915e+00 -7.60218361e-03 -1.52546585e+00 -5.23492455e-01 7.83055127e-02 3.64810199e-01 -6.56108499e-01 7.64020756e-02 -5.10820866e-01 -9.72650766e-01 9.97369140e-02 -1.18042791e+00 5.85969806e-01 1.11468568e-01 -2.02221319e-01 -8.54911149e-01 9.99042466e-02 -1.11748278e-01 1.21158510e-01 7.68881023e-01 1.06805885e+00 -8.20955873e-01 -7.35028267e-01 1.29784286e-01 3.57216522e-02 -8.20238352e-01 5.46865404e-01 -1.75785303e-01 5.76662302e-01 -6.51119113e-01 -5.78970790e-01 3.14595819e-01 -1.66470096e-01 6.51949167e-01 1.06301591e-01 -4.81538594e-01 -1.15615833e+00 -3.69137585e-01 1.56255329e+00 1.24698091e+00 4.37923633e-02 8.20653975e-01 3.16411369e-02 1.27472830e+00 1.56818616e+00 6.07445955e-01 8.96622419e-01 8.32049310e-01 7.10667014e-01 1.59084305e-01 4.82926667e-01 5.02570748e-01 1.83194429e-01 6.74515367e-01 -2.25406542e-01 -1.09183407e+00 -9.47849989e-01 7.60957956e-01 -2.33901882e+00 -6.53943956e-01 -4.36214834e-01 1.79741526e+00 2.65389949e-01 2.56552994e-01 3.92098606e-01 1.61625057e-01 8.51796329e-01 -3.19757164e-01 -5.00201166e-01 -9.64632452e-01 3.23524803e-01 -4.07869518e-01 7.03931034e-01 6.83989346e-01 -8.61037552e-01 4.91122723e-01 5.71182251e+00 2.22266585e-01 -2.47161433e-01 1.37114137e-01 -2.42493730e-02 -2.75530100e-01 -5.19741094e-03 -2.86985673e-02 -5.38865268e-01 3.28314066e-01 8.52802396e-01 -5.81207097e-01 8.02307129e-01 4.64493155e-01 5.11572897e-01 -7.48624563e-01 -1.29388130e+00 4.25471872e-01 -3.73467952e-01 -1.29003060e+00 -5.25257289e-01 1.52626947e-01 8.38996172e-01 -4.61410403e-01 -4.63978350e-01 -6.07805513e-02 8.77647042e-01 -4.85093981e-01 7.86602080e-01 9.17985812e-02 3.68909538e-02 -1.31994152e+00 6.51812971e-01 4.54663604e-01 -1.57201719e+00 -2.98969209e-01 -2.60400683e-01 -2.60533512e-01 1.20147228e+00 2.17051610e-01 -1.14040899e+00 1.30969667e+00 6.23787701e-01 -1.81633726e-01 5.84209979e-01 1.28575110e+00 2.15507254e-01 -6.78261340e-01 -3.67701471e-01 -1.99825674e-01 6.46270990e-01 -2.48039305e-01 7.04708219e-01 8.76784265e-01 3.48354995e-01 4.81042027e-01 1.20662034e+00 4.91724372e-01 6.11681819e-01 -2.58068979e-01 -3.75569731e-01 1.21014029e-01 9.13623989e-01 1.28674531e+00 -1.53440106e+00 1.84826136e-01 -2.43424475e-01 7.89678216e-01 -1.70193642e-01 4.16322976e-01 -9.19073701e-01 -8.14903498e-01 8.22680950e-01 -1.85920775e-01 2.48351425e-01 -7.15105176e-01 2.27314055e-01 1.94916129e-01 -6.81277588e-02 -3.77408385e-01 6.27502024e-01 -8.99812877e-01 -9.80463326e-01 7.17821777e-01 6.10501409e-01 -8.63245904e-01 -3.63794774e-01 -3.49234015e-01 -7.36658990e-01 6.95129514e-01 -1.81207061e+00 -7.82560945e-01 -3.71975303e-02 5.37957430e-01 1.13806307e+00 -3.59894261e-02 5.80590487e-01 3.27926241e-02 -5.53422511e-01 -6.23761825e-02 -5.78951724e-02 -5.77482641e-01 3.37817669e-01 -1.13903725e+00 2.21385002e-01 8.99380863e-01 -6.15532339e-01 4.43090618e-01 7.27208316e-01 -1.07729423e+00 -2.08769155e+00 -9.96323049e-01 6.67839050e-01 4.03976217e-02 6.24406934e-01 -1.09225430e-01 -3.53379756e-01 1.04369581e+00 6.44989192e-01 -5.28576851e-01 4.02074903e-01 -2.35273317e-01 6.15752995e-01 -1.94245763e-02 -1.12511861e+00 5.49874604e-01 1.09169340e+00 7.17150927e-01 -2.91337222e-01 7.06385493e-01 1.09796786e+00 -6.33340776e-01 -7.67165601e-01 2.42685348e-01 1.39191598e-01 -4.09459621e-01 6.04079604e-01 -6.36955261e-01 1.49406761e-01 -6.76927447e-01 -5.20253144e-02 -1.97741568e+00 -1.00660753e+00 -1.11561501e+00 4.37415719e-01 1.20531833e+00 6.27966166e-01 -8.75576913e-01 4.05141324e-01 7.63832271e-01 -8.75895441e-01 -7.50237048e-01 -1.01765656e+00 -1.31440115e+00 -4.87143487e-01 -3.25074792e-02 1.17686510e+00 9.13318157e-01 3.51693749e-01 1.09954260e-01 -6.44581541e-02 8.70301247e-01 6.12324178e-01 4.21771914e-01 5.05316496e-01 -1.09322977e+00 -9.16811228e-02 -1.41389444e-01 3.99465472e-01 -5.56282401e-01 1.64020032e-01 -7.89722383e-01 5.63166082e-01 -2.39927769e+00 -2.38471389e-01 -1.09133220e+00 -5.47939464e-02 7.49016404e-01 4.78617221e-01 -7.13613629e-01 7.41579294e-01 1.73636302e-01 -9.78247404e-01 -1.31194443e-01 1.56703484e+00 -1.76216856e-01 -4.96843845e-01 7.12421238e-02 -3.65931213e-01 2.51587451e-01 7.94815302e-01 -6.15602314e-01 -5.77892363e-01 -6.64155185e-01 3.11052442e-01 9.38063860e-01 -3.47157657e-01 -3.30469042e-01 8.48608971e-01 -1.16436446e+00 -3.89492631e-01 -9.06771600e-01 1.64410949e-01 -1.36464226e+00 7.40973413e-01 7.41329432e-01 -1.79407716e-01 1.19414890e+00 1.85560063e-01 6.92333162e-01 1.73965856e-01 -6.06470227e-01 -9.35334340e-02 -1.39559180e-01 -1.04773808e+00 2.35520452e-01 -9.10528481e-01 -5.02231598e-01 1.90896535e+00 -1.70633748e-01 -9.25369203e-01 6.09244257e-02 -6.92377210e-01 1.26064599e+00 8.68829433e-03 4.16203082e-01 7.22906291e-01 -1.05987632e+00 -6.78562105e-01 -2.51488268e-01 -2.86921680e-01 2.72969544e-01 3.13287109e-01 9.12185490e-01 -5.04889131e-01 6.03341758e-01 -5.28864324e-01 -2.44664311e-01 -1.13465261e+00 1.09267926e+00 -3.50883096e-01 -5.85570693e-01 -3.46457243e-01 6.10881090e-01 2.15212931e-03 -1.02083944e-01 7.59870112e-02 -5.34551382e-01 -1.57685932e-02 1.03808381e-01 6.79840505e-01 9.85159874e-01 2.95508802e-02 -2.28307433e-02 -8.80744159e-01 2.19275445e-01 -3.08551311e-01 -2.72554189e-01 1.47941244e+00 -3.00792694e-01 -4.93465066e-01 -3.74381803e-03 3.62112135e-01 -9.81544331e-02 -9.54533637e-01 9.73493680e-02 3.97679895e-01 -6.64502740e-01 -4.14167494e-01 -1.13610971e+00 -9.33048964e-01 -3.15681487e-01 -2.13367298e-01 8.73441041e-01 1.20118797e+00 3.95012312e-02 7.63487220e-01 3.63136411e-01 1.09073246e+00 -1.03332949e+00 1.21160507e-01 7.93926775e-01 1.02460802e+00 -5.27393818e-01 -7.25758895e-02 -1.02209508e+00 -6.32759869e-01 1.08906221e+00 7.53270984e-01 -1.44540211e-02 2.66113490e-01 8.73357058e-01 -3.45943093e-01 -2.21070200e-01 -9.77296650e-01 -2.06901416e-01 -6.14626408e-01 1.02702177e+00 -4.56732422e-01 3.28378052e-01 -6.20805264e-01 4.36563402e-01 8.01516101e-02 -1.74249202e-01 1.10409725e+00 1.70539415e+00 -5.09158671e-01 -1.22211444e+00 -7.10856140e-01 1.79079548e-01 1.14478596e-01 4.69439954e-01 -5.18070832e-02 1.05792058e+00 5.48083745e-02 1.50852811e+00 4.31505561e-01 -1.61490843e-01 8.79874587e-01 -3.59754026e-01 6.48568630e-01 -7.72470176e-01 -6.31925464e-01 3.60827059e-01 7.28145659e-01 -4.85332876e-01 -5.16763210e-01 -8.05861533e-01 -1.90651023e+00 -4.82677430e-01 -3.00748259e-01 3.82847756e-01 6.48032725e-01 8.54060948e-01 2.61810899e-01 1.12534702e+00 8.22866201e-01 -1.13057017e+00 -7.46069402e-02 -4.01512802e-01 -7.35418081e-01 -2.83376396e-01 1.52414054e-01 -9.97799277e-01 2.90521115e-01 -3.67346913e-01]	[4.965420246124268, 1.7447339296340942]
8e84cb96-709f-4b8d-ab7f-13748728eb7b	tragedy-plus-time-capturing-unintended-human	2204.13548	null	https://arxiv.org/abs/2204.13548v1	https://arxiv.org/pdf/2204.13548v1.pdf	Tragedy Plus Time: Capturing Unintended Human Activities from Weakly-labeled Videos	In videos that contain actions performed unintentionally, agents do not achieve their desired goals. In such videos, it is challenging for computer vision systems to understand high-level concepts such as goal-directed behavior, an ability present in humans from a very early age. Inculcating this ability in artificially intelligent agents would make them better social learners by allowing them to evaluate human action under a teleological lens. To validate the ability of deep learning models to perform this task, we curate the W-Oops dataset, built upon the Oops dataset [15]. W-Oops consists of 2,100 unintentional human action videos, with 44 goal-directed and 30 unintentional video-level activity labels collected through human annotations. Due to the expensive segment annotation procedure, we propose a weakly supervised algorithm for localizing the goal-directed as well as unintentional temporal regions in the video leveraging solely video-level labels. In particular, we employ an attention mechanism-based strategy that predicts the temporal regions which contribute the most to a classification task. Meanwhile, our designed overlap regularization allows the model to focus on distinct portions of the video for inferring the goal-directed and unintentional activity while guaranteeing their temporal ordering. Extensive quantitative experiments verify the validity of our localization method. We further conduct a video captioning experiment which demonstrates that the proposed localization module does indeed assist teleological action understanding.	['Yezhou Yang', 'Zhiyuan Fang', 'Arnav Chakravarthy']	2022-04-28	null	null	null	null	['action-understanding']	['computer-vision']	[ 3.6603925e-01 3.7118456e-01 -4.2241758e-01 -1.6654672e-01 -1.7546481e-01 -4.3019921e-01 7.4336511e-01 -2.7860129e-01 -5.8051306e-01 5.6347382e-01 3.3826315e-01 4.7440663e-02 -9.0069570e-02 -4.5930958e-01 -9.4637150e-01 -6.8811882e-01 -4.8923361e-01 1.5481021e-01 1.1718652e-01 7.6685958e-02 1.8925788e-01 1.4708744e-01 -1.6299163e+00 4.0716162e-01 6.9818169e-01 9.6198380e-01 2.6350442e-01 5.7315183e-01 4.3444860e-01 1.5230572e+00 -5.6036180e-01 -2.4113131e-01 3.7761310e-01 -5.5697781e-01 -6.8442559e-01 5.3738415e-01 5.0473458e-01 -7.9472840e-01 -7.5235212e-01 1.0614622e+00 -1.3024162e-01 4.0889427e-01 5.5900031e-01 -1.8116101e+00 -6.6826653e-01 4.9868679e-01 -2.1226260e-01 3.9551088e-01 8.6460429e-01 6.1835355e-01 1.0543249e+00 -3.7097931e-01 7.3790896e-01 1.1371784e+00 3.5383904e-01 7.1677905e-01 -8.0678725e-01 -4.9887690e-01 4.7926489e-01 5.8121419e-01 -1.0740852e+00 -3.1243303e-01 1.0733236e+00 -6.9988269e-01 7.7040082e-01 9.2258587e-02 1.0485215e+00 1.7657113e+00 1.4170881e-02 1.1730385e+00 8.3406377e-01 3.8313765e-02 3.0244547e-01 -2.3441964e-01 -1.2471742e-01 1.0786508e+00 2.9539585e-02 3.4228408e-01 -6.9082522e-01 4.1640885e-02 8.0702704e-01 3.4454590e-01 -5.6335527e-01 -4.4383055e-01 -1.5868214e+00 5.7056481e-01 3.4067583e-01 2.8226319e-01 -5.8812153e-01 3.9060462e-01 4.0874434e-01 1.7990600e-01 3.0370247e-01 3.8175890e-01 -4.0493324e-01 -3.8791752e-01 -5.7432103e-01 1.9542383e-01 4.3846124e-01 1.0031402e+00 5.4861695e-01 -6.1124820e-02 -4.6843401e-01 3.4320781e-01 1.9967856e-01 2.2915834e-01 5.5479413e-01 -1.2827737e+00 4.5266274e-01 8.9042008e-01 4.3862244e-01 -1.1243409e+00 -4.4999102e-01 -1.4975728e-01 -3.4827378e-01 6.2786199e-02 6.9142723e-01 -9.7410917e-02 -7.6036137e-01 2.0194249e+00 2.6586670e-01 6.4276898e-01 -2.3409543e-03 1.1102718e+00 3.4552112e-01 4.8281780e-01 3.8605648e-01 -3.9145744e-01 1.3588326e+00 -1.1575793e+00 -7.2541153e-01 -1.1199042e-01 7.4320966e-01 2.1455748e-02 1.1525295e+00 1.8582088e-01 -6.1403656e-01 -3.9424869e-01 -7.3819947e-01 1.2677953e-01 -1.4523911e-01 6.4031988e-02 7.5934500e-01 1.6819668e-01 -5.5887347e-01 4.8417154e-01 -1.0310726e+00 -2.8861654e-01 6.9238412e-01 1.3362551e-01 -5.5692261e-01 1.5154222e-01 -1.0769089e+00 6.0304248e-01 5.5936432e-01 -1.3238576e-01 -1.6890653e+00 -4.5923275e-01 -1.0605215e+00 -2.0316187e-02 7.5694507e-01 -2.8329751e-01 1.1261187e+00 -1.4038004e+00 -1.2555515e+00 8.6878097e-01 -2.6677545e-02 -7.2969443e-01 7.2352982e-01 -1.6319455e-01 -2.9098698e-01 6.4124388e-01 1.0915670e-01 8.0259013e-01 1.0612971e+00 -1.0439320e+00 -8.7992126e-01 -3.5436580e-01 6.3219142e-01 2.7942079e-01 -5.9405750e-01 -1.4341265e-01 -3.3820841e-01 -8.0073291e-01 -1.1580142e-01 -1.0184971e+00 1.4002290e-01 1.8777207e-01 -3.5047129e-01 -5.1897007e-01 8.4923339e-01 -7.2414136e-01 1.0263268e+00 -2.0324194e+00 3.1535611e-01 -2.8698781e-01 4.1905221e-01 8.9648791e-02 -1.5025902e-01 2.3956738e-01 6.8060488e-02 -1.2648055e-01 -1.3147651e-01 -1.9470763e-01 7.8611173e-02 2.0618299e-01 -2.4363624e-01 6.8299639e-01 -4.9682856e-02 9.6544868e-01 -1.2961284e+00 -5.2125180e-01 2.8319085e-01 2.5927487e-01 -6.0624111e-01 5.1362163e-01 -4.6964952e-01 8.0668324e-01 -7.3559880e-01 9.7243512e-01 -5.6421857e-02 -1.9635731e-01 1.1719778e-01 -1.5969336e-01 8.8063255e-02 7.8438520e-02 -3.5159335e-01 1.6351638e+00 -2.2023714e-01 7.6181012e-01 -8.5601360e-02 -1.2150770e+00 3.2775313e-01 5.9192210e-01 9.9676883e-01 -6.0963959e-01 2.0680112e-01 -2.2138655e-01 3.8291898e-02 -1.1536392e+00 5.5552449e-02 8.3449878e-02 -2.2067928e-01 3.5899365e-01 1.9452351e-01 4.7854006e-01 3.2550490e-01 1.8856873e-01 1.4969474e+00 5.2597570e-01 3.7758330e-01 7.4768484e-02 5.2382213e-01 1.6178969e-01 8.0211520e-01 7.6642644e-01 -9.0708476e-01 2.0294292e-01 6.5286666e-01 -7.0919216e-01 -9.0713948e-01 -7.0882320e-01 3.7927082e-01 1.3544350e+00 3.3419350e-01 -3.0050638e-01 -9.7308391e-01 -1.2050024e+00 -2.7480751e-01 7.7329808e-01 -9.0985996e-01 -4.6109569e-01 -5.7732749e-01 -2.7672306e-01 5.0333720e-01 5.2404404e-01 6.6790122e-01 -1.3546139e+00 -9.4720906e-01 6.4471066e-02 -5.1688659e-01 -1.4214942e+00 -5.4141933e-01 -1.8983966e-01 -4.4771931e-01 -1.4132390e+00 -6.0513210e-01 -7.0602673e-01 9.1153020e-01 2.8598171e-01 8.0491245e-01 1.9556603e-01 3.3820666e-02 8.1127638e-01 -6.1660272e-01 -4.9035251e-02 -2.5746223e-01 -4.8903242e-01 3.1887719e-01 3.3302319e-01 6.5626401e-01 -6.2817532e-01 -5.8527637e-01 5.6871086e-01 -7.0481718e-01 1.9171435e-01 3.5973114e-01 6.3787627e-01 1.7203884e-01 1.3996282e-01 3.5894501e-01 -4.5701277e-01 3.0493620e-01 -5.9691113e-01 -4.7539929e-01 2.4927804e-01 -2.7375972e-02 -2.8284645e-01 7.8272438e-01 -9.2351097e-01 -8.5536414e-01 2.0358452e-01 2.2815053e-01 -7.4703151e-01 -4.4917667e-01 1.8863027e-01 -1.8674032e-01 1.2848750e-01 3.9437285e-01 5.0898230e-01 -1.5140758e-01 2.8722830e-02 5.8195010e-02 4.7213376e-01 4.9397877e-01 -5.3248161e-01 6.8405801e-01 6.9715238e-01 -3.3265108e-01 -7.8258038e-01 -1.0907149e+00 -4.5317262e-01 -4.0277323e-01 -8.0984771e-01 1.1710160e+00 -1.0332440e+00 -1.2090658e+00 5.1279545e-01 -9.7848785e-01 -6.1636055e-01 -1.3276751e-01 6.4316434e-01 -1.1626781e+00 4.5812607e-01 -4.6463510e-01 -7.6865613e-01 1.9521117e-01 -1.0978832e+00 1.0657525e+00 1.9566016e-02 -2.1421415e-01 -8.2915384e-01 -1.7797066e-01 7.2872114e-01 -1.6852254e-01 2.5400236e-01 5.2599740e-01 -8.7794197e-01 -7.1251631e-01 -1.7533050e-01 2.2236729e-02 1.9363683e-01 1.4085476e-01 -3.5137767e-01 -7.4116713e-01 -1.1233035e-01 1.0928980e-01 -6.5797263e-01 7.4869043e-01 2.1969286e-01 1.2944365e+00 -6.3776767e-01 -2.8566611e-01 4.4513956e-01 8.4677589e-01 4.5632654e-01 5.4632878e-01 1.9740038e-01 7.3633069e-01 7.6309043e-01 8.6443150e-01 6.0501951e-01 3.7465784e-01 8.4697503e-01 9.5016533e-01 3.4109440e-01 3.8433399e-02 -4.7396353e-01 9.2747813e-01 2.4480446e-01 -4.9050501e-01 -5.6657529e-01 -6.2326813e-01 6.7291206e-01 -2.1586430e+00 -1.5093691e+00 2.0858176e-01 2.0403647e+00 6.1224222e-01 7.9826050e-02 1.6988060e-01 -1.6220690e-01 7.2558481e-01 3.7509170e-01 -7.0848107e-01 2.0878842e-01 2.4286604e-01 -6.6047204e-01 2.7983868e-01 1.8431582e-01 -1.4042445e+00 9.8502827e-01 5.4618497e+00 5.8828568e-01 -8.6607808e-01 1.2322007e-01 3.8575876e-01 -1.7341365e-01 -4.2265832e-02 -3.7770355e-01 -5.2028382e-01 7.8724605e-01 6.8679792e-01 3.5071891e-02 6.7355990e-01 1.0293757e+00 7.0065528e-01 7.9762302e-02 -1.3987496e+00 8.4392011e-01 3.5664353e-01 -9.8448825e-01 -1.1175483e-01 9.8517947e-02 6.0584366e-01 -1.9765832e-01 -8.4861398e-02 5.6099212e-01 2.4934442e-01 -9.0827823e-01 9.2182922e-01 6.0738373e-01 3.9848864e-01 -2.9539245e-01 3.7948719e-01 6.7916179e-01 -1.0550374e+00 -5.0297397e-01 -9.9220648e-02 -2.1703841e-01 1.6353375e-01 -4.1768190e-02 -6.6997516e-01 -6.1899528e-02 5.6507015e-01 1.0313896e+00 -2.7861065e-01 6.7225403e-01 -6.3417977e-01 5.8322650e-01 -1.6900571e-01 1.3928898e-03 4.1731250e-01 -2.2850122e-01 8.0783039e-01 7.0089263e-01 3.1454575e-01 2.7683055e-01 2.9290172e-01 8.9617854e-01 -9.9357799e-02 -3.4878165e-01 -9.2449623e-01 -4.4241264e-01 3.0825323e-01 9.1667438e-01 -6.6964602e-01 -4.9107897e-01 -4.3496019e-01 1.1806306e+00 4.9931616e-01 4.9127230e-01 -1.3814875e+00 1.0272921e-01 8.9452052e-01 5.0967142e-02 2.1301779e-01 -3.1250808e-01 3.7953830e-01 -1.4841847e+00 5.7392552e-02 -8.4865928e-01 1.8276085e-01 -8.3223778e-01 -7.7009273e-01 3.9881417e-01 -1.7359708e-02 -1.5523604e+00 -4.7957957e-01 -5.0212914e-01 -4.9497974e-01 -6.8044715e-02 -1.0866867e+00 -1.1397073e+00 -5.9058005e-01 8.3580494e-01 9.9329948e-01 -2.3109132e-01 3.9094245e-01 1.8637416e-01 -7.0720142e-01 3.2086596e-01 -5.1558650e-01 3.4670258e-01 3.4127679e-01 -9.7385949e-01 -2.0729950e-01 8.8391751e-01 3.0621973e-01 4.8825201e-01 8.5419863e-01 -7.0667911e-01 -1.2764819e+00 -1.3278242e+00 5.4097438e-01 -5.6250215e-01 7.5941873e-01 -3.0983198e-01 -6.1884260e-01 1.2213070e+00 -3.4856033e-02 1.9212803e-01 4.7122151e-01 -4.2400825e-01 -2.4687327e-01 3.4848836e-01 -1.0667189e+00 7.6193076e-01 1.6597322e+00 -4.3766800e-01 -9.7208172e-01 7.4813581e-01 8.5566717e-01 -1.0831533e-01 -5.5483252e-01 3.7885958e-01 6.0294843e-01 -1.0270439e+00 1.0106175e+00 -9.1630799e-01 7.1024084e-01 -2.7091014e-01 -3.3151429e-02 -1.1395757e+00 -1.4032397e-01 -5.8061665e-01 -5.3302562e-01 8.9197189e-01 -2.0226095e-02 -2.5096834e-01 1.0003406e+00 5.2978033e-01 -2.9801953e-01 -4.3629551e-01 -8.4921128e-01 -9.8647606e-01 -6.1554098e-01 -5.6215227e-01 2.3895518e-01 1.0764195e+00 2.5273430e-01 -1.8172659e-01 -9.3044734e-01 2.6128352e-01 6.7758125e-01 -1.6253199e-02 6.5833384e-01 -8.9683747e-01 -1.3297145e-01 -2.7495846e-01 -6.5346307e-01 -1.2704430e+00 6.7975235e-01 -5.8295864e-01 2.4112374e-01 -1.1145854e+00 6.3896433e-02 -8.6581543e-02 -2.2125906e-01 7.9736382e-01 -1.4873490e-02 3.3249271e-01 -6.0099568e-02 3.4159496e-01 -1.0314755e+00 7.8191894e-01 1.3066229e+00 -3.1482032e-01 -8.6705238e-02 -8.8736042e-02 -1.5405862e-01 1.1738012e+00 5.6615096e-01 -3.7700552e-01 -6.3133824e-01 -2.0488232e-01 -1.6219522e-01 2.4560922e-01 7.7985275e-01 -1.0882009e+00 9.9178299e-02 -5.6912524e-01 4.6065683e-03 -8.4069505e-02 4.6860573e-01 -1.1379062e+00 -1.1210200e-01 6.1142516e-01 -5.9141171e-01 -5.0363189e-01 -3.3113170e-01 9.6776938e-01 -1.8203028e-01 -1.6018115e-01 5.1058078e-01 -3.0714718e-01 -1.1216865e+00 4.6413177e-01 -6.9525492e-01 1.5872860e-02 1.6531191e+00 -2.0464851e-01 -3.3395222e-01 -5.1733387e-01 -8.5196066e-01 3.9054760e-01 4.5960018e-01 5.1210821e-01 6.5467387e-01 -1.2656481e+00 -3.6155713e-01 1.6183546e-01 4.3808344e-01 -4.4777775e-01 3.1108546e-01 1.0044245e+00 -4.1252190e-01 4.2751771e-01 -4.1402122e-01 -4.6234593e-01 -1.0331035e+00 9.4964135e-01 3.0296162e-01 4.8195850e-02 -8.1032968e-01 8.3938444e-01 5.5766064e-01 -6.2745221e-02 4.6013129e-01 -3.4980929e-01 -4.1891575e-01 -8.7749511e-03 6.9483727e-01 3.3163980e-01 -5.3617835e-01 -8.7943053e-01 -3.1793991e-01 9.6857019e-02 5.1863559e-02 2.3347892e-01 1.2164792e+00 -1.4198330e-01 1.9459519e-01 1.3036852e-01 1.0519936e+00 -3.4835494e-01 -1.9786249e+00 1.1528656e-01 -1.2832063e-01 -5.3207809e-01 -7.2947391e-03 -5.6708229e-01 -1.1207117e+00 6.8478978e-01 2.2411749e-01 3.0873248e-01 1.0031509e+00 6.1949372e-02 8.2285571e-01 4.6811655e-01 7.9022813e-01 -9.7757638e-01 5.5716103e-01 2.5173968e-01 8.9114928e-01 -1.4128195e+00 -3.0340046e-01 -3.7968901e-01 -7.4824643e-01 8.1106853e-01 9.3650693e-01 -1.2870039e-01 1.8206021e-01 -2.1160096e-01 -2.8893951e-01 -3.5241064e-01 -9.2773980e-01 -2.7265048e-01 8.5576199e-02 7.2415781e-01 -7.1131662e-02 -6.8775483e-04 -1.8638046e-01 4.9145782e-01 1.7410731e-01 1.0870200e-01 6.0983992e-01 8.2695723e-01 -4.8649475e-01 -4.7571626e-01 -1.6507785e-01 3.1090775e-01 -2.8977627e-01 3.0536181e-01 -3.5616177e-01 6.6234398e-01 2.4699181e-01 9.4622260e-01 9.2842691e-02 -5.0195932e-01 3.1392965e-02 7.1996979e-02 3.9896259e-01 -5.6292218e-01 -2.1087644e-01 -1.7772637e-01 1.2042030e-01 -1.0691735e+00 -7.4435210e-01 -7.9181647e-01 -1.2959970e+00 -2.3725862e-02 1.9184522e-02 -7.3867247e-02 2.4652706e-01 1.1790290e+00 1.4265265e-01 5.2236992e-01 4.1646779e-01 -1.0022013e+00 -3.4139651e-01 -9.5569515e-01 -4.1174543e-01 8.6970919e-01 4.3014821e-01 -1.0572054e+00 -7.0061117e-01 4.7032130e-01]	[8.512505531311035, 0.7234265208244324]
6b1e8da7-cf1c-4a2c-92e9-770b51ca12a7	robust-image-protection-countering-cropping	2206.02405	null	https://arxiv.org/abs/2206.02405v5	https://arxiv.org/pdf/2206.02405v5.pdf	Image Protection for Robust Cropping Localization and Recovery	Existing image cropping detection schemes ignore that recovering the cropped-out contents can unveil the purpose of the behaved cropping attack. This paper presents \textbf{CLR}-Net, a novel image protection scheme addressing the combined challenge of image \textbf{C}ropping \textbf{L}ocalization and \textbf{R}ecovery. We first protect the original image by introducing imperceptible perturbations. Then, typical image post-processing attacks are simulated to erode the protected image. On the recipient's side, we predict the cropping mask and recover the original image. Besides, we propose a novel \textbf{F}ine-\textbf{G}rained generative \textbf{JPEG} simulator (FG-JPEG) as well as a feature alignment network to improve the real-world robustness. Comprehensive experiments prove that the quality of the recovered image and the accuracy of crop localization are both satisfactory.	['Xinpeng Zhang', 'Zhenxing Qian', 'Xiaoxiao Hu', 'Sheng Li', 'Hang Zhou', 'Qichao Ying']	2022-06-06	null	null	null	null	['image-cropping']	['computer-vision']	[ 9.43764865e-01 -1.35362431e-01 8.93667862e-02 7.16185644e-02 -6.67550981e-01 -1.25639224e+00 1.94793269e-01 4.80473787e-02 1.06138326e-02 2.90992051e-01 -1.41518652e-01 -6.03321433e-01 3.96254152e-01 -7.86400676e-01 -1.16057730e+00 -1.02818573e+00 8.16390067e-02 -7.88219929e-01 1.56989217e-01 -2.75868922e-01 5.07031322e-01 4.34437364e-01 -1.24957097e+00 2.13252530e-01 9.37720656e-01 9.57186878e-01 5.49953520e-01 1.05377948e+00 7.03196943e-01 5.01091599e-01 -9.28944349e-01 -5.58189154e-01 6.43154144e-01 -2.05999240e-01 -2.07258910e-01 3.28091800e-01 2.34018520e-01 -7.57885516e-01 -5.86027682e-01 1.58803487e+00 3.28619599e-01 -6.69309139e-01 5.11972308e-01 -1.45021605e+00 -9.01534259e-01 4.37503099e-01 -9.81147289e-01 -7.82505572e-02 3.43076468e-01 3.16460997e-01 1.94528863e-01 -7.17927694e-01 5.33197045e-01 8.73805702e-01 5.53909242e-01 1.36699885e-01 -9.86852050e-01 -1.10098851e+00 -1.68572351e-01 -1.63496166e-01 -1.52313280e+00 -1.48269862e-01 6.43983543e-01 8.92112218e-03 1.05034903e-01 6.48777843e-01 1.15748346e-01 8.92704010e-01 6.16383493e-01 6.47251666e-01 1.27963269e+00 -7.25694895e-01 -2.72601634e-01 1.11644804e-01 -2.22246125e-02 6.69202447e-01 6.85602725e-01 3.97459418e-01 -3.85162652e-01 -2.89839327e-01 7.96312034e-01 -1.20695740e-01 -8.70783091e-01 -7.96082020e-02 -1.11285257e+00 4.14018095e-01 3.94904703e-01 -8.14710036e-02 -1.70856118e-01 2.66750306e-01 1.24357551e-01 2.79433221e-01 7.93798268e-02 -5.91876321e-02 -6.69684708e-02 7.92417288e-01 -8.83051276e-01 1.56899750e-01 3.63673329e-01 1.34336150e+00 6.85031176e-01 2.15862542e-01 7.11009726e-02 2.37782180e-01 3.96881104e-01 1.20646107e+00 3.97463925e-02 -6.80222631e-01 7.64592290e-01 -1.33707905e-02 4.68718648e-01 -1.53314650e+00 2.57487416e-01 2.52439696e-02 -1.04131174e+00 5.39385974e-01 2.33032286e-01 -3.10180575e-01 -9.57961321e-01 1.32557750e+00 -6.72662407e-02 -2.25233077e-03 3.22620690e-01 6.82254255e-01 2.00899377e-01 9.79098201e-01 -7.35458434e-02 -1.20414384e-01 1.55660975e+00 -5.59676707e-01 -7.45498836e-01 -5.48968948e-02 3.32492799e-01 -1.22310150e+00 6.28893256e-01 6.69805467e-01 -8.14431071e-01 -5.98640084e-01 -1.77263868e+00 1.53545916e-01 -3.97034913e-01 4.09167796e-01 1.03975475e-01 1.43686855e+00 -9.58448350e-01 2.08372250e-01 -3.07447284e-01 -2.71335356e-02 2.02924028e-01 2.45287403e-01 -5.07132947e-01 -3.27525258e-01 -1.13991404e+00 3.69776368e-01 6.36606753e-01 3.23454559e-01 -1.24893224e+00 -4.39937413e-01 -8.78641129e-01 3.11145466e-02 1.57390565e-01 -5.45585789e-02 5.91782391e-01 -8.81030738e-01 -8.06977153e-01 8.87205184e-01 9.31425542e-02 -5.96493661e-01 6.00752831e-01 -3.44483763e-01 -6.57843649e-01 4.68063444e-01 9.35064107e-02 6.07138515e-01 1.56195509e+00 -1.71142459e+00 -3.86711091e-01 -3.68165195e-01 -4.88602370e-01 4.72446978e-02 -4.36265290e-01 1.68747708e-01 -3.31430584e-01 -1.34266627e+00 9.46014598e-02 -9.33683753e-01 -7.49249458e-02 9.07827392e-02 -1.10230267e+00 9.27662492e-01 1.38441074e+00 -1.07311690e+00 1.25259852e+00 -2.46175504e+00 -4.27192003e-01 5.37650228e-01 -1.57267421e-01 6.58425570e-01 -2.93998003e-01 7.65121698e-01 -3.39872450e-01 3.54291111e-01 -4.53164458e-01 4.09930479e-03 -4.14906114e-01 -9.10266712e-02 -1.02180052e+00 9.94278431e-01 1.40192911e-01 5.54583907e-01 -2.51529515e-01 -1.66371197e-01 1.86377481e-01 4.73393440e-01 -3.82614583e-02 2.30578572e-01 -1.08780719e-01 2.25275472e-01 -3.20043296e-01 6.97223842e-01 1.56254244e+00 2.98953831e-01 1.79954261e-01 -2.27757066e-01 -7.91209638e-02 -7.08904505e-01 -1.22305310e+00 9.92326140e-01 4.03705165e-02 4.74672496e-01 3.90680432e-01 -4.61454779e-01 1.15668261e+00 2.96211332e-01 6.04764260e-02 -4.35018688e-01 3.43503565e-01 1.35874927e-01 -6.96259916e-01 -4.14794475e-01 8.39933157e-01 7.55578816e-01 -2.88819671e-01 5.38095415e-01 -3.98638964e-01 -1.56996474e-01 -3.25709075e-01 2.31124341e-01 7.42191076e-01 3.69934797e-01 7.23878294e-02 -4.52180624e-01 5.37792981e-01 -4.32213675e-03 2.19091639e-01 8.01493883e-01 4.01796773e-02 8.61132264e-01 2.69320101e-01 -5.01852669e-02 -1.17465639e+00 -7.87553608e-01 -1.52790211e-02 7.24337459e-01 9.27893996e-01 -1.88675120e-01 -1.28382158e+00 -7.20211208e-01 -8.00813958e-02 7.50025511e-01 -5.44637561e-01 -1.14341430e-01 -6.18029475e-01 -9.74348366e-01 1.25067675e+00 1.87167779e-01 8.90479147e-01 -8.74819338e-01 -7.00650394e-01 -5.37566952e-02 -5.31752467e-01 -1.22812700e+00 -8.12336802e-01 1.27980217e-01 -4.01811063e-01 -1.25411367e+00 -8.88873279e-01 -1.00232518e+00 1.04977262e+00 8.08573008e-01 4.12860066e-01 5.17600298e-01 -3.66186291e-01 -5.30969128e-02 -5.07576346e-01 -5.86459816e-01 -8.13624144e-01 -4.71365571e-01 -2.88551658e-01 7.51816556e-02 2.98109632e-02 -1.88398376e-01 -7.69078314e-01 5.69949031e-01 -1.47573674e+00 9.22352821e-03 4.00072932e-01 5.00949383e-01 3.53788018e-01 6.51269019e-01 6.57666922e-02 -5.82510889e-01 3.39661092e-01 -5.64428233e-02 -7.37950802e-01 5.44895768e-01 -5.03271580e-01 -2.10447013e-01 7.52050757e-01 -4.37302560e-01 -1.01726031e+00 1.65664628e-01 1.26920804e-01 -2.47282594e-01 -2.48954996e-01 -2.21191525e-01 -5.63940048e-01 -4.29333568e-01 4.82994676e-01 7.63492048e-01 -2.03656882e-01 -2.55852669e-01 4.15466547e-01 8.12726736e-01 1.17331052e+00 -1.43628985e-01 1.62066650e+00 6.27971351e-01 -7.74020925e-02 -8.46972644e-01 -1.23542070e-01 6.06295951e-02 -2.12854654e-01 -1.81304410e-01 7.59188831e-01 -1.08737695e+00 -8.51867139e-01 1.14664376e+00 -1.15938425e+00 2.12073158e-02 3.31759185e-01 6.26642630e-02 -4.49185371e-01 1.11154962e+00 -4.43417579e-01 -7.89599836e-01 -6.16013408e-01 -1.28085566e+00 1.28102326e+00 2.11274579e-01 5.00995457e-01 -2.76620895e-01 -4.80787188e-01 3.80175352e-01 8.80823731e-02 7.03769624e-01 9.11212564e-01 -1.32638812e-01 -8.26794028e-01 -5.60531795e-01 -6.92319632e-01 4.06559795e-01 -2.42602006e-02 -4.78165038e-02 -9.02652264e-01 -6.58424079e-01 2.02333152e-01 -5.92906848e-02 6.49205029e-01 1.60058752e-01 1.02185261e+00 -4.39464271e-01 -2.87418008e-01 9.32451189e-01 1.84853303e+00 3.43555838e-01 1.25932682e+00 2.60987729e-01 4.62966651e-01 2.55312502e-01 9.23751831e-01 4.59355861e-01 -6.43324628e-02 1.84237629e-01 1.03394580e+00 -2.41053119e-01 -1.35403778e-02 -5.31642079e-01 6.87437952e-01 1.42192349e-01 3.14687759e-01 -9.54397559e-01 -3.41118455e-01 3.61107707e-01 -1.25532925e+00 -8.01966071e-01 -2.75975883e-01 2.23330235e+00 4.65767562e-01 1.98860280e-02 -5.21674156e-01 2.82217503e-01 1.32362854e+00 4.94810939e-01 -4.49557811e-01 -2.34878242e-01 -4.64544654e-01 7.06251105e-03 1.34703398e+00 2.86755025e-01 -1.31435537e+00 8.63944232e-01 5.53370476e+00 1.03606188e+00 -1.10216069e+00 -1.83781087e-01 6.91158116e-01 8.82377148e-01 -2.12248504e-01 2.41148829e-01 -8.37095797e-01 6.19868457e-01 3.76756489e-01 1.25020202e-02 2.49025837e-01 5.40092170e-01 5.11020645e-02 -3.49672437e-01 -1.88730732e-01 4.74928200e-01 5.67840934e-01 -9.17490244e-01 -1.74870081e-02 2.30124965e-01 2.61551946e-01 -7.13991880e-01 3.26749444e-01 -4.10811812e-01 5.26877880e-01 -9.54070568e-01 9.44524527e-01 5.39965630e-02 1.28015685e+00 -8.02625656e-01 3.44194531e-01 4.65263724e-01 -1.35643005e+00 -8.51490125e-02 -4.85255092e-01 6.70620024e-01 1.90525383e-01 4.03630704e-01 -5.96807659e-01 9.23172235e-01 9.08060312e-01 1.50204480e-01 -7.41257429e-01 6.10077262e-01 -5.22181869e-01 6.52022243e-01 -1.70655742e-01 3.45406801e-01 8.53048339e-02 -4.23464477e-02 7.41375506e-01 1.18352914e+00 6.71166837e-01 2.67873053e-03 3.97126712e-02 4.48361903e-01 -1.99768588e-01 -5.19659519e-02 -7.04795003e-01 7.79379010e-02 4.32485819e-01 9.22041655e-01 -7.62531042e-01 1.26138717e-01 9.82595533e-02 1.48818874e+00 -5.34967899e-01 3.37436974e-01 -1.07237577e+00 -9.55492079e-01 1.97576299e-01 -5.22271618e-02 5.89159548e-01 -4.00549710e-01 -8.01830739e-02 -1.15889251e+00 8.97242799e-02 -1.15786684e+00 7.15582371e-02 -1.08920598e+00 -6.54336751e-01 4.48877573e-01 -3.53966206e-01 -1.30043638e+00 3.44276786e-01 -4.34024841e-01 -2.54949033e-01 8.14918041e-01 -1.59081757e+00 -1.44242215e+00 -3.61521572e-01 7.84959495e-01 3.26274991e-01 -1.29105523e-01 8.69163513e-01 -9.79106799e-02 -3.90933186e-01 7.25096881e-01 3.29430461e-01 3.86440724e-01 7.88471699e-01 -7.45098829e-01 7.07042217e-01 1.76922774e+00 -9.02220309e-02 3.34982902e-01 9.27848637e-01 -1.08923483e+00 -1.71115553e+00 -1.23680675e+00 4.17004317e-01 1.51875749e-01 1.99841917e-01 -5.07174611e-01 -5.98239601e-01 5.36709189e-01 6.93437040e-01 -2.46665627e-01 3.46398711e-01 -1.36970401e+00 -8.21004629e-01 2.18341611e-02 -1.73918378e+00 5.74918926e-01 4.27517861e-01 -3.72054666e-01 -2.04793829e-02 3.73169035e-01 9.92359340e-01 -3.47023934e-01 -6.28838956e-01 3.98661047e-01 5.01314759e-01 -1.03145790e+00 1.19962430e+00 1.80774763e-01 2.12325439e-01 -5.25183737e-01 -5.70240915e-01 -7.39799976e-01 2.24701539e-01 -1.23816752e+00 3.28518033e-01 1.35811460e+00 -5.27548045e-02 -3.92384410e-01 6.85516834e-01 -1.67226747e-01 4.81256872e-01 2.86058962e-01 -4.19549257e-01 -6.29749894e-01 -1.29718378e-01 -1.23840593e-01 7.07644641e-01 8.59984159e-01 -4.11629677e-01 -7.31571019e-01 -1.10712266e+00 1.19209242e+00 1.07960474e+00 -3.58833675e-03 8.40948045e-01 -4.86438453e-01 -2.05532372e-01 4.92589355e-01 -1.44120544e-01 -9.80145335e-01 -3.72768939e-01 -4.49079484e-01 1.44576833e-01 -7.25077868e-01 1.11677647e-02 -1.95184693e-01 -1.92163941e-02 3.10467720e-01 -2.29152620e-01 6.41133130e-01 5.15490949e-01 2.47639388e-01 2.02476412e-01 1.08099123e-02 9.61546481e-01 1.82324219e-02 1.68146670e-01 -3.68561856e-02 -6.87791646e-01 4.03461903e-01 8.93456697e-01 -6.95903420e-01 -3.80515367e-01 -4.97517973e-01 -5.64752072e-02 4.56571966e-01 7.45764673e-01 -1.11173081e+00 1.02672122e-01 -5.50574623e-02 5.21943510e-01 -8.37720633e-01 1.71626166e-01 -1.24644899e+00 5.57072349e-02 7.40982831e-01 -2.71019101e-01 3.62436593e-01 2.30731770e-01 8.38008523e-01 -3.95939797e-02 -3.54832351e-01 9.67182100e-01 3.09388153e-02 -4.07329112e-01 5.85358590e-02 -5.54735661e-01 -3.94258380e-01 1.32187414e+00 -3.83156359e-01 -8.35271060e-01 -4.69685525e-01 -2.19110146e-01 -5.04938466e-03 7.52853990e-01 2.61296004e-01 7.98256695e-01 -6.79291844e-01 -6.83965743e-01 6.19374752e-01 -8.48829281e-03 -4.91613925e-01 3.46423954e-01 2.26280093e-01 -1.13374674e+00 7.86109418e-02 -2.00386882e-01 -3.30131382e-01 -1.76528168e+00 1.04895473e+00 -4.57904376e-02 -1.72220767e-01 -5.48841715e-01 4.25681621e-01 2.73426443e-01 9.50149074e-03 2.38140389e-01 2.87555039e-01 1.03400633e-01 -3.05979550e-01 7.63024807e-01 2.12318957e-01 -1.60313115e-01 -8.50103319e-01 7.10384129e-03 5.56535780e-01 -3.04094076e-01 -4.23424244e-02 1.03535187e+00 -6.99195266e-01 -8.23027641e-02 -7.91636348e-01 1.10915685e+00 2.61331916e-01 -1.12181354e+00 4.80733216e-02 -3.59675914e-01 -8.20319057e-01 -1.43885493e-01 -8.14455092e-01 -1.11795390e+00 7.56230772e-01 9.78606999e-01 3.05811703e-01 1.52685475e+00 -9.05837834e-01 1.07014012e+00 1.05271377e-01 6.24095500e-01 -7.63231337e-01 4.15082164e-02 -2.33045653e-01 7.85792708e-01 -7.99976289e-01 2.38970950e-01 -9.74335015e-01 -6.96377516e-01 1.13884330e+00 3.54014859e-02 -3.82361561e-01 6.43513322e-01 7.78429747e-01 3.16228181e-01 3.08085591e-01 1.66909990e-03 3.31895471e-01 -4.49905306e-01 1.01605535e+00 -3.52284312e-01 -5.86952418e-02 -6.00778684e-02 1.08418234e-01 -1.44492939e-01 9.88489166e-02 9.25338566e-01 1.19189131e+00 -5.32848001e-01 -1.14721715e+00 -1.15933979e+00 -2.17973381e-01 -8.75489056e-01 -1.21558994e-01 -1.55907989e-01 5.90776801e-01 1.99051633e-01 1.11627638e+00 -4.67828363e-01 -3.71118367e-01 -9.91914347e-02 -2.63616532e-01 1.53745234e-01 5.76293841e-02 -7.49641061e-01 3.49244148e-01 -2.79854268e-01 -4.27578747e-01 -1.73813939e-01 -3.91563922e-01 -7.61305571e-01 -4.70415801e-01 -5.87775707e-01 -1.76641479e-01 7.99813211e-01 2.07573354e-01 2.51538783e-01 5.59389293e-02 1.30505741e+00 -5.68010151e-01 -5.23548067e-01 -2.52906680e-01 -8.80265057e-01 2.82018781e-01 4.39337432e-01 2.10126728e-01 -3.12566847e-01 6.04648769e-01]	[4.451807022094727, 8.006694793701172]
385998e2-adc1-4161-ad74-39b554845f34	unconstrained-face-sketch-synthesis-via	2112.01019	null	https://arxiv.org/abs/2112.01019v1	https://arxiv.org/pdf/2112.01019v1.pdf	Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark	Face sketch generation has attracted much attention in the field of visual computing. However, existing methods either are limited to constrained conditions or heavily rely on various preprocessing steps to deal with in-the-wild cases. In this paper, we argue that accurately perceiving facial region and facial components is crucial for unconstrained sketch synthesis. To this end, we propose a novel Perception-Adaptive Network (PANet), which can generate high-quality face sketches under unconstrained conditions in an end-to-end scheme. Specifically, our PANet is composed of i) a Fully Convolutional Encoder for hierarchical feature extraction, ii) a Face-Adaptive Perceiving Decoder for extracting potential facial region and handling face variations, and iii) a Component-Adaptive Perceiving Module for facial component aware feature representation learning. To facilitate further researches of unconstrained face sketch synthesis, we introduce a new benchmark termed WildSketch, which contains 800 pairs of face photo-sketch with large variations in pose, expression, ethnic origin, background, and illumination. Extensive experiments demonstrate that the proposed method is capable of achieving state-of-the-art performance under both constrained and unconstrained conditions. Our source codes and the WildSketch benchmark are resealed on the project page http://lingboliu.com/unconstrained_face_sketch.html.	['Wenxiong Kang', 'Zhengtao Wu', 'Lingbo Liu', 'Lin Nie']	2021-12-02	null	null	null	null	['face-sketch-synthesis']	['computer-vision']	[ 2.10849747e-01 -2.09446818e-01 -9.33019519e-02 -6.75143003e-01 -4.85968083e-01 -5.37330925e-01 6.50216222e-01 -9.36205089e-01 1.59374133e-01 4.35779423e-01 2.57279165e-02 8.67593586e-02 2.32313365e-01 -6.02217793e-01 -6.42391503e-01 -5.93383372e-01 3.60481620e-01 1.00641266e-01 -3.14618677e-01 -1.68902591e-01 2.02030689e-01 8.45732033e-01 -1.77162170e+00 3.93726319e-01 4.17217940e-01 1.30695581e+00 -6.25817701e-02 5.83011329e-01 -1.71070948e-01 4.05082732e-01 -4.55083102e-01 -8.03776979e-01 4.00142580e-01 -6.03841245e-01 -1.68678507e-01 4.96939451e-01 9.31503773e-01 -5.83649158e-01 -4.72937346e-01 9.47540998e-01 8.82201374e-01 -2.35154182e-01 6.56675756e-01 -1.45901155e+00 -9.06282425e-01 1.00391485e-01 -5.31537175e-01 -4.78065968e-01 3.52480531e-01 4.08456147e-01 6.58758640e-01 -1.65832520e+00 5.49883664e-01 1.56094313e+00 3.93906295e-01 1.01436198e+00 -8.32892954e-01 -1.12145019e+00 1.16954014e-01 -4.89346348e-02 -1.65183461e+00 -1.16847551e+00 1.25743008e+00 -1.99598372e-01 4.11036700e-01 1.77885041e-01 3.64200145e-01 1.24567151e+00 -6.35998622e-02 6.94723129e-01 8.68143737e-01 -2.15586737e-01 8.11599791e-02 1.10435411e-02 -5.22951782e-01 1.04183948e+00 5.41903451e-03 6.14610948e-02 -6.85651720e-01 -8.62908214e-02 1.16093445e+00 4.06289622e-02 -2.41168648e-01 -2.30441287e-01 -9.76128638e-01 4.69895154e-01 2.60168940e-01 2.95970012e-02 -2.83066243e-01 2.47727811e-01 2.09743738e-01 3.28301251e-01 4.04855847e-01 -8.15526545e-02 -2.82649696e-01 2.45049298e-01 -1.03898251e+00 3.64054650e-01 7.00692952e-01 1.21625602e+00 5.84261239e-01 4.02424425e-01 -3.05209637e-01 1.21520162e+00 3.82392764e-01 7.16019809e-01 1.60141513e-01 -1.13337255e+00 2.83106089e-01 4.63416427e-01 -1.95622724e-02 -1.04718733e+00 5.14088385e-02 -2.80033029e-03 -9.69032109e-01 3.56018752e-01 1.08756118e-01 -1.79888144e-01 -9.65964317e-01 1.81808853e+00 2.21816838e-01 2.55140215e-01 -1.72211006e-01 9.19020295e-01 1.12663543e+00 6.11768842e-01 -1.93546470e-02 -2.17319161e-01 1.41717303e+00 -9.27918851e-01 -8.51927817e-01 -7.44185522e-02 -2.97461629e-01 -9.93081629e-01 1.15837300e+00 3.44663024e-01 -1.30154431e+00 -9.17426348e-01 -1.01681185e+00 -2.25315824e-01 -1.86723515e-01 7.00286865e-01 4.27990407e-01 7.31250763e-01 -1.13658273e+00 3.12544972e-01 -2.78051943e-01 -2.19447821e-01 8.55272830e-01 3.87130052e-01 -5.31424284e-01 -2.45432019e-01 -6.97030187e-01 3.63906115e-01 -3.46442834e-02 3.04754764e-01 -9.54222918e-01 -4.99900788e-01 -8.02616417e-01 1.99221849e-01 4.37764078e-01 -7.85358071e-01 1.03805768e+00 -1.41944718e+00 -1.95706010e+00 8.52424443e-01 -3.51103395e-01 4.50115651e-01 4.82005268e-01 -4.43815365e-02 -5.33665657e-01 1.03792042e-01 -2.40649968e-01 8.45123470e-01 1.53582287e+00 -1.43395150e+00 -1.03871018e-01 -4.56178665e-01 -2.97108442e-01 9.74342674e-02 -5.03826141e-01 2.27694884e-01 -1.01138532e+00 -9.96145308e-01 -2.48394623e-01 -7.37242937e-01 2.20081687e-01 8.44323993e-01 -2.56998301e-01 -2.70926088e-01 8.83119702e-01 -6.48086846e-01 9.71884191e-01 -2.17496705e+00 1.77994266e-01 1.67445838e-01 1.97774991e-01 5.34407258e-01 -5.46274304e-01 3.91601384e-01 -4.87734452e-02 -2.34733038e-02 -2.38391161e-01 -6.04975462e-01 1.22024722e-01 9.09136832e-02 -3.34317386e-01 3.36051852e-01 6.28811359e-01 9.00180638e-01 -5.58272064e-01 -6.77992940e-01 1.44177556e-01 7.63909638e-01 -6.58762753e-01 5.56707323e-01 -2.44622678e-01 2.17238694e-01 -3.56572986e-01 1.32355988e+00 1.11174846e+00 1.00918114e-01 1.91258147e-01 -3.02478224e-01 5.92057705e-02 -4.78126943e-01 -1.16229594e+00 1.84057164e+00 -4.30796683e-01 4.99937236e-01 4.75917041e-01 -3.96782428e-01 1.21391106e+00 4.18796897e-01 1.38779551e-01 -5.75725019e-01 1.49650887e-01 3.59489799e-01 -3.06564271e-01 -4.31301117e-01 2.69126594e-01 -2.83726037e-01 2.79946387e-01 1.13186181e-01 2.57559687e-01 -2.00487062e-01 -9.37244520e-02 -1.57793060e-01 7.10888445e-01 2.79123873e-01 1.56260580e-01 -1.40257329e-01 8.84391308e-01 -8.53037775e-01 5.91242790e-01 8.68748948e-02 -1.65566981e-01 8.37676048e-01 5.67636549e-01 -4.60390598e-01 -9.92321670e-01 -1.27393627e+00 -3.50153707e-02 1.07127666e+00 -2.06987839e-02 -3.46662581e-01 -7.49359787e-01 -5.75533509e-01 8.10604915e-02 2.79449850e-01 -5.45954108e-01 -6.41010236e-03 -5.58308065e-01 -1.15012378e-01 7.15612888e-01 5.20604372e-01 7.21631825e-01 -1.31883609e+00 -1.39682785e-01 -1.55304164e-01 1.58686548e-01 -1.00155771e+00 -9.07168269e-01 -6.80676639e-01 -4.94271725e-01 -9.52546179e-01 -1.04141986e+00 -9.62604880e-01 9.95810151e-01 1.59005150e-01 1.05306315e+00 4.50148463e-01 -3.48282307e-01 3.21204424e-01 -8.73634368e-02 -4.04613554e-01 -1.32435858e-01 -2.03603998e-01 -3.43470573e-02 5.14117777e-01 -8.41590110e-03 -5.20459116e-01 -8.07009637e-01 4.51204062e-01 -9.52057540e-01 8.98836106e-02 7.12898314e-01 9.08923686e-01 4.51268971e-01 -2.47515053e-01 7.14616954e-01 -6.51614785e-01 6.45536184e-01 -3.33533883e-01 -5.67886770e-01 4.43810850e-01 -2.33298182e-01 -1.62385747e-01 8.23537469e-01 -3.73040825e-01 -1.29948318e+00 3.15773845e-01 -3.97388160e-01 -7.72997618e-01 -2.26716772e-01 -1.28937647e-01 -7.69537210e-01 -2.71170110e-01 2.61073530e-01 3.93642187e-01 1.21365048e-01 -4.25068557e-01 4.81280833e-01 8.71850073e-01 6.86012030e-01 -8.93351793e-01 9.77381110e-01 4.34539199e-01 -4.73384652e-03 -1.01679575e+00 -3.54973197e-01 9.08588469e-02 -6.53308213e-01 -4.82204944e-01 5.50134182e-01 -9.91596580e-01 -8.79884183e-01 7.21781552e-01 -1.20590830e+00 -1.33286119e-01 1.06638178e-01 -6.19047768e-02 -6.11092329e-01 2.47444034e-01 -3.87265027e-01 -9.18109238e-01 -5.20129919e-01 -1.20114493e+00 1.52223933e+00 3.99585843e-01 2.00245470e-01 -5.15680909e-01 -1.81612015e-01 2.44125649e-01 5.80573499e-01 2.60820419e-01 6.76096857e-01 7.08503872e-02 -6.90204799e-01 -4.55757938e-02 -5.75950384e-01 4.48755145e-01 3.03424358e-01 3.10495883e-01 -1.30124438e+00 -3.45532745e-01 -3.43284339e-01 -5.42514026e-01 6.55710340e-01 -3.81875001e-02 1.59473705e+00 -5.23998439e-01 -8.60894285e-03 9.38401759e-01 1.39279819e+00 2.11040065e-01 7.63776362e-01 -6.02447927e-01 7.61266232e-01 6.91192508e-01 3.45902890e-01 7.29471982e-01 2.41161555e-01 7.61847317e-01 3.14967424e-01 -1.19550802e-01 -3.35781366e-01 -4.28827077e-01 4.29443926e-01 7.16141999e-01 -1.83364242e-01 -3.87800783e-01 -4.10743475e-01 3.11989129e-01 -1.44630182e+00 -9.53211665e-01 4.88334179e-01 1.89913499e+00 8.50440919e-01 -4.11985010e-01 7.27690235e-02 -1.44128427e-02 6.27315223e-01 3.05175573e-01 -6.45609021e-01 -4.40200061e-01 -5.72216362e-02 5.34239233e-01 -9.98601913e-02 3.44258517e-01 -7.47324884e-01 1.13019848e+00 5.40838575e+00 9.70751584e-01 -1.19556487e+00 -2.27139875e-01 8.13281655e-01 -8.92562270e-02 -3.31988871e-01 -3.20212811e-01 -6.22842371e-01 5.16611934e-01 4.22265768e-01 1.29292682e-01 7.72327602e-01 8.22943270e-01 -8.60766396e-02 4.14379299e-01 -1.13230109e+00 1.37938237e+00 4.84723717e-01 -1.22531760e+00 4.08101678e-01 -1.76822171e-01 5.81912458e-01 -6.36312366e-01 2.90629268e-01 1.70502484e-01 -3.96273732e-01 -1.34014940e+00 7.26695001e-01 9.24451172e-01 1.59857988e+00 -8.58066618e-01 2.94667989e-01 7.34548178e-03 -1.44297993e+00 1.58108454e-02 -4.15434867e-01 2.29204953e-01 -1.75139129e-01 2.05224782e-01 -3.71025503e-01 4.45804417e-01 3.97908151e-01 6.41047537e-01 -4.42783177e-01 6.43299460e-01 -1.80851430e-01 3.73593837e-01 -7.93165416e-02 8.33691061e-02 -1.70966476e-01 -7.13683888e-02 1.82680190e-01 1.12122631e+00 5.08142710e-01 3.51433724e-01 -9.34210792e-02 1.07444799e+00 -5.43377459e-01 1.05916508e-01 -6.93529844e-01 -2.41204649e-01 6.63315773e-01 1.41115928e+00 -5.00388622e-01 -2.89114147e-01 -4.63736504e-01 1.26934612e+00 2.19342470e-01 3.64302337e-01 -7.60286689e-01 -5.26242375e-01 9.34127808e-01 3.23347598e-02 3.87200177e-01 -1.38973936e-01 -1.07178584e-01 -1.19480181e+00 1.16969585e-01 -1.09826803e+00 -3.82606350e-02 -8.74338448e-01 -1.31990921e+00 7.79001653e-01 -2.14347348e-01 -1.05057776e+00 -9.45691317e-02 -9.61527765e-01 -8.52907598e-01 9.78145421e-01 -1.54130256e+00 -1.52343750e+00 -6.48964047e-01 9.08084512e-01 8.99259627e-01 -5.24755716e-01 7.00440228e-01 5.36420465e-01 -7.18368113e-01 1.03048170e+00 -3.73259008e-01 2.23624125e-01 9.17952955e-01 -7.45383382e-01 5.01523137e-01 5.72996438e-01 5.07743172e-02 6.89290881e-01 2.06636742e-01 -4.42607135e-01 -1.84747910e+00 -1.06924820e+00 7.66475737e-01 -2.56851435e-01 3.95805240e-02 -7.02719033e-01 -6.61762953e-01 4.28610593e-01 3.34473699e-01 3.66492271e-01 4.93797779e-01 -4.49646026e-01 -5.13956249e-01 -3.68784904e-01 -1.32425213e+00 8.70652199e-01 1.32632411e+00 -6.52223289e-01 -7.02184662e-02 5.92517443e-02 3.56430709e-01 -3.17638487e-01 -7.60197878e-01 3.78788531e-01 1.09005857e+00 -1.00330138e+00 1.05769706e+00 -3.73437613e-01 6.01203263e-01 -2.75786012e-01 -2.57753581e-01 -1.00191224e+00 -1.75691187e-01 -7.92388856e-01 -1.85186900e-02 1.55174589e+00 -4.27687131e-02 -3.67057890e-01 8.03707600e-01 4.36389208e-01 -3.59555446e-02 -9.61096585e-01 -6.97230697e-01 -4.60716099e-01 -1.08025424e-01 -1.92293003e-01 9.78733242e-01 7.62205005e-01 -5.46617329e-01 2.17571303e-01 -6.89055681e-01 -6.86863139e-02 6.54501498e-01 2.08549157e-01 1.00217092e+00 -1.02135575e+00 -6.46177530e-02 -5.07069886e-01 -1.48699701e-01 -9.02242243e-01 4.53163743e-01 -6.86562955e-01 2.16270816e-02 -1.12042379e+00 8.69159922e-02 -2.75190562e-01 3.14443447e-02 5.00568330e-01 -1.58212736e-01 4.93358701e-01 3.93345863e-01 -1.49979610e-02 -2.19742015e-01 8.88729453e-01 1.52909315e+00 -3.74868736e-02 2.47319996e-01 -1.00397602e-01 -6.87120020e-01 6.89574122e-01 7.33379781e-01 -9.51441899e-02 -5.32306850e-01 -4.24137294e-01 -1.04200192e-01 2.74862349e-01 4.61818606e-01 -8.60125244e-01 4.94931452e-02 -3.29534262e-01 8.55078101e-01 -4.19253975e-01 7.13844657e-01 -8.64731133e-01 5.38819246e-02 1.82913452e-01 -2.96028316e-01 1.29574582e-01 2.14141667e-01 2.46415094e-01 -2.29739770e-01 6.76231831e-02 9.11049187e-01 -1.39420152e-01 -6.61084592e-01 7.86367595e-01 7.95019642e-02 -1.03640646e-01 8.42603207e-01 -1.68768182e-01 -3.27485234e-01 -4.33786124e-01 -2.40377367e-01 1.85705498e-02 4.78471607e-01 5.20765424e-01 1.17161739e+00 -1.67350495e+00 -9.54675496e-01 8.61107290e-01 1.58917397e-01 -3.11107904e-01 2.71336734e-01 1.97614864e-01 -5.99646747e-01 1.53350756e-01 -6.24115109e-01 -1.23085879e-01 -1.39487112e+00 5.18745542e-01 2.84405649e-01 4.54908401e-01 -1.74425215e-01 1.04545188e+00 3.93021226e-01 -4.66979861e-01 3.75216007e-01 -5.06258756e-02 1.16035432e-01 -6.89074919e-02 5.80172300e-01 2.50985086e-01 -2.54597068e-01 -8.43301356e-01 -3.26342344e-01 8.77926469e-01 2.30607390e-01 -1.42375929e-02 1.01428545e+00 1.44357786e-01 -1.64401546e-01 -2.03702152e-02 1.30264640e+00 1.69771865e-01 -1.44441819e+00 -8.31064656e-02 -4.07598734e-01 -8.42020154e-01 -2.43725210e-01 -7.45399475e-01 -1.53217673e+00 1.01872075e+00 5.65172791e-01 -4.92743909e-01 1.50475562e+00 -2.75543332e-01 8.21257770e-01 2.98498660e-01 2.43920937e-01 -7.85576046e-01 2.97625989e-01 2.10509211e-01 1.52283370e+00 -1.16655660e+00 -8.68347958e-02 -4.48308259e-01 -6.75073504e-01 1.34236634e+00 8.23164701e-01 -1.39721304e-01 7.96692789e-01 3.32993984e-01 1.43962532e-01 -1.46596223e-01 -8.49515140e-01 3.63075808e-02 5.15422285e-01 4.99503046e-01 5.58371842e-01 6.78205863e-03 -3.81813087e-02 6.13390267e-01 -8.75285566e-02 2.81525970e-01 -5.61224036e-02 6.32633209e-01 -1.45991772e-01 -1.19693756e+00 -3.89971703e-01 2.55789876e-01 -3.01623613e-01 -1.56991296e-02 -7.15389967e-01 5.75065970e-01 4.50561166e-01 7.19476581e-01 -2.47731283e-02 -3.99634600e-01 3.21569830e-01 1.45282149e-01 7.33168721e-01 -4.18888301e-01 -4.23397064e-01 6.98217154e-02 3.40284663e-03 -6.54283166e-01 -2.10952669e-01 -4.24038142e-01 -8.44268084e-01 -4.02437419e-01 -3.66394445e-02 -3.49080175e-01 5.29515743e-01 4.80158418e-01 4.76798683e-01 3.09398860e-01 8.78173947e-01 -1.23575127e+00 -3.87384146e-01 -8.94455612e-01 -5.32694817e-01 2.40774661e-01 2.96466678e-01 -6.53611064e-01 -7.79070333e-02 2.30723158e-01]	[12.567315101623535, -0.08340821415185928]
afa0c052-48b0-4253-be28-631b3415453d	an-approach-for-adaptive-automatic-threat	1903.10604	null	https://arxiv.org/abs/1903.10604v2	https://arxiv.org/pdf/1903.10604v2.pdf	An Approach for Adaptive Automatic Threat Recognition Within 3D Computed Tomography Images for Baggage Security Screening	The screening of baggage using X-ray scanners is now routine in aviation security with automatic threat detection approaches, based on 3D X-ray computed tomography (CT) images, known as Automatic Threat Recognition (ATR) within the aviation security industry. These current strategies use pre-defined threat material signatures in contrast to adaptability towards new and emerging threat signatures. To address this issue, the concept of adaptive automatic threat recognition (AATR) was proposed in previous work. In this paper, we present a solution to AATR based on such X-ray CT baggage scan imagery. This aims to address the issues of rapidly evolving threat signatures within the screening requirements. Ideally, the detection algorithms deployed within the security scanners should be readily adaptable to different situations with varying requirements of threat characteristics (e.g., threat material, physical properties of objects). We tackle this issue using a novel adaptive machine learning methodology with our solution consisting of a multi-scale 3D CT image segmentation algorithm, a multi-class support vector machine (SVM) classifier for object material recognition and a strategy to enable the adaptability of our approach. Experiments are conducted on both open and sequestered 3D CT baggage image datasets specifically collected for the AATR study. Our proposed approach performs well on both recognition and adaptation. Overall our approach can achieve the probability of detection around 90% with a probability of false alarm below 20%. Our AATR shows the capabilities of adapting to varying types of materials, even the unknown materials which are not available in the training data, adapting to varying required probability of detection and adapting to varying scales of the threat object.	['Toby P. Breckon', 'Qian Wang', 'Khalid N. Ismail']	2019-03-25	null	null	null	null	['material-recognition']	['computer-vision']	[ 7.11811543e-01 -3.82724345e-01 4.73327011e-01 -7.82013591e-03 -5.85988939e-01 -7.80339420e-01 5.37511349e-01 3.99773687e-01 -6.15632772e-01 3.06751817e-01 -4.60195929e-01 -5.77513397e-01 -8.17515671e-01 -9.02155340e-01 -3.46402496e-01 -6.43174946e-01 -3.91874313e-01 9.31933403e-01 7.23387599e-01 -5.66476405e-01 3.61862183e-01 1.20317268e+00 -1.64521325e+00 3.47369909e-01 4.17772770e-01 1.24130309e+00 7.28611797e-02 1.01605380e+00 1.89832121e-01 -2.79919687e-03 -6.34303927e-01 2.48742387e-01 9.59958375e-01 -1.80845574e-01 -7.39302516e-01 2.20699966e-01 2.97967374e-01 -1.67285353e-01 2.37647712e-01 7.84858763e-01 3.18927795e-01 2.62282103e-01 9.09817994e-01 -9.15983617e-01 3.86815041e-01 -1.21040195e-01 -4.43481386e-01 8.06091428e-01 3.67303640e-01 4.40398633e-01 2.74212420e-01 -4.25750285e-01 2.44831085e-01 8.68364155e-01 5.70966184e-01 6.31659985e-01 -8.72999012e-01 -7.31097639e-01 4.21294235e-02 -2.72995923e-02 -1.22252417e+00 3.97089094e-01 5.58669865e-01 -9.08108473e-01 9.15606081e-01 7.67592013e-01 5.15556693e-01 8.47414136e-01 4.55655962e-01 2.88517028e-02 1.59610772e+00 -3.24650109e-01 5.50765455e-01 2.66215742e-01 7.55293518e-02 5.57521403e-01 3.33706260e-01 6.01943910e-01 -1.31644219e-01 -5.04601657e-01 6.10588312e-01 -1.25064347e-02 -9.90880057e-02 -9.63382125e-02 -5.08506238e-01 6.22165620e-01 2.24993125e-01 5.90074778e-01 -5.06313145e-01 -2.72634596e-01 6.79342449e-01 1.92350119e-01 3.47406209e-01 5.91816604e-01 -7.31196344e-01 9.26541612e-02 -6.43602371e-01 2.05887184e-01 5.02170146e-01 3.98979783e-01 2.08379298e-01 3.44690800e-01 2.40382895e-01 4.97319520e-01 2.47705609e-01 4.23524946e-01 6.33250535e-01 2.10396469e-01 3.46359968e-01 6.78299248e-01 -2.78219610e-01 -8.35383058e-01 -5.85748792e-01 -5.12932897e-01 -3.87764931e-01 7.62070954e-01 1.95894346e-01 -1.29220292e-01 -1.40901649e+00 1.11999238e+00 8.23036611e-01 1.51075721e-01 1.17089212e-01 8.41295183e-01 2.78438121e-01 5.74215829e-01 4.23735738e-01 -8.22785422e-02 1.40523171e+00 7.69835385e-03 -2.93734968e-02 -1.57206193e-01 4.61567402e-01 -5.53844333e-01 7.12973714e-01 7.25005627e-01 -5.13672173e-01 -6.07700408e-01 -1.17538011e+00 1.27987218e+00 -7.68943548e-01 -4.14958060e-01 2.65741616e-01 1.36796010e+00 -4.57713872e-01 5.17828345e-01 -7.44609714e-01 -4.67877418e-01 1.61463678e-01 7.74822474e-01 -1.62115499e-01 2.72460461e-01 -1.12870228e+00 1.06008089e+00 8.62844884e-01 6.36767074e-02 -1.17934287e+00 -5.83883226e-01 -6.14567459e-01 -3.26122433e-01 6.75016642e-01 -2.53679574e-01 7.54189730e-01 -9.06757295e-01 -1.23287141e+00 8.31102550e-01 9.05168295e-01 -4.67959821e-01 6.28886223e-01 -1.85332105e-01 -6.12712979e-01 4.75522071e-01 -2.71964818e-01 -2.31586136e-02 9.26083505e-01 -1.46637619e+00 -5.41679084e-01 -5.14563918e-01 1.18980603e-02 1.61036789e-01 -1.77465707e-01 4.64732826e-01 5.76628745e-01 -5.04447877e-01 2.65425324e-01 -9.34462845e-01 -3.65117639e-01 -4.98283327e-01 -5.76584749e-02 2.87169397e-01 1.19645023e+00 -7.09924638e-01 8.10666919e-01 -1.87700498e+00 7.93414097e-03 6.81852758e-01 -2.52505690e-01 5.18498659e-01 3.51315975e-01 4.08100367e-01 -4.23094958e-01 -1.43696249e-01 -8.97536397e-01 6.84234917e-01 -3.40989441e-01 7.89654925e-02 -4.43778485e-01 5.09173155e-01 3.68358165e-01 1.52445346e-01 -7.67945588e-01 -3.58413607e-01 3.90072942e-01 6.31485358e-02 -9.09598991e-02 1.89493582e-01 -1.42042667e-01 5.53190410e-01 -7.71971166e-01 9.75524187e-01 7.74678469e-01 6.80916429e-01 -5.34625724e-02 7.02594370e-02 -1.23572163e-01 -5.87205470e-01 -1.27786565e+00 8.76412392e-01 -2.70735085e-01 -1.54975772e-01 2.65413702e-01 -1.08014417e+00 1.12006712e+00 3.91971469e-01 8.56189311e-01 -3.24861139e-01 5.49996316e-01 3.53890389e-01 2.02847898e-01 -4.02773142e-01 4.58595961e-01 -8.10211003e-01 -2.34727010e-01 4.08637494e-01 -1.27602309e-01 -5.82073629e-01 -4.26585317e-01 -1.36868313e-01 1.17989290e+00 -1.88879743e-02 1.68844193e-01 -3.72057259e-01 7.59978175e-01 4.68997329e-01 6.61513954e-02 4.40889925e-01 -2.94496268e-01 3.46279651e-01 -2.15685591e-01 -5.78040063e-01 -7.98409283e-01 -1.09364092e+00 -5.42889416e-01 6.09393299e-01 9.25406814e-02 2.70177096e-01 -7.94411838e-01 -8.89892280e-01 -1.02634393e-01 5.21935701e-01 -5.05555034e-01 -4.17872548e-01 -7.80934691e-01 -1.13042879e+00 5.53394973e-01 3.44256073e-01 4.87547368e-01 -9.26368475e-01 -1.47715235e+00 2.52083331e-01 6.09987795e-01 -1.07570732e+00 3.22083980e-01 4.00893986e-01 -1.06331205e+00 -1.19989657e+00 -1.88545361e-01 -1.71149299e-01 6.47510409e-01 -1.50227472e-01 5.83466530e-01 3.64389479e-01 -1.09235191e+00 9.92221832e-01 -6.44160211e-01 -7.12650836e-01 -7.68107355e-01 -2.76653320e-01 3.58741671e-01 1.66104868e-01 8.00906718e-02 -1.41709715e-01 -3.12882215e-01 5.83393395e-01 -1.59318829e+00 -6.79460108e-01 5.64097047e-01 5.61833382e-01 5.04812896e-01 5.86289465e-01 3.19660813e-01 -8.64061832e-01 5.47787130e-01 -5.34987509e-01 -7.38150656e-01 2.29974762e-01 -4.76775587e-01 -4.82237041e-01 6.15007401e-01 -6.06635392e-01 -8.79584610e-01 6.03120029e-02 -2.72032112e-01 -3.55842113e-01 -7.28618205e-01 3.66666198e-01 1.03049446e-02 -6.53755128e-01 1.10543001e+00 1.07473239e-01 -2.86201417e-01 -3.20027947e-01 -2.91191965e-01 6.60862803e-01 3.06709051e-01 -7.61684656e-01 1.30090904e+00 3.02685946e-01 6.14504576e-01 -8.25990498e-01 -3.74582112e-01 -6.64282382e-01 -9.55628157e-01 -7.57914007e-01 8.62812340e-01 -3.67086172e-01 -2.22062573e-01 4.12401348e-01 -4.39344585e-01 -9.55876485e-02 -1.94070533e-01 5.12134016e-01 -4.08432454e-01 6.11462951e-01 -3.37120593e-01 -1.31245637e+00 -4.74981755e-01 -1.03214252e+00 1.04769111e+00 -1.04443923e-01 -1.62412107e-01 -8.02830338e-01 9.20912400e-02 4.16548133e-01 4.51266438e-01 8.91762376e-01 9.04919744e-01 -9.29532468e-01 -4.05957788e-01 -7.06866384e-01 2.32474774e-01 3.76732498e-01 2.18831211e-01 -1.50048599e-01 -8.35209489e-01 -5.05418599e-01 6.95755363e-01 -2.54938185e-01 5.69260478e-01 -5.79660274e-02 1.03682685e+00 5.57641685e-02 -2.13284940e-01 2.77294904e-01 1.79325998e+00 7.71810591e-01 3.53366613e-01 6.96092010e-01 2.75156796e-01 8.25208008e-01 1.37861001e+00 5.37686944e-01 -6.96760833e-01 7.32292056e-01 7.74303317e-01 -9.49072316e-02 3.84898514e-01 3.51359665e-01 1.82904899e-01 7.57699013e-02 -2.93562382e-01 -1.80196445e-02 -1.51273811e+00 1.85017973e-01 -1.17438662e+00 -8.71977210e-01 -1.36803627e-01 2.33666205e+00 3.82312328e-01 5.27505457e-01 1.67862505e-01 5.84676325e-01 5.46983838e-01 -3.71139318e-01 -3.51792693e-01 -7.55757868e-01 1.38226107e-01 6.74738646e-01 8.19504261e-01 3.40510845e-01 -1.19053984e+00 5.42970479e-01 5.81437206e+00 8.17706823e-01 -1.30469632e+00 2.31344327e-01 4.06794578e-01 8.04032292e-03 1.81962937e-01 -1.00648537e-01 -6.61673427e-01 2.07177714e-01 1.01646876e+00 1.18447013e-01 -3.84448394e-02 7.55445302e-01 -9.57890600e-02 -3.76488209e-01 -5.04508495e-01 4.60037053e-01 2.93717325e-01 -5.97737014e-01 3.98972221e-02 1.97751038e-02 1.47917256e-01 -2.29783058e-01 1.17986120e-01 1.02392048e-01 -8.08947459e-02 -7.22885311e-01 7.66433239e-01 2.26449996e-01 7.40700841e-01 -6.89849615e-01 7.62691915e-01 4.52924520e-01 -1.18481147e+00 -4.97522146e-01 4.13779020e-02 2.50960141e-01 3.23651671e-01 -5.68869011e-03 -1.17489588e+00 9.67985392e-01 8.19385111e-01 -2.80062109e-01 -5.07067561e-01 9.02446270e-01 3.20864320e-01 6.26401722e-01 -7.13395894e-01 1.76910713e-01 5.54330885e-01 -1.37462616e-01 9.86403584e-01 1.19051266e+00 2.40574911e-01 4.31796581e-01 5.12189567e-01 3.29467207e-01 9.96957123e-01 2.81539410e-01 -6.66744292e-01 1.47582546e-01 -1.88551113e-01 1.02475357e+00 -1.32855523e+00 -3.07666689e-01 1.66633993e-01 5.80155253e-01 -4.75920081e-01 -1.28650397e-01 -9.41077769e-01 -1.56884044e-01 2.64030814e-01 6.42327309e-01 9.69143957e-02 -4.35382605e-01 -1.45148620e-01 -4.83779043e-01 -9.72540528e-02 -9.16878819e-01 9.70688224e-01 -5.04261494e-01 -1.12206459e+00 1.10148704e+00 9.53888834e-01 -1.59407330e+00 -4.38511036e-02 -1.19803834e+00 -5.48442543e-01 7.34597325e-01 -1.02101135e+00 -1.32527757e+00 -2.92710304e-01 4.82250005e-01 6.83424175e-01 -4.04807895e-01 6.30676150e-01 9.45823491e-02 -3.21528822e-01 9.61837545e-02 -3.11194688e-01 -3.32312107e-01 1.38105467e-01 -9.94123101e-01 -9.99478176e-02 9.49793458e-01 -3.52540582e-01 2.18023464e-01 8.17405820e-01 -1.31287932e+00 -1.24472249e+00 -1.08950019e+00 -2.04746768e-01 -5.83813667e-01 7.24780023e-01 -3.85790646e-01 -1.01242125e+00 3.88973951e-01 -2.35413164e-01 -2.55553782e-01 9.60210025e-01 -2.73833215e-01 1.96553227e-02 1.67729422e-01 -1.83372235e+00 1.78489342e-01 7.32819080e-01 -1.39273122e-01 -6.81392074e-01 6.24460280e-01 1.49724185e-01 -5.98779738e-01 -8.74720037e-01 8.01784694e-01 1.32254615e-01 -6.88049197e-01 1.06182778e+00 -7.48236954e-01 -2.34706074e-01 -3.59410405e-01 -2.07238302e-01 -8.29030454e-01 -1.07331678e-01 -1.35727271e-01 3.16126049e-01 7.03558028e-01 2.41431966e-01 -8.35597575e-01 7.70964682e-01 8.10083628e-01 -3.47141922e-01 -6.33779585e-01 -1.36040461e+00 -1.12725651e+00 -8.85027274e-02 -5.75809121e-01 4.33388352e-01 8.86470795e-01 -3.22970539e-01 -3.21499616e-01 -5.17016696e-03 7.07966208e-01 6.07786417e-01 -1.09505795e-01 4.29881573e-01 -1.24058628e+00 -6.16812766e-01 -1.81079954e-01 -9.77120936e-01 1.22887731e-01 -2.18566120e-01 -7.14533567e-01 -5.33637330e-02 -7.88414419e-01 -1.59659415e-01 -7.72440076e-01 -3.36520374e-01 3.93182069e-01 -3.19668762e-02 2.61956304e-01 9.93265137e-02 -8.15093052e-03 1.88271523e-01 1.06483571e-01 8.20890129e-01 -2.08767325e-01 -2.20938444e-01 2.54679739e-01 -6.04418740e-02 5.66050291e-01 8.71490300e-01 -6.92302465e-01 -3.39675128e-01 -1.30076408e-02 -1.22912697e-01 -8.04594904e-02 4.93018597e-01 -1.48242164e+00 -1.19082972e-01 -4.53898638e-01 3.80596042e-01 -6.02845311e-01 4.99871671e-01 -1.38149011e+00 6.03153169e-01 1.04523051e+00 2.35268742e-01 2.60025084e-01 9.19059157e-01 5.63550591e-01 4.32169177e-02 -6.45488143e-01 1.01851368e+00 -4.96589601e-01 -6.96211934e-01 3.15135717e-01 -7.05802858e-01 -5.69575250e-01 1.78751326e+00 -8.71235192e-01 1.92605436e-01 3.46253365e-01 -6.73912525e-01 -1.89982504e-01 4.24755633e-01 1.70674220e-01 8.84584785e-01 -6.98384464e-01 -5.36872625e-01 2.58044124e-01 1.64249897e-01 -1.47237360e-01 4.43135887e-01 4.94890034e-01 -8.07987690e-01 1.96724027e-01 -6.37807727e-01 -5.66323102e-01 -1.73176908e+00 8.06240082e-01 6.59602165e-01 -2.29422286e-01 -5.11149168e-01 6.62100673e-01 -6.18974939e-02 -2.28747457e-01 -4.46385354e-01 -1.94013089e-01 -4.28971350e-01 -1.88999012e-01 2.55800128e-01 1.07952595e-01 4.54230219e-01 -9.88311291e-01 -3.84729773e-01 1.08093083e+00 -6.90356409e-03 -1.25556543e-01 1.27274740e+00 4.86042947e-01 2.18823925e-01 2.27260515e-01 5.28627157e-01 -1.02523506e-01 -8.22825730e-01 1.94809690e-01 1.09462157e-01 -7.52367198e-01 9.14827213e-02 -1.06822312e+00 -7.12696493e-01 5.84154487e-01 1.13404822e+00 3.56277943e-01 1.50061238e+00 -1.60816565e-01 5.36181211e-01 1.15572110e-01 6.65241241e-01 -9.67958987e-01 5.00859246e-02 1.47935212e-01 8.99529755e-01 -9.93028820e-01 2.98418880e-01 -7.20892310e-01 -6.39032245e-01 1.20597494e+00 7.55457342e-01 -2.69933175e-02 6.24858201e-01 3.80311161e-01 8.24087411e-02 -6.77767336e-01 -4.26208228e-01 -2.29269564e-01 2.54610479e-01 7.52248168e-01 -2.76942134e-01 6.43235371e-02 -1.65551439e-01 2.16558769e-01 7.98968226e-02 -4.34591323e-01 2.93850005e-01 1.57322943e+00 -7.83825338e-01 -1.14437985e+00 -1.03905916e+00 5.64207494e-01 -4.30105060e-01 2.83778131e-01 -6.82012677e-01 8.92311156e-01 3.58334899e-01 6.54232621e-01 -2.29790851e-01 -5.56021273e-01 6.95183933e-01 -1.78043433e-02 4.97203261e-01 -8.85239124e-01 -1.25878847e+00 -1.77231640e-01 -1.11214928e-02 -1.10200182e-01 -1.33344963e-01 -7.71310389e-01 -1.21772301e+00 3.26900423e-01 -5.28147638e-01 1.75803483e-01 1.01480496e+00 8.84019792e-01 -2.05606878e-01 5.19730985e-01 7.61929691e-01 -6.03634059e-01 -7.34365225e-01 -8.50543201e-01 -7.65748560e-01 4.94777113e-01 -1.41697496e-01 -1.02516091e+00 -4.99372393e-01 -1.26351357e-01]	[7.421346664428711, 2.0246164798736572]
cc8d7059-cf18-472d-8dec-6e691744f5cd	all-snow-removed-single-image-desnowing	null	null	http://openaccess.thecvf.com//content/ICCV2021/html/Chen_ALL_Snow_Removed_Single_Image_Desnowing_Algorithm_Using_Hierarchical_Dual-Tree_ICCV_2021_paper.html	http://openaccess.thecvf.com//content/ICCV2021/papers/Chen_ALL_Snow_Removed_Single_Image_Desnowing_Algorithm_Using_Hierarchical_Dual-Tree_ICCV_2021_paper.pdf	ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss	Snow is a highly complicated atmospheric phenomenon that usually contains snowflake, snow streak, and veiling effect (similar to the haze or the mist). In this literature, we propose a single image desnowing algorithm to address the diversity of snow particles in shape and size. First, to better represent the complex snow shape, we apply the dual-tree wavelet transform and propose a complex wavelet loss in the network. Second, we propose a hierarchical decomposition paradigm in our network for better understanding the different sizes of snow particles. Last, we propose a novel feature called the contradict channel (CC) for the snow scenes. We find that the regions containing the snow particles tend to have higher intensity in the CC than that in the snow-free regions. We leverage this discriminative feature to construct the contradict channel loss for improving the performance of snow removal. Moreover, due to the limitation of existing snow datasets, to simulate the snow scenarios comprehensively, we propose a large-scale dataset called Comprehensive Snow Dataset (CSD). Experimental results show that the proposed method can favorably outperform existing methods in three synthetic datasets and real-world datasets. The code and dataset are released in https://github.com/weitingchen83/ICCV2021-Single-Image-Desnowing-HDCWNet.	['Sy-Yen Kuo', 'Jian-Jiun Ding', 'I-Hsiang Chen', 'Cheng-Che Tsai', 'Cheng-Lin Hsieh', 'Hao-Yu Fang', 'Wei-Ting Chen']	2021-01-01	null	null	null	iccv-2021-1	['single-image-desnowing']	['computer-vision']	[ 7.08343238e-02 -5.80700636e-01 2.90128142e-01 -2.45070398e-01 -1.47036761e-01 -2.31545389e-01 7.71729946e-02 -2.44775563e-01 3.21691670e-02 6.76338613e-01 3.00509363e-01 -1.98126212e-01 2.91603982e-01 -9.84939337e-01 -5.39307296e-01 -1.17814577e+00 -6.48573861e-02 -3.26555163e-01 4.40653861e-01 -4.71057475e-01 -1.39312401e-01 1.69475019e-01 -1.83898056e+00 6.10358045e-02 1.37749243e+00 9.94221210e-01 5.13019502e-01 4.11699593e-01 2.50621904e-02 5.78014255e-01 -4.64613408e-01 -1.45102486e-01 6.89161658e-01 -5.22819102e-01 -4.90573160e-02 2.33743593e-01 3.36263776e-01 -5.78335464e-01 -5.28366625e-01 1.25655520e+00 6.17239356e-01 1.38343409e-01 2.73249835e-01 -1.24923193e+00 -1.96684405e-01 4.31839466e-01 -1.03367472e+00 4.06066954e-01 8.97315592e-02 2.85936713e-01 7.85324633e-01 -7.43481874e-01 1.67492062e-01 1.14619756e+00 7.04697430e-01 1.22740455e-01 -5.82946002e-01 -1.14625132e+00 2.42662534e-01 3.30943525e-01 -1.51488578e+00 -1.89267188e-01 6.16996586e-01 -3.48213673e-01 -6.31974116e-02 6.53257191e-01 1.13338435e+00 6.12578273e-01 4.69415188e-02 9.86111879e-01 1.67233551e+00 -1.81334600e-01 -1.12495102e-01 -9.84175056e-02 4.04820859e-01 5.89466929e-01 7.16456771e-01 4.22856599e-01 -6.36951625e-01 -4.82701585e-02 2.72105694e-01 1.80870682e-01 -7.49620020e-01 2.23091394e-01 -7.88667381e-01 7.49477446e-01 6.34468853e-01 -2.18923777e-01 -1.83640629e-01 -1.24924570e-01 2.00779259e-01 2.48355776e-01 7.31537521e-01 -4.10575241e-01 -2.39248663e-01 2.21308336e-01 -1.18676972e+00 5.96049786e-01 6.48164332e-01 9.16021347e-01 1.03031254e+00 2.21957058e-01 1.12217444e-03 5.97293317e-01 6.17379189e-01 1.10229397e+00 1.30336106e-01 -5.60343683e-01 5.60226679e-01 2.69638330e-01 1.87195614e-01 -1.15258682e+00 -3.87739182e-01 -7.37574875e-01 -1.07585776e+00 2.38613546e-01 1.08888000e-01 -2.98080176e-01 -8.74253094e-01 1.10658848e+00 5.25371909e-01 8.92411172e-01 2.69841462e-01 1.39931524e+00 1.25614083e+00 8.41061056e-01 -2.38076523e-01 -3.42788815e-01 1.56499791e+00 -7.94469893e-01 -5.96523285e-01 -2.60798246e-01 2.12433398e-01 -7.89100170e-01 8.49722803e-01 1.82093441e-01 -5.46280622e-01 -4.12522495e-01 -1.22982502e+00 2.64373720e-01 -1.49137929e-01 3.44231576e-02 5.59258878e-01 6.87765181e-01 -5.88168740e-01 2.03886136e-01 -6.06229007e-01 -1.72358051e-01 3.14916760e-01 -3.05730015e-01 3.16711158e-01 -2.72093028e-01 -1.46219528e+00 4.23628569e-01 2.31825143e-01 6.79173648e-01 -8.40049744e-01 -6.84518516e-01 -7.48888493e-01 -1.31507963e-01 1.59271091e-01 -6.02695942e-01 8.33818436e-01 -9.33066249e-01 -1.10649204e+00 5.60314715e-01 -4.02206689e-01 -5.09994507e-01 5.12981713e-01 -2.51047939e-01 -5.70120454e-01 1.58203214e-01 -7.16360519e-03 9.15951580e-02 9.89854813e-01 -1.72194624e+00 -8.51636767e-01 -1.65497229e-01 1.18801132e-01 4.25440460e-01 5.89651465e-02 -3.64584886e-02 -1.54315352e-01 -7.53308415e-01 2.72572905e-01 -1.09082389e+00 -1.24892935e-01 -2.06803475e-02 -5.09178519e-01 4.25294608e-01 8.11001539e-01 -6.67986631e-01 1.24583685e+00 -2.37755895e+00 -3.88754904e-01 2.42434293e-01 5.15098870e-01 2.90428907e-01 1.82695631e-02 2.27998585e-01 2.51231670e-01 -1.53968439e-01 -3.98814738e-01 -1.71024561e-01 -3.48844618e-01 4.78017747e-01 -4.63374346e-01 6.62437499e-01 -2.71278828e-01 5.37817836e-01 -9.41663563e-01 -5.35105526e-01 3.82708311e-02 2.47346163e-01 5.92276752e-02 1.33923277e-01 1.42297760e-01 3.24322283e-01 -5.44219136e-01 9.31768537e-01 1.70092976e+00 2.31909975e-01 -4.75544333e-01 -1.91828951e-01 -2.05489010e-01 -1.64006919e-01 -1.19669557e+00 9.19109225e-01 -2.03683913e-01 6.47371650e-01 3.91184270e-01 -4.11752105e-01 9.99192894e-01 -5.77354152e-03 9.17873252e-03 -4.67006594e-01 3.26035738e-01 3.80457550e-01 -7.09575787e-02 -7.49888480e-01 5.59079766e-01 -4.05962408e-01 4.40831512e-01 1.23110875e-01 -6.74532950e-01 -1.19237661e-01 2.76543479e-02 2.17921585e-01 7.02443302e-01 -2.46534586e-01 -1.47609740e-01 -4.30217415e-01 3.93759102e-01 -8.34760591e-02 9.42183495e-01 6.52998209e-01 -3.80272925e-01 7.25553513e-01 1.04289122e-01 -4.34925914e-01 -6.22525990e-01 -1.02370727e+00 -2.91469783e-01 7.56649435e-01 9.10153985e-01 -1.79374129e-01 -5.32208145e-01 -1.66013658e-01 2.90821165e-01 4.19409513e-01 -5.78829885e-01 2.58154627e-02 -1.41466364e-01 -1.25254655e+00 4.76374298e-01 1.02871560e-01 1.16768646e+00 -8.36263955e-01 -4.00628150e-01 -1.24026604e-01 -4.75485295e-01 -1.22934866e+00 -3.47977787e-01 -2.23963782e-01 -7.97538579e-01 -1.16574299e+00 -5.55976927e-01 -5.95039785e-01 4.77841198e-01 1.17452848e+00 9.10844982e-01 4.93246466e-01 -6.78258538e-02 -1.30588397e-01 -9.49027061e-01 -7.85942972e-01 2.03463864e-02 -2.03328565e-01 -1.31831244e-01 3.35668921e-01 3.35625708e-01 -7.25285172e-01 -8.86862576e-01 4.08912838e-01 -8.35754275e-01 1.61793485e-01 4.40216124e-01 6.82957232e-01 3.90976697e-01 3.37994963e-01 -6.03008345e-02 -6.24785900e-01 4.72682238e-01 -7.59930670e-01 -6.47903442e-01 -3.13604802e-01 -3.33383858e-01 -5.67762673e-01 1.73440024e-01 -7.18649998e-02 -1.06769633e+00 -8.91021043e-02 8.39929804e-02 -2.83497751e-01 -3.27301435e-02 5.89948416e-01 -1.80138111e-01 -4.86182928e-01 2.49525473e-01 7.76982069e-01 6.43362999e-02 -3.70770216e-01 -1.27737403e-01 8.29118907e-01 2.52375960e-01 -3.29336166e-01 1.48092604e+00 9.27910268e-01 1.26318544e-01 -1.23651016e+00 -1.02215123e+00 -5.44032395e-01 -1.02287397e-01 -4.28398222e-01 5.56806207e-01 -1.50321293e+00 -7.25523889e-01 1.01160204e+00 -9.25635576e-01 -1.47708207e-01 8.35512355e-02 5.28580189e-01 1.09312057e-01 6.62003219e-01 -4.65823025e-01 -1.01776910e+00 -5.59153020e-01 -9.64662015e-01 9.65517521e-01 5.56627691e-01 4.94820535e-01 -5.40600717e-01 -1.13077894e-01 2.61367321e-01 4.61571276e-01 3.88291508e-01 1.20768748e-01 7.51755852e-03 -9.54772055e-01 1.03286475e-01 -4.72045600e-01 3.19820106e-01 9.20497179e-02 2.30142593e-01 -1.00801063e+00 -3.23695540e-01 6.80569112e-02 1.50758415e-01 1.36866307e+00 5.05978942e-01 8.36944044e-01 -1.43808387e-02 -1.74654141e-01 1.14926589e+00 1.51535153e+00 -9.88755822e-02 7.91029871e-01 5.81070900e-01 7.20410049e-01 4.90815580e-01 8.51185918e-01 6.33248627e-01 5.97892642e-01 1.33133009e-01 6.83526158e-01 -3.31011355e-01 -7.71152079e-02 -1.34105965e-01 5.00712037e-01 8.57862592e-01 -3.73454839e-01 -3.85792762e-01 -4.86800462e-01 5.05162358e-01 -1.76901698e+00 -9.08659101e-01 -7.65353382e-01 1.97738826e+00 4.45755094e-01 1.50059253e-01 -7.57439807e-02 -3.91259268e-02 8.24058473e-01 6.63850367e-01 -3.92075449e-01 8.47258791e-02 -6.52401328e-01 -8.92305970e-02 1.00948536e+00 5.43510377e-01 -1.07648146e+00 8.19651484e-01 5.56082869e+00 9.21372533e-01 -9.95724380e-01 1.17205806e-01 1.23480283e-01 -6.83599064e-05 -3.51622373e-01 1.05245940e-01 -9.85100508e-01 1.03215706e+00 5.05747139e-01 -2.82435209e-01 2.40277842e-01 2.63898402e-01 8.85203183e-01 -4.75117028e-01 8.36129114e-02 8.96688581e-01 6.43334026e-03 -1.01309097e+00 -4.67006266e-02 -1.75175518e-02 5.00519812e-01 3.80022407e-01 -2.66102940e-01 -1.76352292e-01 4.61187512e-01 -5.60408652e-01 7.17978597e-01 4.62079436e-01 4.33524132e-01 -3.99255157e-01 8.94986868e-01 2.45376751e-01 -1.65776825e+00 7.26284012e-02 -6.15896821e-01 -3.88377845e-01 1.15713008e-01 1.23591948e+00 -1.46601185e-01 7.94703245e-01 1.12251878e+00 1.01711941e+00 -3.14198554e-01 1.56899905e+00 -5.48467875e-01 9.34902668e-01 -6.66260839e-01 2.35503521e-02 2.12935016e-01 -5.44471204e-01 9.25199568e-01 1.13350177e+00 4.94640261e-01 3.87433469e-01 3.45388502e-01 4.03975189e-01 1.82957929e-02 5.73550351e-03 -4.73968685e-01 5.32018721e-01 6.63449347e-01 1.24839699e+00 -4.60829854e-01 -2.59008616e-01 -4.60396200e-01 5.48582494e-01 -5.90971708e-01 4.92035538e-01 -8.08855772e-01 -3.61803174e-01 1.11648917e+00 1.58264607e-01 3.94765109e-01 -2.50889182e-01 -4.30639982e-02 -1.37611473e+00 2.57133245e-01 -8.29236388e-01 1.08251475e-01 -9.38567758e-01 -1.30858231e+00 5.61636269e-01 -1.67543799e-01 -1.77252579e+00 8.49616945e-01 -2.75458068e-01 -1.03239739e+00 1.10531867e+00 -2.36810613e+00 -1.28146291e+00 -1.24747741e+00 6.36679709e-01 2.90343046e-01 2.75562927e-02 2.16225877e-01 3.13482225e-01 -4.52549011e-01 2.45410785e-01 4.93013918e-01 3.52110192e-02 6.47832036e-01 -8.83917153e-01 3.90676111e-01 1.14761055e+00 -3.98533285e-01 8.59011039e-02 1.01963615e+00 -6.90819740e-01 -1.20456314e+00 -1.13774502e+00 3.68500084e-01 3.20175558e-01 7.80884027e-01 -2.77123332e-01 -9.86238718e-01 3.43619645e-01 1.78840920e-01 2.48845086e-01 5.58638155e-01 -2.56956846e-01 -2.20462665e-01 -4.33999598e-01 -9.70595539e-01 3.24954450e-01 9.20550346e-01 -1.28472880e-01 -3.37045580e-01 5.01880407e-01 7.72680759e-01 -5.93803942e-01 -4.40317035e-01 3.62432241e-01 4.88767564e-01 -1.26239192e+00 6.38715625e-01 2.26597069e-03 4.41750258e-01 -8.82196009e-01 -1.89765871e-01 -1.47081113e+00 -2.26740301e-01 -5.98571301e-01 9.78575647e-02 1.15699685e+00 1.74392357e-01 -1.01237071e+00 7.56939113e-01 -1.38700873e-01 -2.30350867e-01 -5.29748082e-01 -8.25582743e-01 -7.88997650e-01 -2.22320423e-01 -1.03580520e-01 8.84957910e-01 7.84532845e-01 -4.90126669e-01 -7.42098391e-02 -7.22500622e-01 8.81590188e-01 9.98921514e-01 6.66502655e-01 8.93859982e-01 -1.41172755e+00 1.37337251e-02 5.99310696e-02 -4.05347288e-01 -1.15474606e+00 -1.28790308e-02 -5.93294322e-01 2.75388539e-01 -1.38738322e+00 2.23982543e-01 -5.05948484e-01 -1.57428622e-01 2.64199764e-01 -5.69634736e-01 1.86025530e-01 2.28178635e-01 5.24992347e-01 -2.47981086e-01 7.89848566e-01 1.40522194e+00 -1.49787739e-01 -4.85146008e-02 3.12939495e-01 -6.17874503e-01 7.38248467e-01 8.82097602e-01 -6.72952294e-01 -5.16937636e-02 -5.27483165e-01 7.58657977e-02 -1.00116022e-01 5.24048209e-01 -1.13791871e+00 1.26719847e-01 -1.50291443e-01 1.09041795e-01 -6.93008721e-01 2.41049021e-01 -8.18758130e-01 -9.45999660e-03 5.51888049e-01 4.49597448e-01 -3.16426218e-01 1.19164996e-01 7.42961884e-01 -4.82447475e-01 -1.78633839e-01 7.89850473e-01 -1.02496348e-01 -8.11891019e-01 5.31737268e-01 -4.01799411e-01 7.49642327e-02 9.09351707e-01 -4.04550195e-01 -6.65578663e-01 -5.00737429e-01 -4.04744059e-01 8.56735885e-01 4.85672444e-01 1.61424622e-01 6.51373088e-01 -8.86179030e-01 -1.25698900e+00 2.85763383e-01 1.97795987e-01 8.07217658e-02 5.15652120e-01 9.50173616e-01 -8.90552640e-01 -4.55686718e-01 -5.54668270e-02 -4.64160770e-01 -1.55255210e+00 -3.97522822e-02 5.14991701e-01 7.75456578e-02 -8.79381299e-01 8.24150801e-01 2.45140672e-01 -3.17974836e-02 -1.77006245e-01 -2.81010717e-01 -1.08301409e-01 2.61158139e-01 5.67717969e-01 2.80582547e-01 -1.82102188e-01 -7.31310129e-01 -6.43419027e-02 7.04385459e-01 1.30447105e-01 5.13537347e-01 1.34447026e+00 -4.55960512e-01 -3.46864641e-01 2.78543860e-01 7.35443592e-01 3.59954536e-01 -1.25523698e+00 -4.75426674e-01 -7.18213320e-01 -9.75893617e-01 3.39565665e-01 -2.56561428e-01 -1.55674434e+00 7.80954838e-01 6.94001079e-01 3.84216219e-01 1.34761155e+00 -4.02576685e-01 1.33581233e+00 4.58797403e-02 3.03959936e-01 -5.90748131e-01 -6.43237710e-01 4.84887749e-01 5.49524486e-01 -1.23731673e+00 4.14966673e-01 -8.60458195e-01 -7.15415657e-01 9.18499887e-01 3.71291876e-01 -1.13859288e-01 9.46954906e-01 4.66591507e-01 4.63049561e-01 -1.76274255e-01 -1.59555450e-01 -8.03443849e-01 -2.51395464e-01 6.11892819e-01 -2.18596876e-01 4.57434386e-01 -2.84712344e-01 4.84210610e-01 -3.51324648e-01 6.18620217e-02 9.17233288e-01 8.77298295e-01 -8.42428982e-01 -7.72841752e-01 -6.72587156e-01 7.73120522e-01 -1.92573935e-01 -4.55632031e-01 1.21705970e-02 4.35137361e-01 3.65198702e-01 1.07478118e+00 -1.07599609e-01 -4.98908162e-01 2.55518377e-01 -5.46186507e-01 3.34090483e-03 -2.69658536e-01 -2.88628429e-01 6.03621453e-02 -1.34265516e-03 -2.63962120e-01 -7.96972334e-01 -6.84778988e-01 -9.60543036e-01 -6.56590104e-01 -5.32452941e-01 3.70012283e-01 2.55950868e-01 8.23638260e-01 2.26472989e-01 3.22156727e-01 8.43898237e-01 -1.04066813e+00 -3.15688029e-02 -8.46566796e-01 -1.41376030e+00 1.76984236e-01 6.88524961e-01 -9.07305896e-01 -9.39207375e-01 -1.11151515e-02]	[10.9191312789917, -3.225064277648926]
a0bf8862-9d6f-41ee-93da-0abc9debca9a	visual-deep-learning-based-explanation-for	2302.08511	null	https://arxiv.org/abs/2302.08511v1	https://arxiv.org/pdf/2302.08511v1.pdf	Visual deep learning-based explanation for neuritic plaques segmentation in Alzheimer's Disease using weakly annotated whole slide histopathological images	Quantifying the distribution and morphology of tau protein structures in brain tissues is key to diagnosing Alzheimer's Disease (AD) and its subtypes. Recently, deep learning (DL) models such as UNet have been successfully used for automatic segmentation of histopathological whole slide images (WSI) of biological tissues. In this study, we propose a DL-based methodology for semantic segmentation of tau lesions (i.e., neuritic plaques) in WSI of postmortem patients with AD. The state of the art in semantic segmentation of neuritic plaques in human WSI is very limited. Our study proposes a baseline able to generate a significant advantage for morphological analysis of these tauopathies for further stratification of AD patients. Essential discussions concerning biomarkers (ALZ50 versus AT8 tau antibodies), the imaging modality (different slide scanner resolutions), and the challenge of weak annotations are addressed within this seminal study. The analysis of the impact of context in plaque segmentation is important to understand the role of the micro-environment for reliable tau protein segmentation. In addition, by integrating visual interpretability, we are able to explain how the network focuses on a region of interest (ROI), giving additional insights to pathologists. Finally, the release of a new expert-annotated database and the code (\url{https://github.com/aramis-lab/miccai2022-stratifiad.git}) will be helpful for the scientific community to accelerate the development of new pipelines for human WSI processing in AD.	['Daniel Racoceanu', 'Lev Stimmer', 'Benoît Delatour', 'Susana Boluda', 'Léa Ingrassia', 'Mehdi Ounissi', 'Anuradha Kar', 'Gabriel Jimenez']	2023-01-13	null	null	null	null	['whole-slide-images', 'morphological-analysis']	['computer-vision', 'natural-language-processing']	[ 1.54907942e-01 -1.77856125e-02 1.79961130e-01 -4.47772890e-01 -8.68337989e-01 -6.92089140e-01 1.44772559e-01 3.89211684e-01 -4.29656833e-01 7.43671477e-01 -1.14921451e-01 -2.97053695e-01 -3.86103764e-02 -5.29668868e-01 -4.48619932e-01 -8.60347867e-01 -4.23771679e-01 9.32845652e-01 6.24983370e-01 -5.83341792e-02 -1.76938161e-01 5.48859417e-01 -1.05102456e+00 8.14183533e-01 9.02677476e-01 6.76089346e-01 5.01024127e-01 5.19432604e-01 -1.44056335e-01 -3.01015563e-02 -5.27852476e-01 -2.79570073e-01 4.72541451e-02 -2.92561084e-01 -8.88584554e-01 -2.23779708e-01 4.31731969e-01 -2.64100403e-01 2.53603250e-01 1.19076943e+00 6.21860385e-01 -4.81292248e-01 7.83579826e-01 -6.82975769e-01 -1.71772450e-01 4.08553451e-01 -3.03367317e-01 9.06270325e-01 -3.84561598e-01 3.53032410e-01 7.72464633e-01 -4.38868493e-01 1.23741388e+00 1.12313700e+00 6.66189969e-01 6.65549278e-01 -1.43818021e+00 -3.25636923e-01 3.45792696e-02 9.58835781e-01 -8.34016442e-01 -2.33832285e-01 3.68636876e-01 -8.89000893e-01 6.93567693e-01 2.92574972e-01 1.05864131e+00 9.86010015e-01 3.18532109e-01 6.44151270e-01 1.54862905e+00 -3.02377373e-01 5.31010926e-01 -3.05802822e-01 8.36815059e-01 4.19271231e-01 5.36328971e-01 -5.34612596e-01 1.38948396e-01 -3.75321448e-01 5.48242867e-01 7.82389101e-03 -3.22257012e-01 1.03616484e-01 -1.10219979e+00 6.81595445e-01 4.60768282e-01 7.09988713e-01 -5.87236583e-02 -9.96897742e-02 7.79487431e-01 1.53458834e-01 6.69195592e-01 -1.02341495e-01 -3.25716764e-01 4.07738954e-01 -1.22220516e+00 4.56436485e-01 7.19405338e-02 1.39252335e-01 4.17192221e-01 -4.95406181e-01 -2.13575293e-03 8.80335808e-01 8.05176198e-01 4.18220520e-01 5.83337903e-01 -9.06554580e-01 1.76503778e-01 1.01073086e+00 -3.10161829e-01 -2.05630764e-01 -8.31596792e-01 -8.00614432e-02 -7.12123036e-01 9.12280619e-01 8.95104051e-01 -2.03710437e-01 -1.02129066e+00 1.30049598e+00 2.99686611e-01 -1.52618319e-01 -3.54209006e-01 1.22546124e+00 4.06923831e-01 1.10007949e-01 4.68639463e-01 9.16479304e-02 1.90496790e+00 -5.14176071e-01 -3.95749331e-01 -3.19067955e-01 8.50682795e-01 -4.29691702e-01 9.45156217e-01 4.77802427e-03 -8.17837715e-01 -5.21280197e-03 -1.04343879e+00 -3.11749965e-01 -6.22352839e-01 3.98249596e-01 3.03665429e-01 7.13758230e-01 -1.59908867e+00 3.68216753e-01 -1.32973611e+00 -8.35196793e-01 9.94822264e-01 5.39813042e-01 -3.78210455e-01 1.87064752e-01 -9.84817803e-01 1.06410766e+00 2.26007923e-01 2.24568933e-01 -6.69987679e-01 -9.42332447e-01 6.09403029e-02 -3.94566059e-01 -3.18519592e-01 -8.01853597e-01 7.87090957e-01 -7.09397435e-01 -7.72149086e-01 1.58541465e+00 -2.53989965e-01 -7.44230032e-01 7.59757698e-01 2.12735571e-02 -1.97473839e-01 8.57840121e-01 1.91530004e-01 7.89645076e-01 3.45702440e-01 -1.00420225e+00 -3.72532219e-01 -1.18398738e+00 -1.26381278e-01 -3.74040306e-01 2.27775544e-01 4.29470003e-01 3.54929030e-01 -4.09911782e-01 -7.03099295e-02 -8.95902097e-01 -2.19511822e-01 5.69709659e-01 -2.76981503e-01 -1.06172785e-01 1.08343935e+00 -1.03829777e+00 4.71261352e-01 -1.97483039e+00 -9.12999287e-02 1.93061545e-01 8.28716934e-01 4.35478002e-01 6.32125735e-02 -2.01816246e-01 -3.32769394e-01 5.26092410e-01 -4.13188845e-01 -1.86556697e-01 2.68153157e-02 -2.88475543e-01 -1.45608690e-02 7.26327002e-01 7.74004012e-02 1.05053794e+00 -4.83844161e-01 -4.94130015e-01 5.70741855e-03 6.89015388e-01 -1.33160561e-01 -3.06614399e-01 -5.34020603e-01 4.49972689e-01 -4.52800155e-01 4.48678672e-01 7.03382075e-01 -3.49139571e-01 6.34014249e-01 -4.25781548e-01 -1.31985158e-01 2.92413048e-02 -4.74347681e-01 1.09928191e+00 3.42656344e-01 6.51649952e-01 4.55113888e-01 -7.62953460e-01 7.25122571e-01 2.77886987e-01 4.66649383e-01 -4.30729598e-01 4.70407158e-01 3.15144181e-01 2.88725972e-01 -2.63008922e-01 -5.71822226e-01 -1.61986098e-01 6.55319810e-01 5.90833068e-01 -5.94454370e-02 5.78566909e-01 6.43253744e-01 3.00658382e-02 1.09806180e+00 -2.84118261e-02 -7.23450854e-02 -5.89118540e-01 3.89412612e-01 2.66224056e-01 1.91607282e-01 2.33697310e-01 -7.36972511e-01 5.72464108e-01 8.95589113e-01 -4.94572818e-01 -1.32325220e+00 -1.10949183e+00 -4.35543656e-01 5.64106107e-01 -3.04110855e-01 -1.64107785e-01 -1.22925234e+00 -6.06768310e-01 -2.94071615e-01 1.61549702e-01 -8.79302561e-01 2.25867078e-01 -8.09140682e-01 -1.69198847e+00 7.05907166e-01 2.87294388e-01 3.85659844e-01 -7.61320412e-01 -9.20551956e-01 -1.59002524e-02 -2.14910582e-01 -8.63155782e-01 1.16084523e-01 2.93983281e-01 -1.19494724e+00 -1.54695344e+00 -1.07652223e+00 -8.44914258e-01 7.57408619e-01 -1.24685103e-02 6.35945618e-01 1.69292390e-01 -5.90205133e-01 1.30177051e-01 -3.72371227e-01 -3.30368102e-01 -4.88443822e-01 -3.36434832e-03 -2.68885553e-01 -3.08581263e-01 4.93552834e-01 -8.15646887e-01 -1.03101051e+00 1.12147652e-01 -8.15393984e-01 -6.50980398e-02 5.38652360e-01 3.90898027e-02 8.58068228e-01 -4.06590283e-01 3.88561189e-01 -8.07626665e-01 5.62970221e-01 -4.01916474e-01 -3.90457243e-01 4.22376007e-01 -4.00208533e-01 -3.31463128e-01 2.01210186e-01 3.88250425e-02 -8.85683894e-01 -3.42677236e-01 -2.01099858e-01 2.29314491e-01 -4.62060988e-01 1.94629103e-01 -2.28158921e-01 -8.19661692e-02 7.30462670e-01 -2.46034428e-01 5.71066618e-01 -5.35683632e-01 9.33707058e-02 4.03377771e-01 6.29616976e-02 -3.67025465e-01 1.03157043e-01 1.00952780e+00 -7.31473556e-04 -7.38820910e-01 -4.27334517e-01 -4.87500668e-01 -9.91594076e-01 -2.70583779e-01 1.30458224e+00 -4.56092536e-01 -4.79928732e-01 6.36814237e-01 -1.03321540e+00 -1.08619118e+00 1.03347242e-01 2.10447341e-01 -3.71804595e-01 6.55157030e-01 -8.62843454e-01 -2.88108647e-01 -9.19032395e-01 -1.42775917e+00 9.12350178e-01 1.54495044e-02 -3.71960819e-01 -1.13409424e+00 3.89118254e-01 6.55604839e-01 9.79882106e-02 4.19430166e-01 1.53832316e+00 -9.01183188e-01 -4.29429948e-01 1.37200594e-01 -5.14513075e-01 9.95841548e-02 -1.65629432e-01 1.18563764e-01 -6.89326823e-01 1.91211596e-01 1.31752752e-02 8.67206901e-02 9.50055242e-01 6.37699187e-01 3.25949669e-01 -3.36806402e-02 -5.61896443e-01 2.46828571e-02 1.43774140e+00 1.58762380e-01 8.28226149e-01 8.37601125e-01 3.29289705e-01 7.27005124e-01 1.93972304e-01 -5.45422621e-02 1.01010405e-01 6.73016071e-01 3.15988004e-01 -6.48312569e-02 -5.68906367e-01 1.02014124e+00 5.11069596e-01 1.81989577e-02 -3.36550295e-01 2.12402448e-01 -1.17847037e+00 5.27101874e-01 -1.50393033e+00 -7.54164577e-01 -8.57689679e-01 1.64738655e+00 9.02178824e-01 1.34176970e-01 5.83897114e-01 -6.00360110e-02 9.47862864e-01 -1.51425868e-01 -4.59399015e-01 8.17161873e-02 -3.70116085e-01 2.71519452e-01 1.96051016e-01 4.75716919e-01 -8.88430655e-01 6.76202536e-01 6.13367176e+00 5.42048872e-01 -1.27941203e+00 6.11222386e-01 8.56864929e-01 -2.23799780e-01 3.55633423e-02 -3.54042262e-01 -8.75413179e-01 6.65112615e-01 1.13520026e+00 2.12825894e-01 2.21577331e-01 5.40820658e-01 7.65837669e-01 -2.70783126e-01 -7.54745126e-01 4.11419690e-01 -2.43461847e-01 -1.49393547e+00 -1.02265403e-01 1.85897246e-01 1.58769056e-01 5.91516495e-01 -2.18144525e-02 -3.23427260e-01 -1.25873059e-01 -5.31490386e-01 7.47768581e-01 7.60428011e-01 7.61332870e-01 -1.71663910e-01 9.94629323e-01 -5.27413666e-01 -7.65606821e-01 1.44575909e-01 -3.68323267e-01 4.59978431e-01 3.59546900e-01 1.13504159e+00 -1.07069945e+00 2.39246897e-02 8.86899889e-01 2.32568502e-01 -1.04029417e+00 1.25303125e+00 -7.15305731e-02 7.96867967e-01 -3.29151392e-01 2.51642436e-01 2.09158603e-02 -3.28741372e-01 6.26183033e-01 1.29123306e+00 1.31518394e-01 -1.14195772e-01 -1.65646285e-01 1.23124897e+00 4.09225613e-01 2.13763461e-01 2.31033981e-01 -1.68652266e-01 -5.99003024e-02 1.55260992e+00 -1.60913444e+00 -2.31304064e-01 1.57503374e-02 5.81722617e-01 3.45222980e-01 2.47042462e-01 -4.90036398e-01 8.70046690e-02 6.56266093e-01 7.00118124e-01 5.64522929e-02 -3.60706627e-01 -7.02586472e-01 -4.94584709e-01 -7.74045438e-02 -5.89185536e-01 5.64729631e-01 -9.13962066e-01 -1.24742663e+00 5.46287775e-01 -2.58005951e-02 -5.59498191e-01 3.24108452e-01 -1.09525907e+00 -8.18224132e-01 7.46549368e-01 -1.19511926e+00 -1.33555734e+00 -1.65390059e-01 2.84285098e-01 4.11426090e-02 1.51025914e-02 7.69105375e-01 2.76364118e-01 -5.86447120e-01 -4.34843712e-02 3.31847101e-01 4.48432751e-02 7.34579504e-01 -1.42953801e+00 2.28560746e-01 4.55891937e-01 -5.63423872e-01 7.00644553e-01 6.16355121e-01 -1.05588281e+00 -3.15685779e-01 -1.29475832e+00 6.20480359e-01 -4.97655541e-01 1.06433344e+00 -3.09067070e-01 -9.17247653e-01 7.92717099e-01 -1.59766689e-01 -3.54800165e-01 9.95452702e-01 -1.78725138e-01 -1.74301967e-01 4.32849973e-02 -1.44976175e+00 7.34894276e-01 6.27020478e-01 -1.87715679e-01 -5.55797040e-01 7.10287988e-01 3.34226012e-01 2.82041840e-02 -1.02304482e+00 4.80413437e-03 4.44433361e-01 -1.23690951e+00 1.03574121e+00 -3.06550920e-01 8.94189849e-02 -3.46575528e-01 2.84611315e-01 -6.95111334e-01 -2.30728716e-01 1.83777690e-01 2.03576148e-01 9.60646093e-01 2.67703623e-01 -6.84094787e-01 8.10315132e-01 5.97826481e-01 -3.35963875e-01 -7.74177730e-01 -1.10532296e+00 -3.77761215e-01 3.60348195e-01 -1.94942787e-01 1.39640823e-01 2.94658214e-01 1.40815331e-02 -1.74593344e-01 7.92798340e-01 -2.22346634e-02 6.66436732e-01 -3.52979749e-01 -8.59245434e-02 -1.62280297e+00 3.22521955e-01 -6.96548343e-01 -7.23136127e-01 3.63688141e-01 2.11331785e-01 -1.36118340e+00 -5.32864571e-01 -1.95691812e+00 3.89455557e-01 -3.76978427e-01 -1.98602602e-01 5.71719766e-01 6.93928823e-02 6.97646856e-01 8.14446807e-02 6.40304148e-01 -4.37806457e-01 -7.84740448e-02 1.11491048e+00 -3.53266120e-01 -1.13813289e-01 -2.34754071e-01 -4.20069069e-01 7.30637312e-01 1.38622093e+00 -4.21217024e-01 -2.22243428e-01 -1.03498898e-01 4.56644781e-02 -8.58687401e-01 1.10443926e+00 -1.07254839e+00 -1.38560116e-01 3.55800927e-01 5.53287923e-01 -4.62388158e-01 1.71206772e-01 -5.36749125e-01 1.45301744e-01 4.98508930e-01 -1.32392302e-01 -2.29007140e-01 1.59148604e-01 2.67746866e-01 4.51560497e-01 -5.01758993e-01 1.03601146e+00 -5.65176487e-01 -2.75588691e-01 1.48967713e-01 -9.68572736e-01 -2.59179026e-02 9.12887573e-01 -4.17301178e-01 -9.42883134e-01 3.87920082e-01 -1.46231544e+00 -9.48144048e-02 6.22325182e-01 -1.91232353e-01 8.30435902e-02 -7.64980137e-01 -6.80515468e-01 -3.92430365e-01 -2.56448835e-01 -2.37478763e-01 7.89028585e-01 1.52665138e+00 -9.33038294e-01 5.00832260e-01 -7.59174407e-01 -5.81442833e-01 -1.67073298e+00 1.43443614e-01 5.96619368e-01 -5.11149943e-01 -8.60894442e-01 5.83374321e-01 1.39282793e-01 1.15829811e-01 -1.76101491e-01 -4.96581644e-01 -3.78945559e-01 4.42391038e-01 8.42025936e-01 6.51769519e-01 4.17630404e-01 -5.42940676e-01 -4.62985098e-01 3.41344506e-01 -5.50155342e-01 -4.78868820e-02 1.47104430e+00 -3.03796709e-01 -9.33576643e-01 3.81431043e-01 8.99379611e-01 -3.37488711e-01 -9.40566838e-01 4.39020604e-01 2.67728597e-01 5.23349345e-01 -1.40383214e-01 -1.15513968e+00 -9.75364685e-01 7.95969248e-01 1.47008812e+00 1.57940939e-01 5.08230388e-01 2.62252659e-01 8.84571552e-01 1.47779388e-02 3.02514791e-01 -9.07056391e-01 -2.98472911e-01 1.03366926e-01 8.46902609e-01 -7.06999719e-01 -6.20836914e-02 -4.54993039e-01 -2.68893838e-01 1.35283840e+00 3.18625152e-01 -9.21062082e-02 6.20366693e-01 2.57546484e-01 4.93106842e-01 -6.01932406e-01 -2.69855976e-01 -2.54768848e-01 1.33120820e-01 1.09383512e+00 4.14652079e-01 5.55049106e-02 -7.40428150e-01 9.40445125e-01 -9.38831940e-02 2.80862805e-02 3.62013102e-01 6.86693847e-01 -7.82183647e-01 -1.37875557e+00 -4.92312998e-01 7.61081219e-01 -6.11878991e-01 2.17203796e-02 -7.86856651e-01 6.49659991e-01 4.60066974e-01 4.74532485e-01 -1.00807533e-01 3.43644202e-01 -9.95415300e-02 5.69184840e-01 6.30985737e-01 -5.03630221e-01 -5.16313493e-01 2.18057603e-01 7.07891071e-03 -1.65678054e-01 -6.86779320e-01 -9.14402485e-01 -1.72044218e+00 3.72874737e-02 3.92184943e-01 -6.27389103e-02 4.64920670e-01 1.22148263e+00 4.08871263e-01 5.19997239e-01 -6.15389407e-01 -9.87859845e-01 2.84662008e-01 -7.98612297e-01 -7.72653818e-01 -9.25535262e-02 -1.17285373e-02 -6.46876872e-01 -4.31662887e-01 6.83835864e-01]	[14.11558723449707, -2.1132256984710693]
b504926b-46af-4f71-9bc4-29542d8bbad1	residual-contrastive-learning-for-joint	2106.1007	null	https://arxiv.org/abs/2106.10070v2	https://arxiv.org/pdf/2106.10070v2.pdf	Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images	This paper is concerned with contrastive learning (CL) for low-level image restoration and enhancement tasks. We propose a new label-efficient learning paradigm based on residuals, residual contrastive learning (RCL), and derive an unsupervised visual representation learning framework, suitable for low-level vision tasks with noisy inputs. While supervised image reconstruction aims to minimize residual terms directly, RCL alternatively builds a connection between residuals and CL by defining a novel instance discrimination pretext task, using residuals as the discriminative feature. Our formulation mitigates the severe task misalignment between instance discrimination pretext tasks and downstream image reconstruction tasks, present in existing CL frameworks. Experimentally, we find that RCL can learn robust and transferable representations that improve the performance of various downstream tasks, such as denoising and super resolution, in comparison with recent self-supervised methods designed specifically for noisy inputs. Additionally, our unsupervised pre-training can significantly reduce annotation costs whilst maintaining performance competitive with fully-supervised image reconstruction.	['Steven McDonagh', 'Ales Leonardis', 'Eduardo Pérez-Pellitero', 'Yongxin Yang', 'Matteo Maggioni', 'Nanqing Dong']	2021-06-18	null	null	null	null	['unsupervised-pre-training']	['methodology']	[ 9.88249242e-01 2.18643114e-01 -1.64058432e-02 -4.77793425e-01 -1.26637852e+00 -2.52975166e-01 7.10194051e-01 -2.04415303e-02 -4.61549312e-01 6.33179009e-01 4.54608887e-01 -7.87912980e-02 -1.74435496e-01 -4.28142697e-01 -6.65149689e-01 -7.88103759e-01 2.57960975e-01 -5.90744708e-03 1.15202166e-01 -1.02397315e-01 2.45506987e-01 4.97233719e-01 -1.77810013e+00 6.54855967e-01 8.27706099e-01 1.00875628e+00 4.68315005e-01 6.38676107e-01 8.69391561e-02 1.28917766e+00 -4.20822054e-01 1.03639536e-01 3.06775928e-01 -6.25889301e-01 -1.01426375e+00 4.64628875e-01 7.84866810e-01 -3.02751195e-02 -2.77727246e-01 9.59320366e-01 5.65614164e-01 2.24356487e-01 6.94303572e-01 -7.76445985e-01 -7.24658608e-01 3.05535495e-01 -5.14400423e-01 4.06986028e-01 -2.86180619e-03 1.68080240e-01 8.89631391e-01 -1.15797675e+00 7.17578530e-01 1.12099051e+00 8.37622166e-01 6.48928463e-01 -1.79926789e+00 -9.42824036e-02 1.03650011e-01 3.85192968e-02 -1.00011683e+00 -8.75311315e-01 6.80648208e-01 -4.67286706e-01 8.86349618e-01 4.33430046e-01 1.61770910e-01 1.05633450e+00 3.89949195e-02 7.17806041e-01 1.72253227e+00 -4.89958525e-01 1.99220538e-01 2.08552498e-02 -4.47501950e-02 5.29576421e-01 -9.06438306e-02 2.59698540e-01 -5.50883591e-01 2.01041058e-01 8.68911207e-01 -1.47282854e-01 -5.39260149e-01 -3.66921127e-01 -1.12437558e+00 5.56982338e-01 6.74027979e-01 3.47146988e-01 -1.72718689e-01 2.06720501e-01 3.93602878e-01 4.71469790e-01 9.02837753e-01 4.27890539e-01 -4.30071533e-01 4.84340996e-01 -1.18527007e+00 -1.39238521e-01 2.83834130e-01 5.94090521e-01 9.31344926e-01 3.37153286e-01 -5.40171802e-01 1.12769783e+00 1.66227043e-01 3.52445282e-02 4.23519939e-01 -1.36408818e+00 7.22227320e-02 2.87085354e-01 -1.82536691e-01 -5.76560915e-01 -3.08280051e-01 -8.84174168e-01 -1.01231444e+00 6.86396956e-01 1.19143412e-01 4.27223116e-01 -1.14997911e+00 1.72664213e+00 -3.79285365e-02 3.24936032e-01 2.54840553e-01 1.00300920e+00 1.10651314e+00 4.91268247e-01 2.59581268e-01 -6.35778189e-01 8.91440094e-01 -1.18332541e+00 -5.80645025e-01 -4.89509493e-01 3.93463314e-01 -6.54068351e-01 1.10362768e+00 5.22716641e-01 -1.27749276e+00 -8.71977210e-01 -9.41510677e-01 -5.57435453e-01 -8.08712691e-02 1.79801479e-01 4.79744852e-01 4.40836281e-01 -1.46491718e+00 9.21098351e-01 -5.76548874e-01 -4.72638942e-02 6.81318045e-01 1.60861805e-01 -6.02787554e-01 -3.95338446e-01 -6.19794488e-01 9.12100613e-01 1.48042634e-01 1.28179088e-01 -1.08750296e+00 -6.95113301e-01 -1.03071094e+00 -2.49968514e-01 3.10004771e-01 -5.69800735e-01 9.06889141e-01 -1.23305762e+00 -1.36390364e+00 1.44521630e+00 -2.10236043e-01 -4.82699722e-01 4.78360057e-01 -7.43034855e-02 -2.58956432e-01 1.73466638e-01 2.40484983e-01 7.63482571e-01 1.38169611e+00 -1.86213768e+00 -3.96774679e-01 -3.11904162e-01 -1.84331879e-01 3.33338857e-01 -3.52153927e-02 -7.26992190e-02 -4.49514478e-01 -7.55134881e-01 2.42306903e-01 -4.62087989e-01 -5.38202763e-01 1.57571003e-01 -7.05349222e-02 -4.43846323e-02 8.15207243e-01 -8.54050994e-01 6.42859578e-01 -2.25579858e+00 4.45645720e-01 2.84406785e-02 4.36945796e-01 4.09531444e-01 -4.52653229e-01 -4.26800139e-02 -3.07141155e-01 -6.75375611e-02 -8.15155804e-01 -6.76968753e-01 -3.81299525e-01 4.88512307e-01 -1.86673552e-01 6.70138299e-01 6.15581989e-01 1.08489919e+00 -1.00160408e+00 -4.66720730e-01 3.72723043e-01 7.73401082e-01 -3.13302368e-01 3.66808504e-01 -8.72893184e-02 8.70879948e-01 6.37438148e-02 4.74764258e-01 7.58024096e-01 -2.45317534e-01 1.91762805e-01 -5.42868137e-01 -2.18832135e-01 1.95028588e-01 -8.71993184e-01 1.86749887e+00 -7.25730777e-01 7.90474355e-01 3.82769525e-01 -1.45606518e+00 9.32400644e-01 1.36968181e-01 4.47150677e-01 -1.02549362e+00 -1.61302879e-01 1.49897262e-01 -5.95596552e-01 -4.85333741e-01 4.24656451e-01 -2.23964617e-01 2.26015136e-01 8.66816938e-02 4.17639166e-01 -1.60427213e-01 6.07759506e-02 2.59251297e-01 1.23060536e+00 5.46328604e-01 3.03538650e-01 -2.86189169e-01 6.59819484e-01 -2.24765405e-01 6.27708912e-01 8.47499788e-01 -2.30152264e-01 1.08749664e+00 1.49259686e-01 -1.31793380e-01 -9.24245000e-01 -1.21094358e+00 -3.25708061e-01 1.19430757e+00 3.81095870e-03 -3.47253442e-01 -4.58288282e-01 -7.62185395e-01 -2.25555733e-01 2.27314532e-01 -4.90637034e-01 1.78343747e-02 -5.13814807e-01 -7.81458497e-01 2.33279005e-01 4.99920875e-01 4.66977149e-01 -1.20357275e+00 -3.70923042e-01 7.06062540e-02 -2.10626885e-01 -1.17485368e+00 -2.49818683e-01 7.91851819e-01 -9.16631639e-01 -9.99503791e-01 -5.69014013e-01 -1.10039520e+00 7.62124240e-01 4.31015283e-01 1.40379810e+00 2.91299641e-01 -6.31089091e-01 6.20732367e-01 -3.10102642e-01 2.98376560e-01 -4.57797974e-01 -3.45763415e-01 -3.06756318e-01 3.16632763e-02 -2.52386838e-01 -7.03820884e-01 -7.24890232e-01 1.71891563e-02 -1.18735886e+00 -1.30074183e-02 7.72115588e-01 1.17172801e+00 1.02637994e+00 -2.79327594e-02 6.12770021e-01 -1.24767137e+00 3.72741073e-01 -2.62817562e-01 -2.73649424e-01 8.98594335e-02 -8.72024179e-01 3.20942372e-01 4.68091011e-01 -2.04464272e-01 -1.28965509e+00 3.25834483e-01 -2.22570926e-01 -3.98993641e-01 -2.70578265e-01 2.24024624e-01 -1.19564310e-01 -4.52199638e-01 9.56736624e-01 2.96883583e-01 4.61669676e-02 -6.41883016e-01 6.74029946e-01 5.78888595e-01 1.06146252e+00 -4.24872607e-01 8.63831520e-01 5.61402500e-01 9.67953131e-02 -8.22421074e-01 -1.14415252e+00 -7.60143459e-01 -7.38777339e-01 -2.49791086e-01 7.79981256e-01 -1.23450232e+00 -3.08332175e-01 2.50261098e-01 -8.53039503e-01 -5.65631330e-01 -7.72197127e-01 6.57059997e-02 -8.46572280e-01 6.48877501e-01 -7.65529871e-01 -7.35855460e-01 -2.73667485e-01 -1.09623122e+00 1.27671683e+00 -4.89182249e-02 2.56321877e-01 -1.02352405e+00 -4.44702581e-02 6.37714207e-01 5.62427461e-01 4.12309378e-01 6.20468318e-01 -5.99143235e-03 -4.41802442e-01 4.13412929e-01 -5.58527529e-01 1.08840775e+00 -3.78842317e-02 -7.11803794e-01 -1.32238865e+00 -5.70115626e-01 1.88398331e-01 -7.41315842e-01 1.56122720e+00 2.90922999e-01 1.35353458e+00 -2.97990412e-01 5.59369773e-02 8.80432427e-01 1.77260518e+00 -4.82794523e-01 1.07767189e+00 2.96168983e-01 8.27476919e-01 7.91653931e-01 4.11361843e-01 -2.18219999e-02 2.16879755e-01 5.21175265e-01 4.67166692e-01 -6.22560978e-01 -8.76818180e-01 -8.13599303e-02 5.31605422e-01 6.69920564e-01 -2.41424024e-01 7.94141665e-02 -4.39633042e-01 5.58873177e-01 -1.89832199e+00 -9.31364357e-01 -2.81002790e-01 2.05462050e+00 1.14783788e+00 -1.66196793e-01 -2.36122325e-01 4.34490293e-01 4.10007894e-01 3.87399346e-01 -4.32138383e-01 -1.58378452e-01 -4.07757759e-01 7.32155323e-01 5.71452081e-01 5.95008135e-01 -1.34974813e+00 9.87478435e-01 6.76978016e+00 8.41810524e-01 -8.99906039e-01 4.48627561e-01 7.42458522e-01 1.43579245e-01 -2.95482159e-01 8.26212317e-02 -2.80041486e-01 1.87713221e-01 7.37121940e-01 4.87846792e-01 4.63380069e-01 5.49521267e-01 2.28102744e-01 1.35280341e-01 -1.12582874e+00 1.11875403e+00 3.19037527e-01 -1.40639234e+00 8.85846186e-03 -1.29643828e-01 9.00559485e-01 5.39468862e-02 2.66626477e-01 1.63256511e-01 1.73554093e-01 -1.28928459e+00 4.85873997e-01 6.50422096e-01 1.05448830e+00 -5.53105533e-01 4.83456194e-01 1.30318344e-01 -1.05899680e+00 -1.81420460e-01 -3.55121136e-01 8.42596740e-02 -1.82391405e-02 8.15062344e-01 -2.60455102e-01 6.38618588e-01 9.32530284e-01 1.26195192e+00 -8.05031776e-01 8.58217180e-01 -4.94131923e-01 5.09321332e-01 3.29905719e-01 1.01666057e+00 -6.57771006e-02 -1.77298054e-01 5.20214319e-01 1.50645614e+00 -1.64892212e-01 -9.51512977e-02 4.12377834e-01 7.18563974e-01 -2.15977043e-01 -4.23991978e-02 -5.07243037e-01 4.07868445e-01 -8.26683715e-02 1.50831330e+00 -5.67799807e-01 -2.55667239e-01 -2.49053895e-01 1.46523046e+00 5.42058229e-01 5.24745643e-01 -3.22880477e-01 -1.84681341e-02 4.18675393e-01 2.13122800e-01 2.78697729e-01 -1.06504150e-01 -3.22363287e-01 -1.17721629e+00 7.20528215e-02 -9.28806365e-01 2.76049465e-01 -8.63487542e-01 -1.56427360e+00 5.84178030e-01 -3.54198009e-01 -1.29507756e+00 -6.48313239e-02 -5.73927224e-01 -3.41216266e-01 6.41836107e-01 -2.25420380e+00 -1.42606163e+00 -4.62726623e-01 8.06566417e-01 7.10418880e-01 9.71610174e-02 6.87045574e-01 2.60249048e-01 -2.82060176e-01 4.37260419e-01 1.43937111e-01 -1.50308132e-01 8.23524415e-01 -1.58984792e+00 -6.34477362e-02 1.13176489e+00 2.66314864e-01 3.10008466e-01 5.23807049e-01 -3.68284881e-01 -1.17475569e+00 -1.52790511e+00 5.83721519e-01 -3.35305274e-01 2.61832058e-01 -2.37764984e-01 -1.00328135e+00 5.49753547e-01 1.24536216e-01 6.57796502e-01 4.25360978e-01 -1.93004817e-01 -7.23794997e-01 -6.58246875e-02 -1.31259882e+00 2.03885093e-01 1.41904724e+00 -9.68705356e-01 -4.95093882e-01 5.28516531e-01 5.96362531e-01 -2.08607003e-01 -9.66372907e-01 5.46031594e-01 9.18368436e-03 -1.02461648e+00 1.37273133e+00 -3.03239316e-01 5.68569183e-01 -5.17188191e-01 -2.62706786e-01 -1.19985890e+00 -4.99665052e-01 -5.19768596e-01 -1.87726185e-01 1.25910389e+00 1.49137869e-01 -2.99653560e-01 4.55754638e-01 -5.06868446e-03 -4.34893996e-01 -2.87975073e-01 -9.00624216e-01 -6.91477060e-01 -5.70687428e-02 -3.01372439e-01 -2.68790692e-01 9.36461329e-01 -4.72067088e-01 5.04435539e-01 -6.38232470e-01 1.47231966e-01 1.22877681e+00 -6.79927990e-02 4.07803714e-01 -1.30689824e+00 -5.39701998e-01 -1.80976659e-01 -4.23063487e-01 -1.04455948e+00 3.97890091e-01 -1.35959959e+00 5.15436530e-01 -1.67119682e+00 2.47001857e-01 -4.70336616e-01 -5.02000034e-01 6.94290638e-01 -1.84967905e-01 1.05395865e+00 1.33013483e-02 4.28231716e-01 -8.32783937e-01 4.13072377e-01 1.18799901e+00 -3.35703075e-01 -9.47315022e-02 -3.11724603e-01 -8.13120425e-01 5.35126269e-01 5.45140862e-01 -3.90201360e-01 -4.02561635e-01 -4.72279727e-01 -6.29875585e-02 -7.28604198e-02 7.06556320e-01 -8.48836958e-01 5.90605475e-03 8.49770904e-02 6.26273334e-01 -1.37079358e-01 2.60685802e-01 -5.42182505e-01 -1.03435010e-01 1.35895759e-01 -6.16510570e-01 -5.53046525e-01 -9.56327394e-02 7.68750489e-01 -2.93158025e-01 -1.95692763e-01 1.17471635e+00 -3.90329272e-01 -9.81817722e-01 2.34266389e-02 -3.56024027e-01 7.48611614e-02 5.68558276e-01 -2.52094954e-01 -3.65363806e-01 -1.06571935e-01 -1.07486570e+00 -1.17160670e-01 4.86134708e-01 1.76890343e-01 1.02455425e+00 -1.03919959e+00 -8.68642449e-01 1.64881110e-01 2.31540725e-01 6.61045238e-02 2.33991265e-01 8.63412559e-01 -2.11504787e-01 -1.55387372e-01 -2.41575867e-01 -6.63926959e-01 -1.24514401e+00 4.42156941e-01 3.58864188e-01 -3.78555298e-01 -1.15201366e+00 7.32448220e-01 9.49814320e-02 -4.19772089e-01 2.76775837e-01 -3.70438807e-02 -3.91271144e-01 -1.49199963e-01 5.96453667e-01 2.51628399e-01 3.38650942e-01 -7.55552471e-01 -1.58912227e-01 5.76537669e-01 -3.92889269e-02 9.24125034e-03 1.69593179e+00 -3.11275125e-01 -3.24676156e-01 3.16401094e-01 1.31159329e+00 -1.58625185e-01 -1.68585455e+00 -5.11239529e-01 1.90309212e-01 -4.55603272e-01 7.19592094e-01 -8.32457423e-01 -1.20688784e+00 6.70040786e-01 1.00628293e+00 -1.00637406e-01 1.52489138e+00 1.22723475e-01 4.81266081e-01 8.29954892e-02 2.30876803e-01 -9.96312261e-01 4.65212554e-01 2.76162267e-01 9.03063834e-01 -1.48983777e+00 1.63219199e-01 -4.53124702e-01 -5.57755470e-01 8.10634255e-01 3.65010679e-01 -3.71260434e-01 3.07539821e-01 3.27062041e-01 5.28198667e-02 -1.57083884e-01 -6.87078953e-01 -8.11296344e-01 4.47466224e-01 1.14311707e+00 4.85885531e-01 -2.51115590e-01 -3.18530589e-01 1.39134377e-01 3.69519621e-01 -1.92683667e-01 5.00413299e-01 1.01336968e+00 -4.83747751e-01 -1.28117180e+00 -1.68700606e-01 3.32766533e-01 -4.32552546e-01 -3.06479007e-01 -2.62428373e-01 3.33586782e-01 3.58787715e-01 1.13391685e+00 4.50951159e-02 -1.64409071e-01 1.95515648e-01 -1.71640351e-01 7.82841384e-01 -8.34607899e-01 -7.36886561e-01 2.02088803e-01 1.67316548e-03 -7.54237771e-01 -1.00313604e+00 -3.15886438e-01 -1.06480908e+00 3.38603258e-01 -1.54751107e-01 -1.31081879e-01 4.40543383e-01 1.00315022e+00 1.99869692e-01 7.06379712e-01 8.55914652e-01 -1.23868883e+00 -2.78094858e-01 -7.81364024e-01 -5.42919338e-01 7.21718252e-01 6.63472831e-01 -4.94336486e-01 -5.59878051e-01 4.46990818e-01]	[11.209341049194336, -2.171700954437256]
119553dd-1dc6-4458-9203-80ba06cbbbb3	make-an-audio-2-temporal-enhanced-text-to	2305.18474	null	https://arxiv.org/abs/2305.18474v1	https://arxiv.org/pdf/2305.18474v1.pdf	Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation	Large diffusion models have been successful in text-to-audio (T2A) synthesis tasks, but they often suffer from common issues such as semantic misalignment and poor temporal consistency due to limited natural language understanding and data scarcity. Additionally, 2D spatial structures widely used in T2A works lead to unsatisfactory audio quality when generating variable-length audio samples since they do not adequately prioritize temporal information. To address these challenges, we propose Make-an-Audio 2, a latent diffusion-based T2A method that builds on the success of Make-an-Audio. Our approach includes several techniques to improve semantic alignment and temporal consistency: Firstly, we use pre-trained large language models (LLMs) to parse the text into structured <event & order> pairs for better temporal information capture. We also introduce another structured-text encoder to aid in learning semantic alignment during the diffusion denoising process. To improve the performance of variable length generation and enhance the temporal information extraction, we design a feed-forward Transformer-based diffusion denoiser. Finally, we use LLMs to augment and transform a large amount of audio-label data into audio-text datasets to alleviate the problem of scarcity of temporal data. Extensive experiments show that our method outperforms baseline models in both objective and subjective metrics, and achieves significant gains in temporal information understanding, semantic consistency, and sound quality.	['Zhou Zhao', 'Zejun Ma', 'Xiang Yin', 'Jinglin Liu', 'Chen Zhang', 'Zhenhui Ye', 'Dongchao Yang', 'Rongjie Huang', 'Yi Ren', 'Jiawei Huang']	2023-05-29	null	null	null	null	['audio-generation', 'temporal-information-extraction']	['audio', 'natural-language-processing']	[ 1.78190693e-01 -7.40544945e-02 -1.93683341e-01 -3.17175537e-01 -1.39651108e+00 -4.60023612e-01 4.43945557e-01 -5.62945344e-02 3.28589343e-02 3.14880818e-01 8.64084482e-01 -5.38316891e-02 -1.30148843e-01 -6.16832197e-01 -4.87770647e-01 -5.69056749e-01 4.06504460e-02 2.25106537e-01 2.52291739e-01 -1.16156153e-01 -6.83616027e-02 -1.37053147e-01 -1.38839912e+00 5.24990499e-01 9.01225746e-01 1.17534626e+00 4.60726291e-01 6.24804914e-01 -2.66057968e-01 9.32399571e-01 -7.79794872e-01 -2.51801699e-01 1.38475433e-01 -8.27833056e-01 -7.41035640e-01 -7.37225786e-02 2.33269900e-01 -4.98380542e-01 -2.74715066e-01 8.26744318e-01 9.15035725e-01 1.30392194e-01 4.12191242e-01 -1.20604587e+00 -4.93984282e-01 9.65209305e-01 -4.48061734e-01 2.29009688e-01 4.43723977e-01 -4.27866466e-02 1.19744778e+00 -9.52576995e-01 5.33982635e-01 1.44128978e+00 9.28043962e-01 4.06989306e-01 -1.16126740e+00 -9.11591649e-01 1.72192380e-01 4.17784810e-01 -1.26602423e+00 -9.26871955e-01 9.81413007e-01 -3.26744109e-01 9.98046339e-01 1.78202987e-01 6.90437675e-01 1.44723296e+00 -5.90215474e-02 8.52845132e-01 7.30090082e-01 -4.25263494e-01 2.02110067e-01 -3.79057229e-01 -4.35342699e-01 3.44187349e-01 -7.98425198e-01 1.34494171e-01 -1.18730676e+00 1.28590465e-01 6.90953851e-01 -4.12868857e-01 -7.49285296e-02 1.66092247e-01 -1.32129669e+00 6.60216331e-01 7.59315677e-03 3.99859250e-01 -4.94954407e-01 2.31684849e-01 6.61222577e-01 4.95944470e-01 6.84165597e-01 3.96266222e-01 -2.30144322e-01 -5.26748598e-01 -1.27772939e+00 2.82573909e-01 2.81679600e-01 9.48388934e-01 2.44170815e-01 5.75960100e-01 -3.33047271e-01 1.29207134e+00 3.61235291e-01 6.15988970e-01 7.71584213e-01 -1.25864708e+00 7.38632262e-01 -1.64357677e-01 -1.47469148e-01 -1.01958430e+00 -2.13973507e-01 -4.29933995e-01 -8.25445652e-01 -3.15598011e-01 5.30656278e-02 4.41572852e-02 -8.78351986e-01 1.95805848e+00 1.08466499e-01 2.56089747e-01 -1.88991632e-02 8.03766906e-01 4.70685273e-01 9.95972097e-01 1.27388891e-02 -3.90418082e-01 1.13489759e+00 -1.14554632e+00 -1.24953973e+00 -2.33917147e-01 6.49161220e-01 -1.06467855e+00 9.97709990e-01 4.61925924e-01 -1.32457423e+00 -7.60889173e-01 -1.00599706e+00 -2.70989478e-01 1.54216528e-01 7.17346370e-02 2.72040784e-01 3.77580523e-01 -9.42921579e-01 5.86483538e-01 -8.27413082e-01 -1.13653176e-01 1.34408697e-01 -2.87077446e-02 -1.68102216e-02 1.39303710e-02 -1.46865726e+00 5.06711960e-01 1.38805225e-01 -2.10353918e-02 -1.10780883e+00 -8.72300446e-01 -8.44639122e-01 -1.22010417e-01 3.63712221e-01 -5.42282283e-01 1.64335907e+00 -6.66028380e-01 -1.68607330e+00 3.09996933e-01 -3.67069274e-01 -6.68171108e-01 3.19706559e-01 -3.71867746e-01 -6.91086531e-01 3.32853347e-01 3.93577129e-01 9.19829607e-01 1.11110044e+00 -8.40072989e-01 -7.98462510e-01 -1.41719744e-01 -3.38348508e-01 3.01477164e-01 -5.87195098e-01 -9.00501162e-02 -5.81140578e-01 -1.53864956e+00 3.16968560e-01 -7.52504110e-01 -7.61025995e-02 -1.48728490e-01 -2.66382784e-01 -9.81806368e-02 9.71875012e-01 -1.10611176e+00 1.70083940e+00 -2.27569509e+00 3.36794019e-01 5.06921969e-02 -5.82369715e-02 -4.89491634e-02 -4.29243535e-01 4.35472071e-01 -3.77096683e-02 3.65417227e-02 -1.86112478e-01 -7.16334164e-01 8.53991881e-02 1.45398796e-01 -7.28239477e-01 -4.48632725e-02 3.23209651e-02 5.73391557e-01 -9.34742630e-01 -6.09393835e-01 9.55247730e-02 5.26319802e-01 -6.63368523e-01 2.26983413e-01 -3.83373529e-01 6.78310335e-01 -2.26317763e-01 4.55214918e-01 1.68702409e-01 1.15370087e-01 -5.12920320e-02 -4.18712527e-01 -1.36120003e-02 1.00418699e+00 -1.17319477e+00 2.25481105e+00 -9.39881921e-01 6.09727502e-01 8.63262266e-02 -8.74381065e-01 8.23958993e-01 7.78898716e-01 8.52349997e-01 -1.15685380e+00 -1.27613112e-01 3.90989602e-01 -2.83773929e-01 -5.32582521e-01 6.12769842e-01 -3.97711068e-01 -1.56460181e-02 5.80758333e-01 1.02495573e-01 -6.93337977e-01 9.52536166e-02 2.40880594e-01 1.01345265e+00 6.67249113e-02 -2.77215123e-01 2.54402190e-01 9.24741551e-02 -2.41869822e-01 7.21911728e-01 3.58843356e-01 1.58868786e-02 9.97464955e-01 1.58510864e-01 1.53564394e-01 -1.14397812e+00 -1.00303054e+00 2.50278115e-01 9.89570260e-01 -9.28180069e-02 -9.21889424e-01 -6.79518461e-01 -3.38461310e-01 -3.76589179e-01 8.25956345e-01 -1.15678474e-01 -1.99865043e-01 -6.07043207e-01 -3.62219185e-01 8.54932964e-01 7.59251356e-01 4.11772490e-01 -7.09020495e-01 -1.83329023e-02 7.41558731e-01 -1.02959871e+00 -1.25869679e+00 -9.32526529e-01 -6.12880336e-04 -8.95592988e-01 -4.65789080e-01 -7.75789440e-01 -7.26006150e-01 3.66999172e-02 2.75122792e-01 8.49829197e-01 -4.69019979e-01 1.40905738e-01 9.61697474e-02 -5.21664381e-01 -2.76052803e-01 -5.85765660e-01 1.48647919e-01 2.39581436e-01 -4.16665524e-02 -3.63779031e-02 -9.72275138e-01 -4.70398605e-01 5.57051361e-01 -9.56105709e-01 1.73970297e-01 3.68448615e-01 7.52074420e-01 5.80912471e-01 4.42674905e-01 9.43878710e-01 -2.53702939e-01 9.43833351e-01 -3.00844312e-01 -1.95504233e-01 -5.04749343e-02 -6.93554759e-01 7.48236850e-02 5.71811855e-01 -7.17765808e-01 -1.06388175e+00 -2.92927444e-01 -5.28130710e-01 -6.90476358e-01 4.39637154e-01 6.42538548e-01 -1.54097781e-01 5.51634073e-01 5.83407402e-01 1.69828966e-01 -7.81029090e-02 -6.95708156e-01 5.12300849e-01 9.42300618e-01 6.86897933e-01 -5.45964897e-01 6.18990362e-01 3.07784677e-01 -3.91883880e-01 -8.25751483e-01 -8.95990133e-01 -4.27835524e-01 -2.55028665e-01 -1.17352307e-01 8.16479981e-01 -1.22430062e+00 -4.22550142e-02 6.97447538e-01 -1.08523476e+00 -5.02618968e-01 -4.55236077e-01 6.83330357e-01 -6.80652380e-01 4.26550865e-01 -8.56829941e-01 -5.83662271e-01 -3.63707483e-01 -1.15122771e+00 1.28630090e+00 -3.45553190e-01 -7.18165100e-01 -8.52657318e-01 -7.35527053e-02 5.08414030e-01 6.78775132e-01 -3.44544083e-01 8.57108831e-01 -1.69952810e-01 -5.12036264e-01 1.99530870e-01 2.15894595e-01 4.52200383e-01 2.97642887e-01 -2.68853962e-01 -9.54014421e-01 -1.11759394e-01 2.03579590e-01 -3.88141990e-01 6.31933808e-01 4.41605628e-01 1.10967755e+00 -4.07041490e-01 -1.26556888e-01 4.57938790e-01 6.73705697e-01 3.75356227e-01 4.46322292e-01 1.21819779e-01 5.89322925e-01 5.92466593e-01 8.29012096e-01 5.85451424e-01 5.01961946e-01 1.02287805e+00 -3.84856351e-02 9.57194492e-02 -7.76865602e-01 -6.76583648e-01 6.32813394e-01 1.84896505e+00 3.29160273e-01 -2.56615967e-01 -6.53041244e-01 9.78465855e-01 -1.58255064e+00 -9.37986732e-01 1.43153563e-01 1.84987116e+00 1.36851609e+00 2.20967785e-01 1.85941979e-01 6.18509293e-01 4.85783756e-01 4.46324855e-01 -3.47833723e-01 -1.63143083e-01 -1.90942511e-01 3.15855965e-02 1.17039926e-01 5.66067219e-01 -7.02934384e-01 8.48110616e-01 6.08238316e+00 1.41565514e+00 -1.19711781e+00 4.08447266e-01 3.63006860e-01 -3.90099198e-01 -7.42097974e-01 -5.92028350e-02 -5.50071001e-01 5.75855434e-01 1.15508223e+00 3.91474850e-02 5.73868811e-01 3.36046755e-01 6.90882623e-01 2.58679718e-01 -1.11625636e+00 1.09492815e+00 -1.21826857e-01 -1.25948799e+00 3.37337665e-02 -2.95769811e-01 7.45554864e-01 -2.48868674e-01 1.96257025e-01 2.37729266e-01 1.06546178e-01 -7.53152370e-01 1.35077119e+00 3.09405923e-01 9.85301971e-01 -5.50789058e-01 2.26349235e-01 2.56496429e-01 -1.58522642e+00 -1.02448404e-01 2.03570217e-01 1.77179337e-01 6.76589608e-01 8.13633800e-01 -7.28195131e-01 4.90393132e-01 7.50061929e-01 8.56281042e-01 -2.31003910e-02 7.17445016e-01 -4.18217361e-01 8.36655796e-01 -4.86344218e-01 4.03168321e-01 2.33756244e-01 3.81057598e-02 7.39422917e-01 1.07191098e+00 6.04266763e-01 -1.58539619e-02 4.24408307e-03 6.91013575e-01 -4.66957763e-02 -1.28446175e-02 -4.28058714e-01 -3.32986563e-01 8.49099040e-01 5.78027725e-01 -3.66869569e-01 -2.14147896e-01 -2.39873841e-01 1.17247653e+00 -2.56716549e-01 3.69720668e-01 -9.19581652e-01 -3.67085487e-01 5.72705269e-01 1.39739707e-01 3.31710309e-01 -3.96550059e-01 -1.85792774e-01 -1.03241336e+00 2.72252023e-01 -1.11340511e+00 2.50668645e-01 -1.07236922e+00 -1.14137459e+00 6.38406813e-01 -2.75186822e-02 -1.30277908e+00 -6.41898632e-01 2.38191739e-01 -1.97056994e-01 6.96881592e-01 -1.33088171e+00 -1.18007374e+00 3.90084200e-02 5.65490186e-01 1.17352080e+00 1.79676549e-03 6.20252490e-01 8.28796566e-01 -1.96802691e-01 6.31361961e-01 -7.69051760e-02 -1.93811581e-01 1.03216672e+00 -9.97990012e-01 5.88976920e-01 9.03660595e-01 2.85656840e-01 3.21267068e-01 6.09006166e-01 -7.22385526e-01 -1.15650392e+00 -1.20147598e+00 1.16677475e+00 -2.44816095e-01 7.72715211e-01 -3.96190375e-01 -8.13860595e-01 5.17772496e-01 9.14715454e-02 -4.51741040e-01 4.85416889e-01 2.02556346e-02 -3.29512775e-01 -3.95311058e-01 -6.79572880e-01 7.44600713e-01 1.27858520e+00 -1.21962202e+00 -5.70324242e-01 1.60427824e-01 1.20981526e+00 -4.72833306e-01 -1.04539108e+00 3.82099152e-01 4.44034010e-01 -6.73590064e-01 1.03613460e+00 5.82265258e-02 4.36574012e-01 -2.40987673e-01 -2.54958898e-01 -1.46773601e+00 -8.54313001e-03 -1.18787503e+00 -5.82632124e-02 1.72233796e+00 3.47491860e-01 -1.68853551e-01 4.33096915e-01 8.08720812e-02 -3.34986836e-01 -4.58496273e-01 -1.01468611e+00 -8.84957314e-01 -2.02205122e-01 -9.91540253e-01 5.35821378e-01 9.50158417e-01 6.29782453e-02 5.79442739e-01 -7.44786084e-01 1.09259620e-01 4.27952170e-01 -4.18776087e-02 3.80931139e-01 -7.56197751e-01 -3.64399165e-01 -4.05169219e-01 6.21941835e-02 -1.54233503e+00 -8.24099779e-02 -5.92341781e-01 2.73011506e-01 -1.44298196e+00 -3.79541397e-01 -7.31400788e-01 -3.87649313e-02 5.13774216e-01 1.50416255e-01 2.50964433e-01 1.48577765e-01 3.95261258e-01 -3.81472975e-01 9.63971615e-01 1.21162450e+00 -3.66492242e-01 -4.21101719e-01 -4.72100358e-03 -3.82407099e-01 5.21468759e-01 4.88303274e-01 -6.74354970e-01 -8.22942615e-01 -7.71179318e-01 2.03180835e-01 5.72207868e-01 -7.48178136e-05 -1.11593115e+00 3.08376431e-01 7.38605410e-02 -1.26221716e-01 -7.09982395e-01 6.69702053e-01 -7.63999104e-01 3.38347107e-01 4.29692976e-02 -6.38050616e-01 1.18956104e-01 2.25710392e-01 5.41346788e-01 -7.28908420e-01 5.55680087e-03 5.40646791e-01 1.24299802e-01 -4.64087695e-01 2.01457575e-01 -5.72086990e-01 1.62603930e-01 4.78384733e-01 -4.50108806e-03 2.99363118e-02 -9.22150433e-01 -6.54384494e-01 1.97085157e-01 1.15441278e-01 7.56244481e-01 5.23625135e-01 -1.69096816e+00 -6.11348093e-01 2.32329309e-01 9.63706616e-03 1.42646372e-01 4.00444239e-01 9.52654004e-01 -1.60539430e-02 4.90093738e-01 1.42111912e-01 -5.64961255e-01 -1.16361701e+00 1.94822982e-01 1.14307843e-01 -2.24404380e-01 -7.56014347e-01 9.53760445e-01 1.07996957e-02 -9.89314616e-02 6.72773838e-01 -6.28459573e-01 1.57816008e-01 2.91871816e-01 3.56555164e-01 3.78865212e-01 2.36778945e-01 -5.36166608e-01 -9.58482847e-02 5.44488907e-01 1.02269545e-01 -8.38310599e-01 1.30960214e+00 -6.67113960e-01 2.08477587e-01 4.82056648e-01 1.20328999e+00 3.89602065e-01 -1.24109209e+00 -4.78680223e-01 -1.18545145e-01 -2.91701764e-01 3.24540079e-01 -7.27356851e-01 -1.06528032e+00 1.14853156e+00 4.24946576e-01 2.56714910e-01 1.50225282e+00 -2.37524450e-01 1.54820454e+00 5.87850856e-03 1.18837608e-02 -1.35674655e+00 5.92503607e-01 5.03293514e-01 9.11444783e-01 -7.89802551e-01 -3.44208688e-01 -2.67526954e-01 -7.29325950e-01 9.30440426e-01 2.46524528e-01 6.40903294e-01 5.16891301e-01 4.88298446e-01 3.24238837e-01 -3.50525975e-02 -8.64073515e-01 -2.83497982e-02 2.67037243e-01 5.66010773e-01 1.90560162e-01 -3.02825153e-01 4.60118949e-02 6.58896089e-01 -5.64457655e-01 -5.02708554e-02 2.08254650e-01 8.22851300e-01 -1.62471727e-01 -1.35509014e+00 -4.01572943e-01 -9.08990875e-02 -5.67620039e-01 -2.33599916e-01 -1.49149433e-01 2.12774411e-01 -9.99874324e-02 1.26786840e+00 -6.79185465e-02 -5.80067456e-01 2.35640436e-01 1.61021471e-01 3.33430856e-01 -3.43538135e-01 -3.53933573e-01 8.12720954e-01 3.38590771e-01 -6.45127416e-01 -4.70178485e-01 -5.37868083e-01 -1.26530683e+00 -6.75787032e-02 -3.61696005e-01 2.07039565e-01 8.10254574e-01 9.87188578e-01 4.76688743e-01 9.66774404e-01 7.36208141e-01 -6.95441008e-01 -5.40657401e-01 -1.14507151e+00 -4.35680360e-01 3.79649967e-01 5.32635987e-01 -4.66683388e-01 -2.93721378e-01 3.32377970e-01]	[15.414769172668457, 5.650062084197998]
1cccd72a-4ab4-4cab-ba5e-d3b1212f5d41	using-a-novel-fractional-order-gradient	2205.00581	null	https://arxiv.org/abs/2205.00581v1	https://arxiv.org/pdf/2205.00581v1.pdf	Using a novel fractional-order gradient method for CNN back-propagation	Computer-aided diagnosis tools have experienced rapid growth and development in recent years. Among all, deep learning is the most sophisticated and popular tool. In this paper, researchers propose a novel deep learning model and apply it to COVID-19 diagnosis. Our model uses the tool of fractional calculus, which has the potential to improve the performance of gradient methods. To this end, the researcher proposes a fractional-order gradient method for the back-propagation of convolutional neural networks based on the Caputo definition. However, if only the first term of the infinite series of the Caputo definition is used to approximate the fractional-order derivative, the length of the memory is truncated. Therefore, the fractional-order gradient (FGD) method with a fixed memory step and an adjustable number of terms is used to update the weights of the layers. Experiments were performed on the COVIDx dataset to demonstrate fast convergence, good accuracy, and the ability to bypass the local optimal point. We also compared the performance of the developed fractional-order neural networks and Integer-order neural networks. The results confirmed the effectiveness of our proposed model in the diagnosis of COVID-19.	['Weihua Guo', 'Mohammed Alghaili', 'Talal Ahmed Ali Ali', 'Ningbo Zhu', 'Mundher Mohammed Taresh']	2022-05-01	null	null	null	null	['covid-19-detection']	['medical']	[-2.19013363e-01 -5.63401021e-02 4.30388525e-02 -1.87789530e-01 3.54253163e-04 2.19696045e-01 -2.60627288e-02 -9.47021246e-02 -4.77150321e-01 8.59265387e-01 -2.92691886e-01 -4.11537468e-01 -1.60560504e-01 -8.02193940e-01 -5.64841449e-01 -7.57261634e-01 -1.42266661e-01 9.72137749e-02 2.28023976e-01 -1.08330883e-01 2.00293556e-01 6.61779463e-01 -1.26152933e+00 4.97266427e-02 1.18884528e+00 1.36528635e+00 8.27809945e-02 5.16584337e-01 -2.70700425e-01 8.57643545e-01 -3.52465510e-01 -1.15909591e-01 1.09969787e-01 -3.81695181e-01 -5.53387105e-01 -2.69247681e-01 8.04162547e-02 -7.02084184e-01 -2.51393616e-01 8.79574776e-01 7.58561611e-01 3.94471958e-02 6.70923471e-01 -9.32228982e-01 -5.03039896e-01 2.63576180e-01 -5.39431632e-01 2.46778384e-01 -1.15376651e-01 -1.33847907e-01 1.69694990e-01 -7.84480274e-01 3.19121540e-01 1.15459836e+00 1.35014510e+00 4.87761497e-01 -4.95312363e-01 -7.17398167e-01 -1.31644174e-01 3.11756283e-01 -1.16141498e+00 2.39679404e-03 8.67489278e-01 -5.29639602e-01 9.07884300e-01 -1.52744591e-01 8.73153210e-01 4.00841385e-01 6.33208811e-01 6.72466218e-01 7.79919565e-01 -6.66355908e-01 1.92502722e-01 -3.54323769e-03 2.18739256e-01 1.29686975e+00 1.88811526e-01 1.21149607e-01 6.02753758e-02 -1.31410360e-01 1.16988158e+00 1.47465482e-01 -2.77714282e-01 -4.62113246e-02 -5.81788540e-01 1.02006042e+00 6.41045153e-01 5.29587269e-01 -5.03409564e-01 3.83962154e-01 5.02690017e-01 5.31133972e-02 8.16073835e-01 3.11026067e-01 -3.75859410e-01 1.17663674e-01 -1.05139673e+00 1.07682742e-01 6.60649657e-01 4.41157818e-01 2.97831386e-01 2.60650605e-01 -1.74667567e-01 9.92412448e-01 2.88630635e-01 2.11433142e-01 7.25553691e-01 -9.38535392e-01 -6.29611164e-02 6.54417157e-01 4.69707232e-03 -1.12519360e+00 -6.99449837e-01 -6.97537839e-01 -1.18278003e+00 4.86367822e-01 4.63246554e-01 -4.44126248e-01 -1.11487114e+00 1.37754858e+00 3.60503107e-01 4.82524663e-01 6.18261658e-03 8.83716106e-01 5.43118775e-01 5.95580518e-01 -4.23604958e-02 -3.05005759e-01 8.97055447e-01 -8.14979970e-01 -8.60236228e-01 2.42132276e-01 6.37705684e-01 -5.45476019e-01 5.98720789e-01 2.04748616e-01 -1.12207532e+00 -4.57782179e-01 -1.37346649e+00 -1.45749852e-01 -2.89603114e-01 4.84210849e-01 8.58082235e-01 3.81675482e-01 -1.14604127e+00 1.07208383e+00 -9.00347769e-01 1.05220936e-01 4.27025437e-01 2.38247514e-01 1.77879363e-01 9.03803110e-02 -1.51831627e+00 8.60585868e-01 1.86528608e-01 5.03340125e-01 -3.41454178e-01 -1.01084435e+00 -4.75475341e-01 -6.08310290e-02 -2.46789038e-01 -7.17028677e-01 1.08054626e+00 -1.12913394e+00 -1.71401131e+00 6.81287527e-01 -5.72853314e-04 -6.84035301e-01 9.71329689e-01 -2.70853430e-01 -2.57256031e-01 2.07279980e-01 -5.27361855e-02 3.81038070e-01 9.05124903e-01 -6.24890625e-01 -7.80711710e-01 -1.40885726e-01 7.00811448e-04 -1.39556184e-01 -3.46345872e-01 -4.13935930e-01 -1.60171151e-01 -7.04317868e-01 2.57975817e-01 -8.54607105e-01 -1.20010488e-01 4.14829224e-01 1.57705083e-01 -3.14527780e-01 6.16024017e-01 -9.83834207e-01 1.32266557e+00 -2.30462527e+00 -2.56444722e-01 1.58568829e-01 2.09227011e-01 5.79577029e-01 3.28276902e-01 -1.02492653e-01 -1.33634254e-01 -1.33917471e-02 -4.18596715e-01 7.60778487e-02 -3.91588539e-01 1.22943580e-01 9.03276503e-02 4.62895602e-01 1.19975895e-01 6.37468636e-01 -8.15069258e-01 -4.11886185e-01 9.96998847e-02 8.29227686e-01 -5.86945772e-01 -2.93431342e-01 -2.53090467e-02 2.08483711e-01 -4.78735477e-01 3.61264914e-01 9.47338164e-01 -2.07612202e-01 -2.12531611e-01 -4.21774238e-01 -2.97780633e-01 -3.24955046e-01 -8.27309549e-01 1.23407662e+00 -7.09886491e-01 6.91824257e-01 6.29037693e-02 -1.10282254e+00 7.30259836e-01 4.05811280e-01 7.76436150e-01 -7.39098608e-01 2.51261771e-01 7.65292048e-01 -9.52571630e-02 -6.46988869e-01 -9.43009853e-02 -1.87858477e-01 6.08691156e-01 -3.18092816e-02 -2.64522791e-01 1.44003794e-01 1.92938969e-01 -4.07322556e-01 8.80755246e-01 -2.06527591e-01 8.60937983e-02 -3.54540914e-01 8.97166610e-01 -2.06449747e-01 5.72657168e-01 3.62037808e-01 -1.83844924e-01 4.04786438e-01 4.95329380e-01 -8.13787878e-01 -9.49734032e-01 -6.22094810e-01 -4.41333205e-01 6.16789997e-01 -2.14435071e-01 3.86242718e-01 -9.26072121e-01 -4.43148434e-01 1.80674955e-01 5.30271649e-01 -6.60063207e-01 -3.33748549e-01 -8.12027454e-01 -6.32867932e-01 6.47121429e-01 5.86292028e-01 1.07717824e+00 -1.05977070e+00 -8.09205174e-01 4.22231495e-01 8.21176022e-02 -6.79840744e-01 -4.15817410e-01 -1.44983605e-02 -1.23409390e+00 -9.86093104e-01 -1.46611130e+00 -1.26645517e+00 7.53526807e-01 -3.65297258e-01 6.61470234e-01 2.54783601e-01 -2.38584742e-01 9.55976918e-02 -3.52805443e-02 -4.34599727e-01 -3.04034829e-01 4.31725457e-02 -2.02948853e-01 -1.90161020e-01 -3.67875211e-02 -4.14539427e-01 -6.66834116e-01 9.82484687e-03 -7.95927644e-01 8.92910808e-02 6.90410852e-01 9.35092449e-01 4.59877342e-01 1.34742096e-01 7.75617957e-01 -5.61543405e-01 9.48454857e-01 -1.89473957e-01 -7.36843348e-01 1.63970500e-01 -8.84353101e-01 3.38084996e-01 6.49316132e-01 -6.45866096e-01 -8.94914329e-01 -2.52602637e-01 -3.36293370e-01 -6.88849926e-01 5.34504354e-01 6.31127656e-01 4.30713892e-01 -3.72634828e-01 4.38155323e-01 1.44963816e-03 1.89795569e-01 -3.14601064e-01 -1.96444262e-02 4.27426964e-01 3.29010248e-01 -2.57871151e-01 -6.22774437e-02 3.30802321e-01 3.68871480e-01 -8.81157637e-01 -5.57319880e-01 1.38954194e-02 -1.63806871e-01 -3.02601099e-01 7.45368898e-01 -5.12675226e-01 -9.11911309e-01 1.21259987e+00 -1.34517062e+00 -2.84497917e-01 -1.96863890e-01 6.37055933e-01 -4.00664151e-01 1.31437674e-01 -9.79811490e-01 -7.47008860e-01 -8.93151164e-01 -1.14446020e+00 4.22145963e-01 4.25832599e-01 1.87383592e-01 -1.14601743e+00 -2.40050122e-01 -3.51601928e-01 6.83435142e-01 4.70666975e-01 1.20513129e+00 -9.08288434e-02 1.06059000e-01 -4.28912193e-01 -3.53552699e-01 6.61241055e-01 1.84286967e-01 -7.39810839e-02 -6.66170955e-01 -2.80678663e-02 4.07145411e-01 1.09828375e-01 8.48359466e-01 9.11968887e-01 9.69096839e-01 -3.12825769e-01 -3.59818041e-01 8.64384949e-01 1.44868279e+00 5.72700918e-01 5.56405008e-01 2.74199933e-01 6.10840142e-01 1.75556362e-01 2.15167001e-01 3.04987997e-01 9.99495834e-02 1.82570040e-01 1.38514996e-01 -1.37129962e-01 -2.21273944e-01 4.99004833e-02 -1.23106897e-01 7.62587249e-01 -2.09937766e-01 3.49137664e-01 -9.52149212e-01 6.22695625e-01 -1.64409149e+00 -5.33966541e-01 -1.94854841e-01 1.93936849e+00 8.97125244e-01 2.45782152e-01 -3.42237294e-01 4.12951559e-01 7.58276284e-01 -2.80907124e-01 -8.29729080e-01 -5.36654353e-01 1.53144807e-01 3.61193091e-01 5.84132373e-01 5.69525480e-01 -9.83450294e-01 5.23127079e-01 6.02897310e+00 9.15517867e-01 -1.70935965e+00 -2.09501125e-02 6.53888881e-01 2.28974104e-01 1.94166154e-01 -5.90206027e-01 -5.20322502e-01 6.13582492e-01 6.38805389e-01 -1.94672048e-02 3.21072489e-01 8.02405596e-01 3.12328547e-01 -1.12993807e-01 -6.71272397e-01 9.35025632e-01 -1.81723997e-01 -1.26394165e+00 -1.71931952e-01 -2.52619565e-01 7.55058527e-01 -2.89975524e-01 1.91362321e-01 1.39635131e-01 -3.22829336e-01 -8.24662745e-01 4.89499897e-01 9.25512135e-01 8.13850939e-01 -9.32119250e-01 9.73151624e-01 1.66163310e-01 -9.97425795e-01 -1.73813552e-01 -3.46812755e-01 -8.33553895e-02 -4.29762714e-02 1.05613065e+00 -8.14926744e-01 3.07370126e-01 5.39440691e-01 5.40689349e-01 -1.41441897e-01 1.21555340e+00 -3.95416617e-02 4.32077169e-01 -4.93960589e-01 -2.81244159e-01 4.00297433e-01 -2.53004491e-01 2.63451397e-01 1.02926886e+00 5.79706013e-01 -5.72713139e-03 -1.59995109e-01 6.74066842e-01 1.07052317e-02 4.48167101e-02 -1.96230635e-01 2.45186388e-02 1.10430643e-02 8.11292589e-01 -6.20453417e-01 -2.46330589e-01 -1.80197671e-01 9.22178745e-01 5.79130277e-02 4.39628184e-01 -9.38889802e-01 -6.94071651e-01 3.51615608e-01 2.47577846e-01 2.68544942e-01 -8.28612000e-02 -5.46841383e-01 -6.01765931e-01 1.82969093e-01 -4.35155094e-01 1.83554888e-01 -5.76597571e-01 -1.06342900e+00 4.63269025e-01 -2.18873933e-01 -1.00096536e+00 -3.84167135e-01 -7.82949746e-01 -4.55609173e-01 1.10062170e+00 -1.56571150e+00 -8.85374248e-01 -1.65424585e-01 4.94804025e-01 2.70957798e-01 -3.87528613e-02 7.26752877e-01 6.44828439e-01 -2.51100898e-01 6.69112980e-01 3.28729481e-01 2.32400313e-01 3.31356734e-01 -8.88983727e-01 -1.58935875e-01 4.52559054e-01 -7.83997238e-01 4.21981037e-01 7.16537297e-01 -6.74677789e-01 -8.26371133e-01 -8.65539014e-01 7.08336055e-01 6.24323368e-01 4.12406623e-01 3.10029835e-01 -1.01378393e+00 2.73742467e-01 -8.22468176e-02 2.85468489e-01 1.10642659e-02 -4.76131707e-01 3.81406784e-01 -3.45964760e-01 -1.53835809e+00 3.35026830e-01 6.39494121e-01 -2.15587050e-01 -2.29351491e-01 1.53847560e-01 6.48481429e-01 -6.43889427e-01 -7.71924198e-01 7.27670968e-01 8.49307537e-01 -7.88462818e-01 7.02457130e-01 -1.93265855e-01 5.12261331e-01 -2.85531841e-02 2.52386034e-01 -1.23069608e+00 -3.67979556e-01 -2.70583957e-01 -3.69242817e-01 8.00726652e-01 3.50732267e-01 -1.01143062e+00 6.94593787e-01 4.67368722e-01 -1.78588197e-01 -1.40045476e+00 -8.53203118e-01 -4.63500500e-01 3.96806061e-01 -1.18606165e-01 2.90481031e-01 7.18788743e-01 -2.59486675e-01 -1.23394899e-01 -1.80288553e-01 -1.97893456e-02 4.32390302e-01 -2.90896952e-01 -7.27753118e-02 -1.24542999e+00 -4.77286652e-02 -6.56208098e-01 -4.45654690e-01 -7.84011006e-01 1.95382219e-02 -6.51070356e-01 -1.48261696e-01 -1.66536152e+00 -5.96851945e-01 -5.45948982e-01 -4.45821971e-01 2.61286110e-01 -1.46835670e-01 -3.90605927e-02 -1.71159133e-01 5.64393913e-03 2.28422895e-01 2.68264890e-01 1.50035286e+00 -2.63057381e-01 -3.97895575e-01 3.02139252e-01 -8.12104270e-02 9.61429954e-01 9.26253021e-01 -1.46250248e-01 -3.94198954e-01 -4.88623589e-01 7.21194297e-02 1.34290144e-01 1.94622517e-01 -1.32055664e+00 4.05546457e-01 3.87353063e-01 7.10714400e-01 -5.69228411e-01 4.38072532e-02 -8.03722441e-01 1.59323722e-01 9.39942181e-01 -2.09556147e-01 -4.03798707e-02 4.46610868e-01 1.01276748e-01 -1.28745362e-01 -4.56612855e-01 1.05571079e+00 -9.98444036e-02 -6.05308294e-01 2.17852443e-01 -1.78623050e-01 -2.46191785e-01 7.94791639e-01 -1.61617458e-01 1.44382954e-01 -1.18933372e-01 -6.43976510e-01 6.50668144e-02 1.82205196e-02 1.48504525e-01 7.74596989e-01 -1.34308338e+00 -5.55970013e-01 3.28720480e-01 -5.19969940e-01 -6.92798349e-04 3.43882799e-01 9.76591706e-01 -1.14573252e+00 4.17225599e-01 -1.76061243e-01 -4.43623453e-01 -6.05455518e-01 4.63148296e-01 1.04268301e+00 -4.97558385e-01 -7.06321001e-01 7.66662478e-01 -1.13820955e-01 -1.18865423e-01 2.74554491e-01 -6.91210508e-01 -2.97388703e-01 8.45633447e-02 4.78313386e-01 7.98465610e-01 1.90736428e-01 -1.61928877e-01 -3.36940855e-01 7.92407274e-01 -6.85972273e-02 -6.11621775e-02 1.31896055e+00 1.85386091e-01 -2.54177183e-01 4.46969271e-01 1.49774313e+00 -3.18265826e-01 -1.23877048e+00 1.38622761e-01 -1.35530919e-01 1.30966172e-01 5.14096260e-01 -8.90514851e-01 -1.46008611e+00 8.14398587e-01 1.28810239e+00 9.12741721e-02 1.30776548e+00 -6.82489216e-01 1.04140151e+00 2.78794318e-02 1.77601963e-01 -1.06595099e+00 -3.18755984e-01 7.17578173e-01 8.44994426e-01 -7.41801322e-01 -1.25452131e-01 -1.80790126e-01 3.21276970e-02 1.43090034e+00 4.15812671e-01 -5.17908573e-01 1.07566690e+00 3.20369184e-01 2.24983677e-01 1.49012133e-01 -1.10826336e-01 2.69184321e-01 1.81811422e-01 2.46778011e-01 6.79402173e-01 -1.63256407e-01 -9.94302392e-01 4.09343332e-01 -6.96805771e-03 7.46471107e-01 1.11147851e-01 9.00271177e-01 -3.40019464e-01 -4.68696684e-01 -2.38405079e-01 5.11286676e-01 -7.09463596e-01 -7.42222071e-02 2.19937146e-01 6.92002475e-01 3.12700450e-01 6.41016364e-01 -5.28259538e-02 7.54179582e-02 3.11922371e-01 1.43206924e-01 5.74409783e-01 1.51596636e-01 -2.63938516e-01 -1.50161624e-01 -4.04539824e-01 -3.82227153e-01 -2.55201936e-01 -2.10375309e-01 -1.68866837e+00 -2.46949583e-01 -2.19706550e-01 1.29000664e-01 8.73109400e-01 9.31097925e-01 1.77161127e-01 9.41555142e-01 4.19790298e-01 -6.91033781e-01 -4.75921154e-01 -1.05135822e+00 -4.75474000e-01 9.32570733e-03 6.72994852e-01 -7.73634255e-01 -4.84882981e-01 -2.29180753e-01]	[7.151516914367676, 3.564427137374878]
46e66172-6786-4f2e-9db5-e8837c65d2dd	learn-spelling-from-teachers-transferring	1907.06017	null	https://arxiv.org/abs/1907.06017v1	https://arxiv.org/pdf/1907.06017v1.pdf	Learn Spelling from Teachers: Transferring Knowledge from Language Models to Sequence-to-Sequence Speech Recognition	Integrating an external language model into a sequence-to-sequence speech recognition system is non-trivial. Previous works utilize linear interpolation or a fusion network to integrate external language models. However, these approaches introduce external components, and increase decoding computation. In this paper, we instead propose a knowledge distillation based training approach to integrating external language models into a sequence-to-sequence model. A recurrent neural network language model, which is trained on large scale external text, generates soft labels to guide the sequence-to-sequence model training. Thus, the language model plays the role of the teacher. This approach does not add any external component to the sequence-to-sequence model during testing. And this approach is flexible to be combined with shallow fusion technique together for decoding. The experiments are conducted on public Chinese datasets AISHELL-1 and CLMAD. Our approach achieves a character error rate of 9.3%, which is relatively reduced by 18.42% compared with the vanilla sequence-to-sequence model.	['Jian-Hua Tao', 'Zhengkun Tian', 'Zhengqi Wen', 'Jiangyan Yi', 'Ye Bai']	2019-07-13	null	null	null	null	['sequence-to-sequence-speech-recognition']	['speech']	[ 5.20347059e-01 4.66247126e-02 -8.58453065e-02 -3.71557176e-01 -8.86704028e-01 -5.09965837e-01 1.79053262e-01 -2.23460704e-01 -6.16750598e-01 9.19965446e-01 4.63993140e-02 -9.09064829e-01 7.95128226e-01 -5.46034873e-01 -7.16031611e-01 -6.05893135e-01 5.77665031e-01 4.07968998e-01 4.36870903e-01 -2.47436300e-01 2.93222219e-01 1.19462512e-01 -1.01371014e+00 5.53538263e-01 1.16373253e+00 5.96529961e-01 7.25803256e-01 1.08061814e+00 -6.78070009e-01 1.11074889e+00 -7.62083471e-01 -2.25136667e-01 -1.56860173e-01 -6.52826250e-01 -5.56690395e-01 -4.19886000e-02 -2.39052862e-01 -2.53484786e-01 -2.12174580e-01 1.01630247e+00 6.37034893e-01 -1.35074602e-02 4.01153892e-01 -6.96718454e-01 -7.19293237e-01 9.50737715e-01 -3.68031889e-01 -8.50137621e-02 4.14733380e-01 5.97143434e-02 4.50109601e-01 -7.57121503e-01 3.26480389e-01 1.22748828e+00 7.41878033e-01 7.02801406e-01 -8.46566677e-01 -6.31700814e-01 2.35611334e-01 1.68156788e-01 -1.40890980e+00 -6.29002273e-01 5.81310332e-01 -2.74148881e-01 1.42095411e+00 2.43816137e-01 2.99281299e-01 9.58311856e-01 -1.52479038e-01 1.01080525e+00 9.99052942e-01 -8.33988547e-01 7.70351291e-02 3.38413179e-01 1.57207876e-01 8.06588173e-01 -2.37891153e-01 -1.71620414e-01 -2.85517752e-01 -7.92719796e-02 5.53410888e-01 -2.64301807e-01 -2.88763970e-01 5.72208226e-01 -7.71012783e-01 5.68611741e-01 -5.53587377e-02 1.03396505e-01 -8.87956098e-02 4.36361544e-02 4.78123128e-01 3.23365837e-01 4.46974158e-01 -1.79970473e-01 -5.72941422e-01 -5.24391055e-01 -1.01465011e+00 -2.48561531e-01 1.02565813e+00 1.06973875e+00 7.95246184e-01 5.74454665e-01 6.33271004e-04 1.04643416e+00 5.43771029e-01 4.17507887e-01 1.02655840e+00 -3.66168946e-01 7.35942662e-01 5.06508529e-01 -2.99007475e-01 -3.85836005e-01 -1.16884047e-02 -4.07013685e-01 -6.39625967e-01 -2.07322851e-01 -8.02326351e-02 -5.44684768e-01 -1.29312885e+00 1.49202776e+00 1.67418301e-01 6.30815387e-01 3.85931730e-01 4.61799949e-01 8.58179212e-01 1.00362265e+00 -9.08018202e-02 -3.97735119e-01 9.97381389e-01 -1.50894666e+00 -8.44251752e-01 -2.32959375e-01 1.16666985e+00 -1.08636868e+00 1.04074204e+00 3.20513934e-01 -1.16797471e+00 -7.93209791e-01 -1.04322088e+00 -7.48066083e-02 -3.36205810e-01 7.27294028e-01 -2.13751271e-01 7.98377275e-01 -1.03535664e+00 2.93866485e-01 -7.46287286e-01 -1.02818571e-01 -1.16636544e-01 3.15275609e-01 -8.75916407e-02 2.61492431e-01 -1.19090009e+00 1.03451765e+00 8.95872116e-01 1.65305763e-01 -8.60854685e-01 -1.76761881e-01 -7.00376511e-01 -6.49132878e-02 2.75016457e-01 -2.81434804e-01 1.50929725e+00 -1.11263359e+00 -2.08282757e+00 3.16454619e-01 -6.41416848e-01 -4.27284837e-01 4.52281684e-01 -1.30433559e-01 -5.76876819e-01 -1.32433638e-01 -2.95380235e-01 3.68613929e-01 5.85453868e-01 -1.14717484e+00 -6.72111452e-01 1.21487550e-01 -2.11084604e-01 2.93517947e-01 -1.43736854e-01 3.21656674e-01 -8.65419865e-01 -7.60368109e-01 9.57083236e-03 -9.13056016e-01 -2.59637177e-01 -7.21823812e-01 -3.92524362e-01 -3.19673717e-01 7.58510053e-01 -1.20218194e+00 1.75216472e+00 -1.84283364e+00 -3.95039693e-02 7.50258788e-02 -2.57734239e-01 9.16117311e-01 -2.20997453e-01 5.95579326e-01 4.88415584e-02 3.62107217e-01 -4.17162776e-01 -5.72550833e-01 -2.16791019e-01 3.50355357e-01 -2.23148316e-01 -3.19181308e-02 2.65391380e-01 8.78933072e-01 -5.58841765e-01 -4.54872578e-01 -2.52713505e-02 4.87619191e-01 -3.57656240e-01 5.31636834e-01 -2.77148187e-01 2.42714226e-01 -3.37303102e-01 5.42084694e-01 6.97392464e-01 5.56094572e-02 2.89114714e-01 3.40236396e-01 -1.18431903e-01 8.22386682e-01 -9.08328176e-01 1.59433126e+00 -4.49333340e-01 3.26738626e-01 2.89102942e-02 -1.04730535e+00 1.28986549e+00 6.43482745e-01 -3.15611750e-01 -4.57240045e-01 1.24425307e-01 4.72462982e-01 1.80924580e-01 -7.15489507e-01 5.84206223e-01 -2.30986178e-01 1.67558461e-01 4.23105061e-01 1.98822599e-02 2.47514412e-01 -2.53589600e-02 4.59618904e-02 8.61246228e-01 6.49403453e-01 2.24359795e-01 2.60340005e-01 9.94918227e-01 -4.15283069e-02 7.82685339e-01 5.84406376e-01 1.90528497e-01 4.50561464e-01 2.36748636e-01 1.87752284e-02 -1.21911108e+00 -6.13922536e-01 2.28412852e-01 9.93285537e-01 -2.74303108e-01 -5.51346064e-01 -1.04956436e+00 -6.46926463e-01 -4.19747055e-01 6.77858949e-01 -2.49478091e-02 -1.48888335e-01 -8.33859503e-01 -5.18241704e-01 1.33900774e+00 6.02376819e-01 4.56473291e-01 -9.84488130e-01 1.61768600e-01 6.74176514e-01 -3.35293710e-01 -1.22023058e+00 -6.60113871e-01 2.56796867e-01 -8.45840335e-01 -3.26863080e-01 -7.39434719e-01 -1.17700982e+00 6.57888532e-01 -1.04691438e-01 7.07701147e-01 4.23058331e-01 1.79425955e-01 -3.47712815e-01 -6.60233736e-01 -1.57128841e-01 -9.75305974e-01 2.72720665e-01 4.30857316e-02 -3.79141979e-02 5.33716977e-01 -3.37926507e-01 -7.68688100e-04 2.96141565e-01 -6.71640635e-01 3.38989049e-01 5.84008515e-01 9.90449786e-01 4.10979331e-01 -4.16312397e-01 7.97121048e-01 -8.94470632e-01 7.27088273e-01 -3.21428984e-01 -4.21392262e-01 6.17704988e-01 -3.84864151e-01 1.72674611e-01 1.02072585e+00 -6.61789060e-01 -1.38547587e+00 3.24937075e-01 -8.10647666e-01 -2.93852538e-01 -2.55414903e-01 8.10447156e-01 -2.71465093e-01 9.24992487e-02 3.61666828e-01 8.23242605e-01 -1.11288898e-01 -8.15066755e-01 1.88299432e-01 1.44737935e+00 4.09161538e-01 -4.83129174e-01 4.83360708e-01 -3.25594515e-01 -7.30642438e-01 -8.54741812e-01 -3.78661841e-01 -4.75973487e-01 -6.66858435e-01 1.34757325e-01 7.17904389e-01 -1.11503768e+00 -6.45585239e-01 5.58738232e-01 -1.35421133e+00 -5.72491109e-01 2.89188206e-01 6.00757957e-01 -3.31202030e-01 8.29810858e-01 -1.01084220e+00 -1.08038282e+00 -4.09248859e-01 -1.44607985e+00 7.95079052e-01 1.84375048e-01 1.22713409e-01 -9.71442521e-01 2.79731536e-03 4.03985947e-01 3.34421694e-01 -4.49219257e-01 6.42748058e-01 -8.87445331e-01 -5.29371560e-01 -1.24710917e-01 1.19603835e-02 7.41200030e-01 3.28697562e-02 3.40617895e-02 -1.03905833e+00 -2.31513381e-01 7.53298849e-02 -4.56510752e-01 8.77707124e-01 -9.77204889e-02 1.08760154e+00 -3.44691753e-01 -2.22033709e-01 5.63610435e-01 1.23653138e+00 7.20238328e-01 8.12475562e-01 5.28098904e-02 8.68023336e-01 2.74331033e-01 2.53219932e-01 2.31461197e-01 5.32648385e-01 6.26382232e-01 -3.88001144e-01 -5.93919307e-02 -3.04426610e-01 -6.21160388e-01 1.00994027e+00 1.93587363e+00 2.07976505e-01 -5.88615596e-01 -9.37343717e-01 3.28549832e-01 -1.74311340e+00 -7.33721852e-01 -1.70073569e-01 1.92024672e+00 1.23702669e+00 2.25905374e-01 -1.53299928e-01 1.30837187e-02 8.00442994e-01 -2.46341079e-01 -4.36616808e-01 -8.63770783e-01 -1.12817541e-01 7.52930492e-02 4.54358071e-01 8.72960508e-01 -6.21011615e-01 1.30539846e+00 6.01029873e+00 1.30862308e+00 -1.39881051e+00 2.39961416e-01 5.27401209e-01 4.41941857e-01 -4.04952347e-01 3.33959550e-01 -1.35534465e+00 7.16257215e-01 1.45158565e+00 7.20702410e-02 4.57342654e-01 4.89399523e-01 3.03679734e-01 1.36341497e-01 -6.78739846e-01 7.82523274e-01 3.07615787e-01 -1.12409508e+00 7.39534199e-02 -2.56514221e-01 4.91390377e-01 2.08900601e-01 -5.03633797e-01 4.63367820e-01 4.48010713e-01 -1.04610825e+00 6.66784286e-01 5.63272655e-01 9.46993470e-01 -6.92837477e-01 8.14014614e-01 9.80772376e-01 -1.26419306e+00 3.36418003e-01 -4.24038142e-01 -1.40081123e-01 5.61568797e-01 2.03008667e-01 -1.28880715e+00 6.54499114e-01 2.19492674e-01 3.70699555e-01 -3.87135029e-01 8.05004060e-01 -3.63094926e-01 1.25291944e+00 -3.47022295e-01 -3.43213707e-01 3.76418889e-01 -1.66536018e-01 1.64954960e-01 1.63383472e+00 4.48627740e-01 2.23870687e-02 5.19146323e-01 4.55562085e-01 -7.45524317e-02 3.67185920e-01 -4.17670250e-01 -2.69188732e-01 5.25659323e-01 9.29086804e-01 -4.27391499e-01 -8.93585086e-01 -4.76524502e-01 1.10549903e+00 4.83077049e-01 3.41346592e-01 -8.59138608e-01 -8.25677574e-01 8.00623000e-02 -2.48890474e-01 3.62888515e-01 -3.89574885e-01 -1.37980968e-01 -1.37497318e+00 3.17669064e-02 -1.11465526e+00 -1.09082729e-01 -9.15790021e-01 -9.59766269e-01 1.00772846e+00 -4.48981345e-01 -1.11292219e+00 -5.66495717e-01 -3.83210808e-01 -6.61493421e-01 1.51084244e+00 -1.63140321e+00 -1.07923889e+00 8.25657919e-02 4.30346251e-01 8.39329004e-01 -4.99782145e-01 7.48706281e-01 4.19730097e-01 -7.40880013e-01 9.63776350e-01 3.60523939e-01 2.94361174e-01 5.36830544e-01 -8.48164678e-01 7.11309731e-01 1.02676904e+00 -6.37939870e-02 7.14008570e-01 1.94478348e-01 -1.02980363e+00 -1.25041175e+00 -9.87531245e-01 1.12117612e+00 -2.72681653e-01 5.49451053e-01 -4.81706351e-01 -1.21226752e+00 7.65923142e-01 3.83298129e-01 -3.21744978e-01 9.07074690e-01 -2.92531013e-01 -6.72420189e-02 2.35503674e-01 -7.98169911e-01 6.13956213e-01 8.58377278e-01 -8.55997503e-01 -7.04632342e-01 -1.45213172e-01 1.17213273e+00 -5.11494517e-01 -6.41852200e-01 2.87121922e-01 4.58204448e-01 -4.61347669e-01 6.29601955e-01 -5.47619224e-01 2.80990243e-01 -6.87050223e-01 -2.02503309e-01 -1.16252983e+00 -9.64131579e-02 -6.76303029e-01 3.53254518e-03 1.45656633e+00 9.03700173e-01 -7.54970014e-01 6.04409218e-01 1.60954267e-01 -5.65996468e-01 -5.46414375e-01 -6.66702569e-01 -7.75122881e-01 1.19684003e-01 -4.70649779e-01 6.35407984e-01 8.02736461e-01 1.57780617e-01 4.79346871e-01 -6.42378330e-01 -1.11938908e-03 1.79924089e-02 -4.07842249e-01 7.06167519e-01 -5.73403895e-01 -6.49139464e-01 -1.16864212e-01 -2.74021993e-03 -1.68907595e+00 2.71647394e-01 -1.14315999e+00 4.31880534e-01 -1.35690451e+00 -8.42486247e-02 -5.32589018e-01 -2.93814093e-01 5.93886971e-01 -2.95752108e-01 9.32331607e-02 1.26815408e-01 8.07895213e-02 -3.16708207e-01 5.64143896e-01 1.07036519e+00 7.02219680e-02 -3.67637277e-01 -5.61430380e-02 -4.34291720e-01 7.16757834e-01 1.13621867e+00 -4.62580979e-01 -4.60807145e-01 -5.86204529e-01 -5.70293963e-02 4.67033893e-01 -3.07821304e-01 -7.60902286e-01 5.86166918e-01 -1.46686718e-01 2.05565318e-01 -9.45320129e-01 3.95256847e-01 -4.02214348e-01 6.78005666e-02 5.38189888e-01 -4.37574595e-01 1.89923719e-01 3.89214516e-01 3.14322263e-01 -3.74908894e-01 -8.18946481e-01 4.65701878e-01 -3.34079117e-01 -6.40769839e-01 -1.16134033e-01 -6.91066980e-01 -1.37674376e-01 7.24815249e-01 -4.66325879e-01 -3.83387744e-01 -3.07877600e-01 -7.33537555e-01 2.19838232e-01 1.73597172e-01 2.84898549e-01 6.49759591e-01 -1.15589559e+00 -7.67311931e-01 5.44641972e-01 -1.05843745e-01 -2.40636066e-01 1.11619316e-01 6.39890432e-01 -7.02175796e-01 4.48433518e-01 2.26819530e-01 -5.12176514e-01 -1.45826769e+00 2.52829134e-01 1.44409657e-01 -2.35767841e-01 -2.69661874e-01 9.40198898e-01 -1.06675863e-01 -1.00964296e+00 3.49667370e-01 -2.97144055e-01 -2.06774220e-01 -3.17939281e-01 5.74348211e-01 1.24651179e-01 9.31429341e-02 -7.93796659e-01 -2.86800593e-01 5.02521694e-01 -2.58558005e-01 -3.78450572e-01 1.03178358e+00 -2.88286388e-01 -1.21964596e-01 6.14667058e-01 1.17283130e+00 1.30597219e-01 -8.63219798e-01 -3.83931369e-01 1.60419717e-01 -2.40577105e-02 -1.75712734e-01 -1.01951313e+00 -6.80563450e-01 1.26570237e+00 3.56161684e-01 -8.74837041e-02 1.06926346e+00 -4.01017725e-01 1.06509721e+00 5.02966285e-01 -1.74830842e-03 -1.25229490e+00 -2.54812598e-01 1.12466931e+00 5.69447339e-01 -1.06113327e+00 -4.33930874e-01 -2.56413221e-01 -7.84583986e-01 1.14611936e+00 7.60347545e-01 1.31379545e-01 4.76908267e-01 6.84153020e-01 2.39466980e-01 7.29158223e-01 -1.20741892e+00 -1.99062288e-01 3.13920453e-02 3.49869072e-01 6.92738056e-01 2.12187275e-01 -4.05266523e-01 5.00589788e-01 -2.05030426e-01 3.42539251e-01 6.55649364e-01 9.67802346e-01 -7.07435071e-01 -1.71461797e+00 -3.75104517e-01 2.74873167e-01 -4.27757084e-01 -6.19484186e-01 -1.40419677e-01 1.65256150e-02 1.81431293e-01 1.14668071e+00 3.99457887e-02 -7.05371916e-01 -5.25348708e-02 5.95966756e-01 7.52848461e-02 -7.40253985e-01 -7.45200813e-01 6.39252901e-01 4.86071467e-01 5.48671521e-02 -1.44709006e-01 -3.41410816e-01 -1.55904114e+00 -2.07669303e-01 -7.35037923e-01 3.00475776e-01 8.37310076e-01 9.20122027e-01 3.26420754e-01 5.99218965e-01 5.51142335e-01 -3.85217100e-01 -5.44857800e-01 -1.21316826e+00 -1.49474248e-01 -1.32546410e-01 2.96682090e-01 1.98238473e-02 -1.22888260e-01 1.94290712e-01]	[14.447226524353027, 7.015989780426025]
14d90ddc-dff7-4c12-82e9-9e510beda458	efficient-machine-translation-corpus-1	2306.11838	null	https://arxiv.org/abs/2306.11838v1	https://arxiv.org/pdf/2306.11838v1.pdf	Efficient Machine Translation Corpus Generation	This paper proposes an efficient and semi-automated method for human-in-the-loop post-editing for machine translation (MT) corpus generation. The method is based on online training of a custom MT quality estimation metric on-the-fly as linguists perform post-edits. The online estimator is used to prioritize worse hypotheses for post-editing, and auto-close best hypotheses without post-editing. This way, significant improvements can be achieved in the resulting quality of post-edits at a lower cost due to reduced human involvement. The trained estimator can also provide an online sanity check mechanism for post-edits and remove the need for additional linguists to review them or work on the same hypotheses. In this paper, the effect of prioritizing with the proposed method on the resulting MT corpus quality is presented versus scheduling hypotheses randomly. As demonstrated by experiments, the proposed method improves the lifecycle of MT models by focusing the linguist effort on production samples and hypotheses, which matter most for expanding MT corpora to be used for re-training them.	['Hassan Sawaf', 'Shreyas Sharma', 'Ahmet Gunduz', 'Kamer Ali Yuksel']	2023-06-20	efficient-machine-translation-corpus	https://aclanthology.org/2022.amta-coco4mt.2	https://aclanthology.org/2022.amta-coco4mt.2.pdf	amta-2022-9	['machine-translation']	['natural-language-processing']	[ 3.82391989e-01 7.29318619e-01 -4.99338843e-02 -4.12496120e-01 -9.84058261e-01 -7.07667112e-01 5.55403709e-01 4.71953928e-01 -5.41927874e-01 9.47255373e-01 -1.01588055e-01 -4.45303321e-01 2.14412019e-01 -4.88211513e-01 -7.56955564e-01 -4.11623389e-01 3.24355155e-01 9.62776184e-01 1.23526484e-01 -2.43066847e-01 5.05567312e-01 2.50508547e-01 -1.55412281e+00 1.33232057e-01 1.58002269e+00 3.19854498e-01 1.08249748e+00 5.78843594e-01 -2.12498859e-01 1.62645310e-01 -8.62396359e-01 -7.74297833e-01 3.91532779e-01 -6.56770945e-01 -5.97168863e-01 1.94111750e-01 3.15712124e-01 -1.49901256e-01 1.94992170e-01 9.46112335e-01 5.68725467e-01 2.50693988e-02 5.43758571e-01 -9.77580369e-01 -3.12247157e-01 1.06584394e+00 -2.70640731e-01 2.74598170e-02 2.82712340e-01 6.90441504e-02 8.11326087e-01 -9.39265370e-01 8.66452754e-01 1.19928575e+00 1.91997364e-01 3.79986376e-01 -9.52865899e-01 -3.73186529e-01 -1.83367521e-01 3.09670627e-01 -1.06512618e+00 -7.46380925e-01 3.75309587e-01 -3.65585595e-01 9.57051158e-01 2.74221659e-01 3.68442118e-01 4.84285861e-01 5.12320638e-01 4.61029828e-01 9.88215983e-01 -1.13430119e+00 1.18041612e-01 5.56112289e-01 -2.85298854e-01 6.24796689e-01 4.27093089e-01 -1.73045635e-01 -5.30926645e-01 9.83062163e-02 3.82558197e-01 -5.47826350e-01 -9.83466133e-02 -8.76474008e-02 -1.19169533e+00 5.23787022e-01 -3.02545696e-01 4.46555734e-01 -6.04237616e-01 -3.33277106e-01 4.39058661e-01 5.54315269e-01 5.91879189e-01 5.37234366e-01 -5.43083906e-01 -4.56170410e-01 -1.29658723e+00 1.42272696e-01 6.82148695e-01 1.23821390e+00 9.39009726e-01 -2.95492679e-01 -3.05748403e-01 1.05607402e+00 7.18649030e-02 6.99121237e-01 6.95936084e-01 -5.26220083e-01 9.06772614e-01 6.34298325e-01 2.79231608e-01 -6.59112990e-01 1.10282883e-01 -4.43674326e-01 -3.11519891e-01 2.55076289e-02 1.59879342e-01 -2.02736601e-01 -8.52078378e-01 1.36946964e+00 4.92637694e-01 -5.14382899e-01 -1.88184991e-01 6.16159678e-01 7.60432216e-04 7.74983585e-01 -2.08566844e-01 -7.53578961e-01 1.30326903e+00 -1.12703598e+00 -1.08383703e+00 -1.54294670e-01 9.45462525e-01 -1.54326606e+00 1.07265151e+00 4.21402991e-01 -1.33539867e+00 -7.21246064e-01 -9.62043822e-01 5.10044731e-02 -1.52640626e-01 6.52253330e-01 6.34524152e-02 5.40075779e-01 -8.92298281e-01 1.01418829e+00 -8.07753623e-01 -5.66970706e-01 -2.48474255e-01 3.97233754e-01 -7.14911371e-02 5.59087805e-02 -1.01829016e+00 1.35131288e+00 4.15449500e-01 2.87519246e-01 -5.69598317e-01 -4.71375227e-01 -6.73365116e-01 1.71647519e-02 2.04643637e-01 -4.06136930e-01 1.62150323e+00 -1.24456334e+00 -1.90232766e+00 4.54757690e-01 -6.23678684e-01 -2.53641933e-01 9.25260127e-01 -2.57931113e-01 -3.19497555e-01 -8.22972730e-02 3.97045165e-01 6.09233558e-01 8.37431729e-01 -1.00787103e+00 -1.05152202e+00 9.68887098e-03 -2.11439192e-01 4.89944726e-01 -2.62671798e-01 1.25719577e-01 -4.67389643e-01 -6.05124652e-01 6.26515374e-02 -1.10472000e+00 2.22934373e-02 -5.40277600e-01 -2.23108426e-01 -2.84745663e-01 6.65959835e-01 -1.11112320e+00 1.43733299e+00 -1.64542747e+00 1.55669153e-01 1.27436280e-01 -2.25495592e-01 4.20632958e-01 -2.27402210e-01 7.48323143e-01 3.15768778e-01 1.41637117e-01 -2.76655126e-02 -4.55813438e-01 -1.43553510e-01 -3.45918126e-02 5.81466518e-02 1.71875879e-01 2.50131577e-01 5.62750340e-01 -9.38699663e-01 -8.29962313e-01 1.01064675e-01 -1.07882306e-01 -2.68196940e-01 4.40792143e-01 -4.00468081e-01 2.41227522e-01 -4.37161177e-02 3.32757384e-01 6.67962134e-01 3.31730962e-01 4.57324564e-01 3.74377221e-02 -3.72372359e-01 6.89339221e-01 -9.93402541e-01 1.51882648e+00 -9.14948046e-01 7.71410525e-01 -1.02255836e-01 -6.89458132e-01 1.01556981e+00 4.92361248e-01 -1.94639675e-02 -6.58452630e-01 1.22036405e-01 5.13739169e-01 2.78799236e-01 -4.18956339e-01 9.45191979e-01 2.69458860e-01 2.06755042e-01 8.21396887e-01 -1.23513311e-01 -1.06880456e-01 9.11258817e-01 1.97799429e-01 5.76802671e-01 5.33614099e-01 1.89295202e-01 -3.54089916e-01 6.63084269e-01 2.10467264e-01 5.99132776e-01 4.45798874e-01 9.49610844e-02 -6.56786859e-02 1.04286000e-02 8.45108181e-03 -1.50212693e+00 -5.63892901e-01 1.60534978e-01 1.02055836e+00 -7.48404786e-02 -3.73976827e-01 -1.19220293e+00 -7.33214557e-01 -4.11350250e-01 1.09662187e+00 -2.31625915e-01 4.11470830e-02 -8.38545144e-01 -1.03338018e-01 2.40596071e-01 -8.87012109e-02 1.85399905e-01 -1.18928277e+00 -6.26019061e-01 5.28360426e-01 -6.59513831e-01 -6.95168078e-01 -8.07578623e-01 1.34176701e-01 -1.05141819e+00 -5.85476995e-01 -8.13831210e-01 -1.02082837e+00 1.01667225e+00 2.53435880e-01 7.47913241e-01 1.18404739e-01 1.52466133e-01 -3.92012358e-01 -5.83025455e-01 -4.33183819e-01 -1.26929677e+00 3.87063712e-01 2.19955355e-01 -3.30232456e-02 3.61018740e-02 -3.12437177e-01 -2.71609843e-01 5.70670009e-01 -5.36692679e-01 4.29913282e-01 7.77048588e-01 8.18314135e-01 6.34789288e-01 -4.03238684e-02 7.17661202e-01 -9.04652357e-01 7.99637258e-01 -5.54887615e-02 -8.47952127e-01 6.99602842e-01 -9.81853545e-01 4.12215114e-01 9.24103260e-01 -4.54243481e-01 -1.36829472e+00 -6.42209575e-02 3.18580627e-01 -1.40358895e-01 1.74956247e-01 5.20701647e-01 -1.22514419e-01 1.73825547e-01 4.48338121e-01 2.84426361e-01 -5.71330748e-02 -6.53791666e-01 2.75077969e-01 1.12241900e+00 1.34312689e-01 -4.05164152e-01 7.88038969e-01 -3.85709077e-01 -2.11458802e-01 -5.23467124e-01 -2.96585709e-01 -3.38129878e-01 -7.87913144e-01 -2.86175102e-01 4.39958364e-01 -6.25163555e-01 -1.79807529e-01 1.77028447e-01 -1.30351543e+00 -2.64768571e-01 1.62011907e-01 4.74781305e-01 -5.00814855e-01 6.68850362e-01 -4.62655097e-01 -9.65500236e-01 -5.57341754e-01 -1.28556824e+00 8.69586408e-01 2.38422707e-01 -4.91309196e-01 -6.99139178e-01 8.55721012e-02 5.00751257e-01 2.26168036e-01 -3.52566510e-01 9.22056437e-01 -5.16164839e-01 -6.18195117e-01 -1.66818395e-01 1.95245489e-01 3.01958829e-01 2.13940516e-01 2.66471237e-01 -5.26223421e-01 -3.71137619e-01 -2.62378782e-01 -3.35267782e-02 1.06815711e-01 2.17152700e-01 4.37184364e-01 -4.88030761e-01 -4.04609680e-01 1.00197017e-01 1.06324553e+00 3.53162259e-01 5.56879580e-01 4.26266521e-01 3.48090023e-01 8.34171593e-01 1.43071830e+00 3.50887090e-01 2.52150089e-01 9.34161782e-01 -7.92501047e-02 5.95568009e-02 -4.00798656e-02 -3.44649911e-01 7.58181393e-01 1.55610883e+00 1.71518460e-01 -4.78294700e-01 -6.48592710e-01 7.28429496e-01 -1.87265778e+00 -6.52493954e-01 -2.02646509e-01 2.49880099e+00 1.06836832e+00 1.65964574e-01 -3.80887575e-02 4.50697029e-03 1.26957369e+00 -4.57043469e-01 -9.85677615e-02 -9.27569807e-01 2.20968530e-01 2.35748559e-01 4.69064504e-01 8.36579621e-01 -4.30823088e-01 1.35414875e+00 5.11463070e+00 9.47899103e-01 -1.11480880e+00 1.85312748e-01 4.03647482e-01 -1.01837672e-01 -3.29778135e-01 4.22184706e-01 -9.22906399e-01 5.37565291e-01 1.17638791e+00 -4.84609246e-01 5.62148035e-01 7.63430834e-01 8.82466793e-01 -3.27670932e-01 -1.17284107e+00 5.78137934e-01 -4.44133617e-02 -1.11444581e+00 2.50351012e-01 1.56948388e-01 6.85067296e-01 -2.75610864e-01 -5.64544737e-01 2.10095271e-01 -6.09560050e-02 -2.76611388e-01 1.11393249e+00 3.22913140e-01 7.63328016e-01 -9.50689673e-01 8.54930460e-01 6.24031365e-01 -9.24665034e-01 2.43948862e-01 -5.98669946e-01 9.24305469e-02 4.03025746e-01 7.19031096e-01 -1.54363704e+00 8.19183350e-01 9.86567810e-02 5.43808676e-02 -5.14058709e-01 8.77123296e-01 -3.61773729e-01 6.36133671e-01 -2.21608371e-01 -4.12393570e-01 -1.30279604e-02 -3.83097470e-01 5.04711807e-01 1.43517959e+00 6.52374506e-01 -2.23107412e-01 8.30091834e-02 6.30795777e-01 6.01491779e-02 6.74708605e-01 -1.70741484e-01 -3.18957657e-01 8.97286713e-01 1.31651032e+00 -7.08013475e-01 -6.10230207e-01 2.69679934e-01 1.19293272e+00 2.89654702e-01 -5.40374517e-02 -7.79608548e-01 -8.54480505e-01 2.91480571e-02 3.65373939e-01 3.62271577e-01 -1.31614506e-01 -3.19358438e-01 -8.38798523e-01 3.53728175e-01 -1.17301440e+00 -1.35949746e-01 -6.58697605e-01 -5.47355533e-01 7.85151601e-01 -1.98367894e-01 -1.28723574e+00 -5.19624174e-01 -1.12769641e-01 -4.47525442e-01 1.17090321e+00 -1.18340302e+00 -7.45412707e-01 1.72454044e-01 6.78185448e-02 9.62932944e-01 -2.27974147e-01 4.62425232e-01 3.38916034e-01 -5.10819912e-01 9.54090834e-01 1.05647385e-01 -4.51988548e-01 1.02312648e+00 -9.93401349e-01 3.62159580e-01 1.24054062e+00 6.36933595e-02 7.32896388e-01 7.80731618e-01 -1.24248183e+00 -1.08077216e+00 -9.97503698e-01 1.86325753e+00 -1.13776684e-01 3.46179634e-01 -5.03299832e-01 -4.81258839e-01 2.41273776e-01 5.02613902e-01 -9.82740641e-01 2.06556678e-01 3.03553585e-02 3.75279099e-01 -1.09554350e-01 -1.05939269e+00 7.46826828e-01 6.83277845e-01 -2.18098566e-01 -6.20008051e-01 5.48620641e-01 6.99014366e-01 -2.55974770e-01 -6.97067380e-01 -1.92157477e-02 3.36754769e-01 -4.68065649e-01 5.03420196e-02 -7.70717189e-02 5.66811264e-01 -4.34985995e-01 4.04335469e-01 -1.63283432e+00 -3.12422514e-01 -1.19186544e+00 2.67176807e-01 1.40538275e+00 9.29858923e-01 -4.24143255e-01 3.96299899e-01 2.32416138e-01 -4.65669692e-01 -5.64777315e-01 -8.87072086e-01 -8.07785869e-01 -4.16451633e-01 1.46133915e-01 4.37645882e-01 7.01805234e-01 2.07999587e-01 4.06563550e-01 -3.20665777e-01 4.20872681e-03 4.86519039e-01 -1.89747602e-01 1.01849866e+00 -8.94589305e-01 -4.99311328e-01 -1.42095387e-01 3.30572985e-02 -9.81289625e-01 -2.33655646e-01 -8.04037571e-01 5.35390615e-01 -1.45426738e+00 2.48531215e-02 -3.38053524e-01 1.27994180e-01 3.76418263e-01 -4.53157276e-01 -2.94690073e-01 3.85927022e-01 3.90612990e-01 -2.75567353e-01 3.71746957e-01 1.47196758e+00 2.21405983e-01 -3.93193424e-01 1.30700935e-02 -2.08341911e-01 2.10436925e-01 7.85626292e-01 -8.63629103e-01 -4.83425498e-01 -4.94677722e-01 5.40725840e-03 1.52440473e-01 -4.00490075e-01 -7.24209368e-01 1.69874296e-01 -1.64732054e-01 -1.09963357e-01 -8.50928426e-01 -1.36004567e-01 -5.52539945e-01 2.32687354e-01 4.93428051e-01 -3.53351444e-01 6.42010808e-01 1.22232147e-01 2.14071065e-01 -1.68003347e-02 -7.82470167e-01 6.64341807e-01 -9.47471615e-03 -1.30842224e-01 -1.90234572e-01 -5.97790301e-01 -2.24768817e-01 8.95948470e-01 -5.17299652e-01 -4.80037509e-03 -3.52873564e-01 -3.75698030e-01 1.68786541e-01 4.65396076e-01 3.45912516e-01 -7.37791508e-02 -8.92713904e-01 -7.94503868e-01 -8.56452137e-02 2.26064678e-03 -3.29949230e-01 -2.02380177e-02 7.15141773e-01 -7.25916386e-01 5.94702184e-01 -2.00493306e-01 -5.19442379e-01 -1.35817111e+00 2.03964427e-01 -4.79101427e-02 -6.93897486e-01 -2.06734404e-01 6.20805681e-01 -2.86982358e-01 -4.34418708e-01 1.57884240e-01 -2.34210089e-01 1.35760680e-01 4.63939365e-03 2.64900476e-01 4.94381875e-01 5.08143246e-01 -2.72878230e-01 -1.63916484e-01 8.98888931e-02 -6.04073822e-01 -7.04978943e-01 1.04763567e+00 -5.32512188e-01 -1.20690167e-01 4.78441805e-01 6.25387549e-01 4.21303600e-01 -9.57541883e-01 -2.34966315e-02 2.53958434e-01 -4.43700969e-01 -2.10890416e-02 -1.26141036e+00 -4.48354781e-01 6.73941910e-01 4.80507672e-01 -6.40347973e-02 8.14196825e-01 -4.35942054e-01 9.15446222e-01 5.33830702e-01 4.65370536e-01 -1.75943899e+00 -3.59684497e-01 5.53864539e-01 7.57007957e-01 -8.78316522e-01 -8.92713368e-02 -5.04305422e-01 -6.69809818e-01 1.14193833e+00 6.00000024e-01 3.12401026e-01 -3.24480347e-02 -9.52511132e-02 2.71123201e-01 3.49685878e-01 -9.38527405e-01 2.45789841e-01 8.08448270e-02 4.43178207e-01 7.89746881e-01 2.90161878e-01 -1.08386588e+00 6.20123148e-02 -4.99460578e-01 -1.74791198e-02 7.25520790e-01 8.45129073e-01 -6.18938565e-01 -1.67513037e+00 -2.61917025e-01 3.14146817e-01 -1.49531856e-01 -3.59569579e-01 -5.25321305e-01 5.55907369e-01 2.59246558e-01 1.17392433e+00 -8.90562907e-02 -2.50801533e-01 2.20057845e-01 2.05809981e-01 6.49926901e-01 -8.52180898e-01 -9.41037059e-01 4.07775521e-01 6.58346534e-01 -7.38506392e-02 -2.24035769e-03 -8.25814545e-01 -9.63910222e-01 -3.40541124e-01 -9.93327379e-01 6.71449244e-01 1.14700484e+00 1.03181589e+00 7.04210162e-01 2.72793561e-01 8.80979478e-01 -7.81761706e-01 -9.13151443e-01 -1.46307302e+00 -2.30739359e-02 3.14605862e-01 -3.34402651e-01 -5.37171423e-01 -2.58637697e-01 3.61842126e-01]	[11.685892105102539, 10.258333206176758]
09ba7aef-d999-482a-95d1-9e53a3b9ee7d	coded-illumination-and-imaging-for	null	null	http://openaccess.thecvf.com/content_ECCV_2018/html/Yuta_Asano_Coded_Illumination_and_ECCV_2018_paper.html	http://openaccess.thecvf.com/content_ECCV_2018/papers/Yuta_Asano_Coded_Illumination_and_ECCV_2018_paper.pdf	Coded Illumination and Imaging for Fluorescence Based Classification	The quick detection of specific substances in objects such as produce items via non-destructive visual cues is vital to ensuring the quality and safety of consumer products. At the same time, it is well-known that the fluorescence excitation-emission characteristics of many organic objects can serve as a kind of ``fingerprint'' for detecting the presence of specific substances in classification tasks such as determining if something is safe to consume. However, conventional capture of the fluorescence excitation-emission matrix can take on the order of minutes and can only be done for point measurements. In this paper, we propose a coded illumination approach whereby light spectra are learned such that key visual fluorescent features can be easily seen for material classification. We show that under a single coded illuminant, we can capture one RGB image and perform pixel-level classifications of materials at high accuracy. This is demonstrated through effective classification of different types of honey and alcohol using real images.	['Misaki Meguro', 'Yinqiang Zheng', 'Chao Wang', 'Yuta Asano', 'Takahiro Okabe', 'Imari Sato', 'Antony Lam']	2018-09-01	null	null	null	eccv-2018-9	['material-classification']	['computer-vision']	[ 9.03610647e-01 -4.85732704e-01 -2.63270706e-01 -3.39659274e-01 -4.71579552e-01 -1.14107358e+00 2.86557704e-01 5.05339026e-01 -1.58633307e-01 5.65066218e-01 -5.23305357e-01 -9.47133377e-02 8.68127272e-02 -8.43530953e-01 -6.59095168e-01 -1.15532339e+00 2.66652316e-01 -2.31960509e-02 6.50691846e-03 1.53056681e-01 3.17852944e-01 7.79649794e-01 -1.76171279e+00 5.42480111e-01 5.21763384e-01 1.33884060e+00 3.58871222e-01 6.21374786e-01 -1.66058943e-01 3.93223047e-01 -5.38856566e-01 -9.12613720e-02 2.42206395e-01 -4.66196746e-01 -3.07484776e-01 3.59224528e-01 3.62261891e-01 -2.15381876e-01 2.73741424e-01 1.34435284e+00 1.09976426e-01 -8.00226852e-02 7.28375733e-01 -8.66967857e-01 -6.57550693e-01 2.03958005e-02 -4.78268176e-01 -1.40030995e-01 6.70468569e-01 4.13471609e-01 8.86591375e-01 -6.55585229e-01 4.39069420e-01 8.82672608e-01 2.25111306e-01 4.48435187e-01 -1.55760157e+00 -5.66603065e-01 -1.96295574e-01 1.81130543e-01 -8.88246417e-01 -2.89414674e-01 1.00289559e+00 -2.95757145e-01 4.55495149e-01 3.79206598e-01 8.73666286e-01 8.45155597e-01 4.42677259e-01 6.43194854e-01 1.80915606e+00 -4.52938706e-01 4.43530858e-01 4.10538971e-01 -1.72266848e-02 8.92295957e-01 4.15342718e-01 2.66534299e-01 -3.86891544e-01 1.94709152e-01 3.36623251e-01 4.03852552e-01 -4.11476642e-01 -2.76974201e-01 -9.69873130e-01 5.78101158e-01 6.49725974e-01 1.18192084e-01 -4.19758648e-01 -9.30385888e-02 4.32443507e-02 1.94126487e-01 2.17870831e-01 6.77205086e-01 -2.99338605e-02 3.98969539e-02 -5.41514039e-01 -3.33734035e-01 6.05612993e-01 3.96738648e-01 1.03362465e+00 -3.80492419e-01 2.75666893e-01 7.08918750e-01 2.60607809e-01 1.07388592e+00 6.62124231e-02 -8.82641912e-01 -3.60145539e-01 8.06169152e-01 3.99257511e-01 -9.89927709e-01 -3.63189906e-01 -1.52512819e-01 -4.52755421e-01 7.84265876e-01 7.35608757e-01 1.01997159e-01 -7.23734438e-01 1.10724127e+00 5.60761511e-01 -1.68225259e-01 -1.32541656e-01 9.08238351e-01 5.38681269e-01 6.09255254e-01 -2.03548118e-01 -4.07282263e-01 1.47126615e+00 -3.22972357e-01 -6.94966257e-01 -1.11329116e-01 2.83609748e-01 -8.71328831e-01 1.30986333e+00 8.60437095e-01 -8.17973793e-01 -4.21252191e-01 -1.39180350e+00 1.06661253e-01 -7.71931827e-01 3.77090946e-02 8.38770330e-01 9.45817471e-01 -2.73202837e-01 5.19868731e-01 -6.66143119e-01 -1.41203642e-01 4.71952856e-01 3.10117155e-01 -3.76437366e-01 -4.48507160e-01 -4.63706225e-01 6.03525877e-01 -2.13542357e-02 3.21586132e-01 -7.05362022e-01 -6.43180072e-01 -4.31538194e-01 -2.67119825e-01 3.09949875e-01 3.80166732e-02 8.31473708e-01 -1.24733758e+00 -1.84621990e+00 9.93905544e-01 -1.36259064e-01 9.07848254e-02 1.47149101e-01 -1.49860635e-01 -3.26973647e-01 5.86635113e-01 -2.12327227e-01 3.19543898e-01 9.64390576e-01 -1.50062954e+00 -5.70051372e-01 -5.82213223e-01 3.27170104e-01 -1.89286634e-01 -1.99118018e-01 -7.27694258e-02 2.52019167e-01 -3.38226408e-02 1.42960623e-01 -9.83722448e-01 1.46857768e-01 5.30323923e-01 -3.38667214e-01 1.24458686e-01 9.76608992e-01 -3.51157367e-01 5.96984148e-01 -2.16282129e+00 -4.52973723e-01 2.95988292e-01 4.40361947e-02 3.52510124e-01 -1.68438312e-02 2.10406303e-01 1.51330322e-01 -1.79909497e-01 -1.16023339e-01 5.11583090e-01 -2.96728879e-01 -6.44805878e-02 1.94107350e-02 8.71564448e-01 3.97397518e-01 7.80521512e-01 -1.14614594e+00 -1.19431354e-01 5.54183125e-01 7.12547362e-01 -6.79391176e-02 7.59455413e-02 -3.05864871e-01 3.43209952e-01 -2.70812243e-01 1.04410076e+00 6.74743712e-01 -2.11975753e-01 1.50931790e-01 -6.74376428e-01 -9.11433622e-02 1.78736225e-01 -1.05541003e+00 1.23446155e+00 -4.86040264e-01 7.53003418e-01 2.69144714e-01 -6.16257846e-01 8.62544239e-01 -8.58063158e-03 4.56873953e-01 -9.65002954e-01 2.51113325e-01 2.66462475e-01 -6.90059550e-03 -4.84864682e-01 1.60621911e-01 -3.06353748e-01 2.15125665e-01 6.17021561e-01 -5.04286051e-01 -2.46379375e-01 1.58948138e-01 -3.96341801e-01 7.64100909e-01 1.04260564e-01 1.83297068e-01 -1.83597401e-01 3.01987231e-01 -2.63255611e-02 1.06293350e-01 3.94381225e-01 -6.83024228e-02 2.90971160e-01 1.73371151e-01 -2.71013170e-01 -7.31504202e-01 -1.16480923e+00 -2.78081179e-01 8.03188920e-01 4.37144667e-01 7.38382414e-02 -6.15494311e-01 -3.79793972e-01 2.26166964e-01 4.32212949e-01 -7.12544858e-01 -2.15562865e-01 -1.18573330e-01 -6.46762967e-01 -3.71195190e-02 3.22854578e-01 4.04377550e-01 -9.01437461e-01 -1.13189960e+00 2.09568128e-01 1.84062332e-01 -9.38131571e-01 2.03930587e-02 6.28072977e-01 -6.09973371e-01 -1.47587895e+00 -2.34678045e-01 -5.10010898e-01 7.83610761e-01 8.31637979e-01 7.92974353e-01 -6.02897676e-03 -8.00132632e-01 4.48766351e-01 -4.19362634e-01 -5.53968906e-01 -3.39897811e-01 -4.94983613e-01 -2.59372979e-01 4.59709495e-01 5.73368311e-01 -2.41624147e-01 -9.58354056e-01 2.59812802e-01 -8.71482313e-01 -1.76934570e-01 5.61901867e-01 6.93189800e-01 8.48125458e-01 2.18630761e-01 1.46525323e-01 -9.85893309e-01 3.00476789e-01 -8.24576914e-02 -6.66641176e-01 3.64917606e-01 -4.15586203e-01 -2.25849841e-02 6.82181418e-01 -5.15972257e-01 -9.89448190e-01 2.84557045e-01 3.80399346e-01 7.36939721e-03 -3.99042666e-01 1.77121654e-01 -1.97863191e-01 -3.97981972e-01 6.95659637e-01 7.23685622e-02 3.30073610e-02 -2.23206013e-01 3.69234741e-01 7.77368844e-01 3.57454866e-01 -4.66019958e-01 5.59237421e-01 9.24422145e-01 3.97565573e-01 -1.20890987e+00 -7.75870919e-01 -6.76489651e-01 -7.28707790e-01 -6.03394449e-01 7.34676719e-01 -5.14942586e-01 -1.25861061e+00 4.08124179e-01 -7.12936223e-01 -2.51017481e-01 -1.08258307e-01 5.05960703e-01 -2.93306857e-01 2.05531314e-01 -3.71902555e-01 -1.06650758e+00 -1.11395635e-01 -9.81342554e-01 1.12516201e+00 2.20052898e-01 -5.13315350e-02 -9.94453490e-01 -2.70604968e-01 2.38909423e-01 1.10425204e-01 6.01706326e-01 9.45531905e-01 2.56685436e-01 -5.67032576e-01 -4.77708399e-01 -2.91592777e-01 3.03297907e-01 6.42143071e-01 2.88946480e-01 -1.26612151e+00 -1.83771223e-01 1.51444674e-01 -3.86818349e-01 7.33713031e-01 3.28876942e-01 1.02678287e+00 -6.20957352e-02 -3.31750542e-01 6.06299698e-01 1.70546377e+00 4.65957463e-01 6.22857511e-01 1.58880591e-01 5.95102966e-01 8.06953251e-01 1.00644791e+00 1.46699414e-01 -4.37436253e-01 5.78435838e-01 6.91478133e-01 -4.04423684e-01 -1.99222684e-01 1.98160410e-01 4.23264444e-01 2.71791458e-01 -1.65512741e-01 -2.49657303e-01 -3.37653816e-01 9.42012146e-02 -1.12807357e+00 -9.16683853e-01 -4.57317710e-01 2.29504800e+00 7.92848468e-01 -1.27366349e-01 1.27256423e-01 4.26656127e-01 6.50884807e-01 -2.33301193e-01 -6.63886666e-01 -2.70657897e-01 -2.35067219e-01 4.70639169e-01 6.32683873e-01 3.24768156e-01 -9.38510239e-01 4.20756936e-01 6.55426645e+00 3.24234366e-01 -1.66857386e+00 -1.87216699e-01 4.36058670e-01 -1.60867199e-01 -2.69105375e-01 -3.11678469e-01 -5.04267335e-01 5.58127105e-01 5.88626444e-01 4.27663684e-01 5.45650184e-01 4.62945998e-01 1.90103292e-01 -6.46525145e-01 -1.13348353e+00 1.24617064e+00 4.71716188e-02 -8.71733606e-01 -2.59708643e-01 1.60529613e-01 5.79913855e-01 -4.40316230e-01 3.54363143e-01 -7.56529748e-01 1.01098984e-01 -8.39304030e-01 6.16481543e-01 4.96665657e-01 7.68945456e-01 -6.76675677e-01 4.19631451e-01 -5.66557720e-02 -9.87424970e-01 -2.97050714e-01 -3.08501691e-01 6.55727684e-02 -1.04039393e-01 8.46443772e-01 -9.18053210e-01 1.06529765e-01 5.42457163e-01 7.03705966e-01 -4.57420439e-01 9.99284387e-01 -3.35011154e-01 4.76289362e-01 -4.45786148e-01 -4.22746271e-01 1.93273395e-01 -5.91496587e-01 5.89980967e-02 1.01142442e+00 4.09521520e-01 1.63808107e-01 -2.48246584e-02 9.40253675e-01 5.62168956e-02 -1.33924950e-02 -5.83006799e-01 -4.21303242e-01 1.86215952e-01 1.53945935e+00 -1.25090170e+00 1.16257846e-01 -4.36529666e-01 1.02420485e+00 -9.10018086e-02 2.61242986e-01 -4.65710044e-01 -4.13302749e-01 4.66355443e-01 2.48894185e-01 2.59844631e-01 -3.01828206e-01 -2.11872265e-01 -7.72201478e-01 -7.96055794e-02 -6.94360197e-01 -6.43201023e-02 -9.73685503e-01 -1.23393035e+00 -4.26117796e-03 -5.33252537e-01 -1.20373869e+00 3.92461896e-01 -1.39602613e+00 -1.90330222e-01 3.91965479e-01 -1.67436552e+00 -1.06318462e+00 -5.24387538e-01 6.04651809e-01 8.88363793e-02 3.70989084e-01 9.05659676e-01 -1.16300397e-01 -2.26022094e-01 1.24244932e-02 5.67702770e-01 -7.26614967e-02 6.50642931e-01 -1.31062520e+00 -3.75324100e-01 4.81430382e-01 4.04019117e-01 5.43926239e-01 7.07690775e-01 -3.05550694e-01 -1.92418480e+00 -7.48890817e-01 1.70950681e-01 -4.06981260e-01 4.28464144e-01 -4.18460011e-01 -6.67578101e-01 -6.94862902e-02 5.04419059e-02 -4.62180674e-02 1.02333689e+00 -1.50572762e-01 -4.32427555e-01 -5.09465158e-01 -1.29209054e+00 2.67322838e-01 6.80646360e-01 -8.39533985e-01 2.99125593e-02 5.62106669e-01 1.81433596e-02 2.19529383e-02 -8.30352783e-01 -8.30801502e-02 1.07500792e+00 -1.05959094e+00 9.52609777e-01 -2.62044132e-01 2.17222795e-01 -4.46644634e-01 -1.94667175e-01 -1.06368363e+00 -1.56811088e-01 -3.32300127e-01 2.87661493e-01 1.00782263e+00 1.24993682e-01 -6.47603154e-01 8.04671168e-01 2.84984231e-01 3.47146392e-01 -4.74650294e-01 -5.03242195e-01 -7.19701350e-01 -4.74163890e-01 -2.79774368e-01 5.65261364e-01 7.06067085e-01 -4.90290560e-02 8.08319077e-02 5.87553065e-03 1.70991033e-01 7.88638413e-01 5.65337777e-01 4.10739332e-01 -1.31875038e+00 -1.55338407e-01 -2.44633585e-01 -5.35825312e-01 -5.45888603e-01 -8.06742609e-02 -7.99555659e-01 1.99278072e-01 -1.21069276e+00 2.57195026e-01 -4.51063424e-01 -4.90671545e-01 3.87300551e-01 -4.70993668e-02 7.33623683e-01 1.32327989e-01 -4.79685441e-02 -3.75977963e-01 -1.21118993e-01 1.29352975e+00 -5.64511538e-01 -1.02010638e-01 4.10228893e-02 -5.90805471e-01 4.56601709e-01 6.90797448e-01 -3.17170024e-01 -3.07011902e-01 -7.94045925e-02 5.21831214e-01 -3.86795998e-01 6.97637856e-01 -9.89815354e-01 -1.95478037e-01 -3.50146562e-01 5.44142962e-01 -2.52011240e-01 4.65387881e-01 -1.12742305e+00 7.39833489e-02 6.77437723e-01 -3.02372605e-01 -3.75078142e-01 -8.85161236e-02 7.30472684e-01 5.07699512e-02 -3.83256078e-01 9.52643991e-01 -3.15136850e-01 -6.22781754e-01 -1.85441196e-01 -1.72492608e-01 -5.01798749e-01 1.12573433e+00 -6.11007631e-01 -6.13929629e-01 -1.88145399e-01 -1.52553752e-01 -3.62866491e-01 7.91367650e-01 -3.88877094e-02 5.69394350e-01 -1.12409008e+00 -9.08278152e-02 2.60306478e-01 1.87911078e-01 -4.20915663e-01 4.53682654e-02 7.00417161e-01 -7.44506180e-01 2.05945849e-01 -3.69375944e-01 -9.31830347e-01 -1.53873849e+00 7.69203126e-01 2.00235948e-01 3.20858508e-01 -2.79056221e-01 6.36424601e-01 2.33409137e-01 1.95757195e-01 -2.67031997e-01 -4.87589329e-01 -6.39712960e-02 8.90280679e-02 7.22497582e-01 4.39206511e-01 2.48565301e-01 -5.44695914e-01 -2.71707565e-01 9.63027358e-01 2.24388242e-01 2.75598735e-01 1.40189552e+00 -1.30311206e-01 -1.59265131e-01 7.63999343e-01 1.30926490e+00 1.68446347e-01 -1.49449170e+00 1.42524257e-01 -3.34095895e-01 -8.57482433e-01 1.12858787e-01 -1.03708804e+00 -1.07394183e+00 1.34948218e+00 1.02720487e+00 4.93395656e-01 1.28000855e+00 -1.47809997e-01 5.90745032e-01 4.47068900e-01 5.18832982e-01 -1.15869462e+00 2.66456246e-01 -3.40425164e-01 4.80485976e-01 -1.23548901e+00 1.39964476e-01 -6.93177104e-01 -2.47210488e-01 1.42162621e+00 5.75901754e-02 1.82050988e-02 4.09623086e-01 3.67714643e-01 2.60936916e-01 -3.51639360e-01 -3.77429605e-01 -3.57437372e-01 2.20501527e-01 9.28173482e-01 3.35383683e-01 3.01638633e-01 1.66843951e-01 -1.83728293e-01 2.00759634e-01 -1.34461090e-01 4.08029914e-01 1.08091450e+00 -6.63726747e-01 -1.02643704e+00 -4.47470993e-01 5.22062302e-01 -5.00261605e-01 2.11878315e-01 -5.04608631e-01 4.88918453e-01 2.65279382e-01 1.13393450e+00 -8.39119181e-02 -2.01049849e-01 1.21969789e-01 3.48820575e-02 1.07015860e+00 -6.24660492e-01 -3.46110314e-01 2.29252458e-01 -1.63945839e-01 -7.66251266e-01 -9.61781442e-01 -6.64772391e-01 -1.08882475e+00 -4.29411530e-02 -5.74509501e-01 -1.65930986e-01 9.22670662e-01 7.80096948e-01 -1.08980522e-01 1.78926751e-01 8.69600594e-01 -6.89796805e-01 -1.51043728e-01 -3.09451222e-01 -1.06888556e+00 7.64761448e-01 4.17309195e-01 -8.25722516e-01 -3.57595086e-01 3.92997861e-01]	[10.184423446655273, -2.6007742881774902]
07c17ee8-6d4e-4e88-a985-24d1f4a95922	graph-structure-learning-for-robust-graph	2005.10203	null	https://arxiv.org/abs/2005.10203v3	https://arxiv.org/pdf/2005.10203v3.pdf	Graph Structure Learning for Robust Graph Neural Networks	Graph Neural Networks (GNNs) are powerful tools in representation learning for graphs. However, recent studies show that GNNs are vulnerable to carefully-crafted perturbations, called adversarial attacks. Adversarial attacks can easily fool GNNs in making predictions for downstream tasks. The vulnerability to adversarial attacks has raised increasing concerns for applying GNNs in safety-critical applications. Therefore, developing robust algorithms to defend adversarial attacks is of great significance. A natural idea to defend adversarial attacks is to clean the perturbed graph. It is evident that real-world graphs share some intrinsic properties. For example, many real-world graphs are low-rank and sparse, and the features of two adjacent nodes tend to be similar. In fact, we find that adversarial attacks are likely to violate these graph properties. Therefore, in this paper, we explore these properties to defend adversarial attacks on graphs. In particular, we propose a general framework Pro-GNN, which can jointly learn a structural graph and a robust graph neural network model from the perturbed graph guided by these properties. Extensive experiments on real-world graphs demonstrate that the proposed framework achieves significantly better performance compared with the state-of-the-art defense methods, even when the graph is heavily perturbed. We release the implementation of Pro-GNN to our DeepRobust repository for adversarial attacks and defenses (footnote: https://github.com/DSE-MSU/DeepRobust). The specific experimental settings to reproduce our results can be found in https://github.com/ChandlerBang/Pro-GNN.	['Xianfeng Tang', 'Wei Jin', 'Suhang Wang', 'Xiaorui Liu', 'Jiliang Tang', 'Yao Ma']	2020-05-20	null	null	null	null	['graph-structure-learning']	['graphs']	[ 1.48662686e-01 2.87276089e-01 -1.14467621e-01 6.07453138e-02 -4.83152151e-01 -1.05146301e+00 4.71468538e-01 9.95239541e-02 2.33172312e-01 6.08762026e-01 1.03691205e-01 -7.63054013e-01 -1.75696492e-01 -1.09810245e+00 -9.88911152e-01 -6.77787125e-01 -5.18082917e-01 1.02392182e-01 2.64414907e-01 -6.03876710e-01 2.94867083e-02 7.52692938e-01 -5.00172973e-01 1.05859004e-02 5.89520216e-01 4.47996140e-01 -4.26483214e-01 7.87448883e-01 4.59672838e-01 7.94453144e-01 -5.58507264e-01 -7.67063439e-01 7.40598500e-01 -3.20679337e-01 -8.02652299e-01 -3.11217070e-01 2.47864529e-01 -6.31229579e-02 -1.26387930e+00 1.73284912e+00 4.55117315e-01 1.40615150e-01 4.10721600e-01 -1.65587831e+00 -9.83141899e-01 1.00144017e+00 -5.31398177e-01 3.00858587e-01 1.69858322e-01 4.84161288e-01 9.14313793e-01 -2.18854576e-01 3.14087600e-01 1.38923573e+00 5.10803998e-01 6.54671371e-01 -1.03248417e+00 -9.66250956e-01 5.13971686e-01 -7.23623950e-03 -1.31372726e+00 -3.25105876e-01 8.75919342e-01 -1.41766876e-01 4.43068415e-01 6.35651588e-01 1.16215095e-01 1.60453475e+00 4.27408874e-01 4.15368915e-01 7.05423176e-01 -5.81174605e-02 1.15571782e-01 -3.18814397e-01 -1.21342801e-01 7.71657407e-01 7.30980873e-01 5.64640522e-01 8.75444338e-02 -5.98914981e-01 6.60082698e-01 1.76216170e-01 -5.87955952e-01 -3.09181392e-01 -7.45279551e-01 9.93709564e-01 1.07417285e+00 1.80491835e-01 -4.16890122e-02 5.63401341e-01 6.69596076e-01 4.90337521e-01 2.42117852e-01 5.07945895e-01 -1.64261505e-01 4.67789710e-01 -4.33436707e-02 1.01463087e-02 9.09735143e-01 9.02211547e-01 3.90825868e-01 3.89996827e-01 5.71065508e-02 4.68177706e-01 2.00810000e-01 4.00349051e-01 1.17461085e-01 -4.75626767e-01 5.45937061e-01 3.16387236e-01 -5.35893261e-01 -1.79451764e+00 -2.68538535e-01 -5.20787477e-01 -1.44767988e+00 1.40730180e-02 2.80752212e-01 -3.61692786e-01 -9.38890815e-01 1.94097221e+00 2.69577861e-01 5.94204128e-01 1.16865464e-01 7.07530379e-01 7.62290478e-01 4.53432500e-01 -5.47166653e-02 1.58097714e-01 8.08069587e-01 -8.24472845e-01 -1.73280567e-01 -4.82364863e-01 4.29265469e-01 -2.94688404e-01 7.40052044e-01 1.49087027e-01 -5.82245648e-01 -1.84597328e-01 -1.00814199e+00 5.23149967e-01 -4.82869029e-01 -8.30684662e-01 7.07201004e-01 9.59475398e-01 -8.39717031e-01 9.39538896e-01 -8.57422054e-01 -2.43867114e-01 5.15126109e-01 3.18578929e-01 -5.65572679e-01 -2.43997172e-01 -1.65338039e+00 4.38424855e-01 5.20662248e-01 1.85429126e-01 -1.51936913e+00 -3.35910559e-01 -9.62640345e-01 9.12259519e-02 7.23463058e-01 -4.64248985e-01 8.25474203e-01 -8.04701388e-01 -1.00788808e+00 4.97935504e-01 5.65435529e-01 -6.48265302e-01 4.58702952e-01 1.08803459e-01 -7.54245162e-01 1.18858032e-01 -1.59543529e-01 -2.71613628e-01 9.46155667e-01 -1.21789098e+00 1.16439499e-01 -2.13728920e-01 6.15769327e-01 -2.87030250e-01 -5.03875911e-01 9.47267488e-02 -2.97158331e-01 -9.19645190e-01 -1.19028650e-01 -1.20023000e+00 -7.10673213e-01 -3.07470620e-01 -1.22885704e+00 2.56587088e-01 7.03360796e-01 -2.56614357e-01 1.09145558e+00 -2.12681746e+00 3.32837552e-02 6.20673418e-01 6.51835620e-01 6.13172412e-01 -4.43933815e-01 8.25359344e-01 -7.05930591e-01 6.22766733e-01 -2.35897437e-01 3.04903954e-01 -1.05874566e-02 1.27114922e-01 -6.51366889e-01 9.13396478e-01 -1.18306808e-01 1.09050941e+00 -1.04588413e+00 1.56333014e-01 -5.84192164e-02 2.95576215e-01 -3.61799777e-01 2.39687130e-01 -1.59604251e-01 4.75640953e-01 -7.17264414e-01 7.67897725e-01 8.27765167e-01 -3.76468331e-01 3.97119045e-01 3.97972912e-02 8.44118237e-01 -2.59500891e-02 -1.01895905e+00 9.62628007e-01 2.92099826e-02 2.46512756e-01 1.78538427e-01 -1.08110285e+00 7.44272768e-01 1.11866407e-01 3.08779236e-02 -1.92165121e-01 4.92980331e-01 -1.03886416e-02 2.27098927e-01 3.29106487e-02 -1.01877473e-01 6.81935698e-02 -3.96377206e-01 4.03994709e-01 -3.29233795e-01 6.93133026e-02 -4.19369712e-03 7.88994908e-01 1.79388058e+00 -5.97702146e-01 3.45610201e-01 -1.17642246e-01 5.93434393e-01 -4.48915005e-01 6.95803344e-01 9.29022849e-01 -3.40458453e-01 4.04895306e-01 9.51073825e-01 -4.02907014e-01 -5.56770384e-01 -1.23654783e+00 4.69794184e-01 8.38390589e-01 2.12072253e-01 -6.04631245e-01 -6.82982326e-01 -1.23977816e+00 2.31798932e-01 4.14019227e-01 -6.70458496e-01 -8.53536248e-01 -4.97963548e-01 -7.30992734e-01 1.06762850e+00 3.26334387e-01 2.58284479e-01 -9.68200326e-01 5.57809770e-01 -1.00047980e-02 2.14068130e-01 -1.16119909e+00 -7.42301822e-01 2.20227800e-02 -4.91378874e-01 -1.58873665e+00 -2.11904153e-01 -5.24546385e-01 1.00261652e+00 4.46207285e-01 1.09700918e+00 6.80125773e-01 -1.66999608e-01 2.10435152e-01 -4.96449500e-01 -3.70872676e-01 -8.35882068e-01 1.62733987e-01 3.85903597e-01 -8.50422657e-04 -1.61165401e-01 -1.03610611e+00 -3.44770759e-01 2.86360264e-01 -1.20976174e+00 -4.58601892e-01 4.28174138e-01 7.02138305e-01 3.90280247e-01 4.53832299e-01 6.24987423e-01 -1.45561028e+00 8.54729176e-01 -8.38230908e-01 -7.63274074e-01 2.21429262e-02 -4.06013638e-01 -1.10976279e-01 1.32357609e+00 -4.82510269e-01 -2.10212529e-01 -2.44576067e-01 -1.98405147e-01 -7.92106330e-01 -7.29864612e-02 6.06643021e-01 -6.19013071e-01 -5.93229949e-01 1.00488687e+00 -3.82166840e-02 -8.82429555e-02 -3.03487312e-02 4.63581413e-01 1.41900063e-01 5.48542500e-01 -6.61817253e-01 1.70579338e+00 2.72920132e-01 3.82269025e-01 -5.03835917e-01 -7.23907709e-01 6.13234900e-02 -1.63607314e-01 7.67428130e-02 1.63249716e-01 -5.79472363e-01 -7.42238581e-01 5.33535182e-01 -7.64340162e-01 -4.24600482e-01 1.25747904e-01 1.64462496e-02 -3.24393749e-01 9.11922872e-01 -8.21649790e-01 -4.27187979e-01 -5.19559681e-01 -1.05641079e+00 2.82814533e-01 1.33796692e-01 2.31484011e-01 -1.21265697e+00 7.67603070e-02 9.94311497e-02 3.23797405e-01 9.75184262e-01 8.72357190e-01 -1.21204877e+00 -6.65984869e-01 -5.23218572e-01 -2.07118422e-01 4.55421954e-01 2.70215511e-01 7.70577136e-03 -7.02815354e-01 -8.56759608e-01 -2.37792194e-01 -2.72525162e-01 7.74710715e-01 4.15865146e-02 1.46792150e+00 -7.48706877e-01 -4.02299434e-01 1.02422965e+00 1.47706330e+00 -1.67353958e-01 7.37682104e-01 1.90519616e-01 1.19214630e+00 2.00986400e-01 2.98249125e-01 1.70143783e-01 -4.23555560e-02 1.32792532e-01 1.24089444e+00 -2.03905385e-02 1.78240120e-01 -5.25800407e-01 4.88937318e-01 5.00485480e-01 1.55273363e-01 -8.34353209e-01 -9.55166578e-01 3.03763747e-01 -1.84688401e+00 -9.57490504e-01 -8.28276798e-02 2.02243900e+00 4.98811275e-01 5.15582085e-01 5.06237745e-02 4.16523665e-02 1.02615333e+00 6.85770452e-01 -6.75625801e-01 -3.97081167e-01 -4.14603055e-02 1.53628066e-01 9.31127787e-01 5.30343354e-01 -1.16549337e+00 1.16563475e+00 5.13097477e+00 8.63955379e-01 -1.02145708e+00 -1.34215653e-01 6.59838855e-01 9.86850560e-02 -1.81082308e-01 1.34677991e-01 -3.56620163e-01 4.76349413e-01 1.14455056e+00 -7.38492429e-01 7.54699707e-01 9.22801018e-01 -1.22056790e-01 8.06681037e-01 -9.59883988e-01 5.14843822e-01 -7.08271787e-02 -1.32237291e+00 1.65922135e-01 2.44256958e-01 5.92845261e-01 2.47219130e-01 2.17264056e-01 3.86658639e-01 1.18935013e+00 -1.36081624e+00 6.17403910e-02 1.15298845e-01 7.97690392e-01 -1.17135322e+00 5.59369385e-01 3.23614448e-01 -1.17451727e+00 -4.69847694e-02 -6.54405415e-01 2.25004554e-01 -1.14685252e-01 6.48909867e-01 -6.81409657e-01 1.00589907e+00 5.15946507e-01 6.62377298e-01 -7.28022873e-01 7.08355010e-01 -6.35655820e-01 7.51354396e-01 -2.87783351e-02 2.53521472e-01 2.67803490e-01 1.41074471e-02 8.59917760e-01 8.62310290e-01 2.13801153e-02 2.35360041e-02 4.51305181e-01 6.65515721e-01 -5.05567193e-01 -1.78108677e-01 -1.19344831e+00 -4.82477099e-01 5.63902855e-01 1.27852798e+00 -6.01332188e-01 1.97097182e-01 -1.70299202e-01 9.20671642e-01 5.44753551e-01 4.05680090e-01 -1.05533457e+00 -5.98938107e-01 9.87332642e-01 3.11298054e-02 1.22160599e-01 -1.45698503e-01 2.44945899e-01 -1.19314790e+00 -1.68614462e-01 -1.49508178e+00 7.35500276e-01 -2.93303967e-01 -1.74842536e+00 9.81928766e-01 -2.81674773e-01 -1.12682116e+00 -2.58959346e-02 -5.52697003e-01 -1.08128929e+00 7.49539435e-01 -1.08459747e+00 -1.22052264e+00 -2.19595447e-01 9.17949378e-01 -1.32632166e-01 -3.68885010e-01 7.38535702e-01 3.93697135e-02 -9.12679911e-01 1.06690502e+00 1.29423682e-02 8.51591527e-01 5.68726242e-01 -1.09306467e+00 1.08484054e+00 1.54218590e+00 2.38177776e-01 7.69271493e-01 8.10280085e-01 -9.40933347e-01 -1.63230228e+00 -1.66669393e+00 -6.00102656e-02 -4.28486079e-01 1.16666281e+00 -5.53579926e-01 -1.06476629e+00 1.02592444e+00 -2.51903012e-02 6.49633646e-01 5.73901594e-01 -8.80087689e-02 -8.04841638e-01 -3.57013755e-02 -1.26223016e+00 1.00266528e+00 1.42205513e+00 -5.99979877e-01 -9.16550234e-02 8.32378805e-01 1.03751910e+00 -5.30075967e-01 -6.38034284e-01 4.29675043e-01 -4.38728146e-02 -8.79395187e-01 1.11460185e+00 -1.02024329e+00 1.16550013e-01 -3.09840143e-01 -8.03854913e-02 -1.63829923e+00 -5.79480112e-01 -1.17032886e+00 -3.75295401e-01 1.02597916e+00 3.14021409e-01 -1.18072796e+00 8.75332594e-01 3.74901623e-01 7.27551850e-03 -7.62076259e-01 -7.43081152e-01 -1.11587000e+00 3.38725388e-01 -2.34830275e-01 7.81882167e-01 1.08741546e+00 -2.05826491e-01 1.07805677e-01 -5.07772386e-01 1.01454496e+00 6.82092667e-01 -1.48670837e-01 1.09040487e+00 -1.00054085e+00 -5.29741645e-01 -3.09482962e-01 -7.61789978e-01 -4.40680504e-01 5.41628480e-01 -1.23885345e+00 -2.55672663e-01 -1.22286308e+00 -1.60772964e-01 -3.20900232e-01 -6.05550826e-01 6.40688300e-01 -4.04582858e-01 1.28113091e-01 2.23375469e-01 -1.40490076e-02 -3.91816914e-01 3.16268861e-01 1.05113828e+00 -3.37746382e-01 1.35645434e-01 2.44873077e-01 -1.37757516e+00 6.82466626e-01 1.09773719e+00 -7.57728696e-01 -5.88109851e-01 -3.85025665e-02 2.39241138e-01 -6.57949150e-02 3.92763138e-01 -8.51974607e-01 1.61952242e-01 -4.34999466e-01 2.50663366e-02 4.07115407e-02 -9.82176289e-02 -7.33879685e-01 3.68843853e-01 7.13736236e-01 -1.66325971e-01 1.21602990e-01 1.55609921e-01 1.04608262e+00 4.62695956e-02 1.04936650e-02 9.65655208e-01 -2.11793795e-01 -3.27518255e-01 1.08699262e+00 -9.53577273e-03 3.74466807e-01 1.15184629e+00 2.14038134e-01 -8.06663990e-01 -8.83250356e-01 -6.17336273e-01 3.30158532e-01 5.28450787e-01 5.41762650e-01 6.22239888e-01 -1.28581369e+00 -8.43897998e-01 1.62880242e-01 2.04642210e-02 -8.22922587e-02 2.87010700e-01 4.78981197e-01 -4.94778395e-01 8.33488535e-03 -1.27103910e-01 1.24910928e-01 -1.28916109e+00 1.27263081e+00 5.49151957e-01 -5.07984042e-01 -6.22976780e-01 9.61211443e-01 4.43429828e-01 -4.93287355e-01 1.92717955e-01 1.65836826e-01 1.35576770e-01 -6.42902136e-01 5.15042603e-01 1.98906407e-01 -6.63847402e-02 -5.63187540e-01 -4.87765193e-01 1.74196474e-02 -3.34252357e-01 6.54096961e-01 1.21685684e+00 2.43082926e-01 -3.36147040e-01 -3.49511892e-01 1.18353379e+00 3.91843796e-01 -8.16190422e-01 -2.25557819e-01 -2.30546683e-01 -6.45228148e-01 -2.47506738e-01 -4.12403226e-01 -1.60114479e+00 4.87157941e-01 1.40280165e-02 7.60409474e-01 1.22848916e+00 -1.15989871e-01 7.87581027e-01 4.89124596e-01 4.77849573e-01 -2.76005417e-01 1.64941043e-01 6.29790187e-01 1.08029151e+00 -9.38028097e-01 9.41631272e-02 -8.90469015e-01 -4.36276466e-01 8.36365759e-01 8.22155595e-01 -7.07308710e-01 8.33754480e-01 1.59064934e-01 -4.05272990e-02 -2.50821650e-01 -6.46558821e-01 1.14927962e-01 9.70989391e-02 9.03856814e-01 -7.26980641e-02 1.83521241e-01 1.79905638e-01 6.04110062e-01 -2.46179953e-01 -8.15120578e-01 9.23613429e-01 7.33605206e-01 -4.21123430e-02 -1.28684330e+00 -3.68388653e-01 3.63019615e-01 -6.88588679e-01 -1.81368843e-01 -8.59340489e-01 5.92209160e-01 -5.01754463e-01 1.04415751e+00 -7.42467999e-01 -8.87740970e-01 3.38548601e-01 -5.13915539e-01 9.40653775e-03 -7.51906931e-01 -6.85008526e-01 -4.74810749e-01 1.83522046e-01 -9.04193461e-01 3.23770732e-01 -8.75966623e-02 -1.01364625e+00 -8.39784384e-01 -2.39236772e-01 2.26909757e-01 5.43335155e-02 4.18727219e-01 5.30261219e-01 6.94580197e-01 1.10930288e+00 -5.38687646e-01 -8.54596138e-01 -6.50538743e-01 -7.48413086e-01 3.80196571e-01 3.83495301e-01 -4.39741343e-01 -9.72556114e-01 -6.42122567e-01]	[6.153866291046143, 7.30024528503418]
730773d2-5bea-41fd-a56a-ff69f55b927b	improving-document-level-relation-extraction	null	null	https://ieeexplore.ieee.org/abstract/document/9194547	https://conferences.computer.org/ickg/pdfs/ICKG2020-66r9RP2mQIZywMjHhQVtDI/815600a305/815600a305.pdf	Improving Document-level Relation Extraction via Contextualizing Mention Representations and Weighting Mention Pairs	Document-level relation extraction (RE) has attracted considerable attention, because a large number of relational facts are expressed in multiple sentences. Recently, encoder-aggregator based models have become promising for document-level RE. However, these models have two shortcomings: (i) they cannot obtain contextualized representations of a mention by low computational cost, when the mention is involved in different entity pairs; (ii) they ignore the different weights for the mention pairs of a target entity pair. To tackle the above two problems, in this paper, we propose a novel encoder-attender-aggregator model, which introduces two attenders between the encoder and aggregator. Specifically, a mutual attender is first employed on the selected head and tail mentions to efficiently produce contextualized mention representations. Then, an integration attender is utilized to weight the mention pairs of a target entity pair. Extensive experiments on two document-level RE datasets show that the proposed model performs better than the state-of-the-art baselines. Our codes are publicly available at "https://github.com/nefujiangping/EncAttAgg".	['Ping Jiang;Xian-Ling Mao;Binbin Bian;Heyan Huang']	2020-08-09	null	null	null	null	['document-level-relation-extraction']	['natural-language-processing']	[-1.08556084e-01 2.41821095e-01 -5.18661559e-01 -3.72460753e-01 -1.15781283e+00 -3.19055855e-01 6.97158337e-01 4.99005854e-01 -3.92662466e-01 9.30345535e-01 6.76494062e-01 -8.28686655e-02 -4.05699424e-02 -8.14332783e-01 -6.04427099e-01 -5.60437500e-01 1.82234511e-01 3.70658785e-01 2.64801413e-01 -1.28439978e-01 6.19293675e-02 1.93644091e-01 -1.10660172e+00 4.72133189e-01 1.05470395e+00 8.33424032e-01 3.08218807e-01 1.13588683e-01 -4.23889309e-01 1.13631415e+00 -6.58394098e-01 -8.93749177e-01 -2.46999681e-01 -4.27714676e-01 -8.96486104e-01 -1.99034035e-01 1.64986148e-01 -1.31425649e-01 -5.76345563e-01 1.13270950e+00 3.68429691e-01 1.55119598e-01 7.58888364e-01 -8.75999272e-01 -1.20544159e+00 1.29636109e+00 -8.57574224e-01 5.98671734e-01 2.65605807e-01 -6.30756557e-01 1.56155360e+00 -1.20587265e+00 6.38647795e-01 9.94289696e-01 2.42283642e-01 3.04510564e-01 -8.79022956e-01 -8.24062288e-01 4.25878346e-01 5.84678352e-01 -1.68893147e+00 -4.27334189e-01 8.08660686e-01 -1.18760131e-01 1.36052370e+00 2.01502755e-01 2.99482644e-01 7.63359487e-01 -5.95148019e-02 9.92780685e-01 4.61316556e-01 -3.16770285e-01 -2.51484543e-01 1.96493194e-01 2.46415332e-01 5.15707970e-01 3.70768934e-01 -4.23508644e-01 -3.87836844e-01 -1.25991954e-02 4.13268596e-01 3.43637317e-02 -3.23796690e-01 2.67590106e-01 -1.07640839e+00 7.32314527e-01 7.00049639e-01 7.62543619e-01 -5.92585862e-01 5.61588667e-02 3.25135052e-01 -1.92904659e-02 6.45001709e-01 3.37003648e-01 -4.60130692e-01 6.02984875e-02 -8.39409590e-01 2.83486784e-01 5.83131373e-01 1.38241065e+00 7.17352331e-01 -4.60678756e-01 -3.16591978e-01 9.88173246e-01 2.84985989e-01 7.83213153e-02 3.70829493e-01 -4.06654298e-01 1.20931184e+00 8.88058841e-01 -7.78656825e-02 -1.27030563e+00 -4.20541354e-02 -5.33605278e-01 -1.04700792e+00 -7.01027274e-01 -2.68269360e-01 -2.45734543e-01 -5.50699234e-01 1.48369801e+00 3.83499175e-01 3.03522915e-01 3.71734500e-01 6.48166776e-01 1.43362117e+00 9.95874345e-01 3.46510261e-01 -2.90735275e-01 1.62541258e+00 -1.06759918e+00 -1.12967241e+00 -4.89464790e-01 7.71286309e-01 -8.27763855e-01 4.69165713e-01 -2.28182226e-01 -1.15186715e+00 -3.70941818e-01 -9.95310426e-01 -4.95700628e-01 -4.54295397e-01 5.00692189e-01 4.59099621e-01 3.96737643e-02 -3.71964157e-01 3.86496872e-01 -6.23248339e-01 1.52882040e-02 3.11602354e-01 1.11055396e-01 -3.48388344e-01 -3.62969600e-02 -1.63424921e+00 1.13787949e+00 5.75999618e-01 3.87478888e-01 -3.12956542e-01 -5.48138380e-01 -1.09865630e+00 4.43944037e-01 6.09313965e-01 -5.25995672e-01 1.17753839e+00 -3.22860032e-01 -9.23944831e-01 7.04310715e-01 -6.14039779e-01 -2.64915496e-01 -2.19525280e-03 -5.12340367e-01 -7.02935874e-01 -7.44880214e-02 3.07325542e-01 1.29169881e-01 9.39630419e-02 -1.27666867e+00 -8.23616266e-01 -1.24801800e-01 1.67704672e-01 3.71504515e-01 -2.01958224e-01 4.46881562e-01 -5.90101898e-01 -8.09959710e-01 1.78790346e-01 -5.51875174e-01 -7.77221471e-02 -8.05230141e-01 -9.18190181e-01 -6.89593673e-01 5.57728529e-01 -6.78713799e-01 1.85311592e+00 -2.05782843e+00 3.37324798e-01 -1.90351725e-01 2.51719654e-01 5.43157101e-01 -6.91899844e-03 8.93556654e-01 -2.84389377e-01 3.59024912e-01 -2.05311134e-01 -5.29942095e-01 -1.25107795e-01 2.91377623e-02 -3.85159940e-01 8.09996575e-02 4.58632171e-01 9.49378490e-01 -1.03355372e+00 -8.93899679e-01 -1.23087198e-01 5.59938729e-01 -2.02780366e-01 3.99973571e-01 -5.46164159e-03 1.00052714e-01 -6.87871575e-01 5.38498044e-01 5.02342463e-01 -2.51421303e-01 3.37485820e-01 -4.91272777e-01 -4.47892025e-02 1.02458107e+00 -1.09435093e+00 1.33155346e+00 -4.47574645e-01 2.40055129e-01 -4.25005794e-01 -8.72437119e-01 1.13275909e+00 6.28806710e-01 2.82605231e-01 -3.90775621e-01 8.67321044e-02 3.79941285e-01 -3.66923399e-02 -6.08401895e-01 7.25990772e-01 -1.83347315e-01 -2.27384582e-01 2.67328560e-01 1.53113067e-01 6.27613217e-02 5.89728594e-01 6.26684487e-01 1.04096913e+00 -2.23227739e-02 6.38408363e-01 9.58692431e-02 7.82190800e-01 -3.03474814e-01 1.02475405e+00 1.79539382e-01 1.96103409e-01 5.73000133e-01 6.08925760e-01 -1.11015074e-01 -6.66052938e-01 -7.58122861e-01 4.19524163e-02 7.70422757e-01 3.09915572e-01 -8.32482159e-01 -3.75517517e-01 -9.10979152e-01 -1.52124718e-01 8.69407296e-01 -5.59653997e-01 -1.00805566e-01 -9.50587809e-01 -7.64003396e-01 3.95929039e-01 8.05329561e-01 5.40184736e-01 -1.03588843e+00 1.05976854e-02 4.25014317e-01 -6.88838005e-01 -1.29624391e+00 -5.55759192e-01 1.63449883e-01 -5.46333015e-01 -8.88025939e-01 -6.52073085e-01 -9.72131431e-01 5.39665997e-01 2.55657911e-01 1.18103659e+00 1.77737027e-01 1.83029145e-01 -3.61992925e-01 -7.01775551e-01 -2.18062371e-01 4.49667983e-02 5.51210999e-01 -2.82149374e-01 -8.72211233e-02 7.67297924e-01 -5.37035227e-01 -4.01065081e-01 1.46664390e-02 -6.75694585e-01 1.40164554e-01 7.97519565e-01 6.82098269e-01 7.65545249e-01 1.12168141e-01 8.66359591e-01 -1.27682579e+00 6.88385248e-01 -9.52999771e-01 -2.23085970e-01 6.97179079e-01 -3.45716745e-01 1.67599857e-01 6.59810901e-01 -3.26474130e-01 -1.32349730e+00 -1.59429729e-01 -2.35608801e-01 -5.02644060e-03 1.77484632e-01 1.13133276e+00 -4.78347510e-01 7.92733192e-01 1.54825658e-01 1.52210698e-01 -7.52805650e-01 -7.11444914e-01 3.70394528e-01 7.97145188e-01 5.04773378e-01 -6.10288918e-01 7.88793027e-01 -1.85761705e-01 -2.58145750e-01 -4.08242971e-01 -1.27416098e+00 -4.84733313e-01 -5.69868207e-01 2.29623929e-01 7.59502649e-01 -1.10503900e+00 -2.22781762e-01 1.42664298e-01 -1.55832613e+00 3.04436296e-01 -1.68528393e-01 5.63210130e-01 1.91755835e-02 2.16521591e-01 -8.37474704e-01 -5.83145857e-01 -4.79615957e-01 -1.05738258e+00 8.80373240e-01 6.60788059e-01 -1.45325363e-01 -7.81810641e-01 9.78124142e-02 2.81528711e-01 9.80685949e-02 6.79170266e-02 1.01667488e+00 -9.18459296e-01 -5.36355913e-01 -3.57429594e-01 -5.64285278e-01 1.18450776e-01 4.47269082e-01 1.57489657e-01 -5.38839102e-01 1.02499291e-01 -3.06091309e-01 -2.71050125e-01 8.11863720e-01 -1.22383386e-01 9.38937485e-01 -5.86813867e-01 -5.30880868e-01 2.31570333e-01 1.19506156e+00 2.33647555e-01 5.86828291e-01 1.86591253e-01 7.57624090e-01 5.54129958e-01 8.29513848e-01 2.14100331e-01 8.84615958e-01 7.29051054e-01 2.06739843e-01 1.08152635e-01 -2.63229251e-01 -5.15747309e-01 1.91918537e-01 1.40361917e+00 -2.85680681e-01 -5.39164603e-01 -7.04252958e-01 8.69785666e-01 -1.98370123e+00 -9.39240932e-01 -2.54546642e-01 1.68047285e+00 1.27237117e+00 -2.08378471e-02 -2.25018084e-01 -5.25004789e-02 9.11236167e-01 4.14957941e-01 -2.46131584e-01 -1.45301044e-01 -1.42370462e-01 1.41781017e-01 1.50674313e-01 3.96846592e-01 -1.04841959e+00 1.10560024e+00 4.53039408e+00 8.88934374e-01 -4.85826552e-01 2.03810781e-01 3.88705790e-01 4.06667069e-02 -4.82970148e-01 2.78951496e-01 -1.35578275e+00 4.97557312e-01 7.47978985e-01 -5.45843601e-01 -1.45867944e-01 7.67456949e-01 -3.28471243e-01 5.23338355e-02 -1.12666523e+00 6.57183349e-01 1.78332835e-01 -1.32853937e+00 1.09829128e-01 -1.47611886e-01 6.67679310e-01 -2.26054057e-01 -2.29521587e-01 4.85129595e-01 3.51475537e-01 -8.89088392e-01 5.02968788e-01 4.81140167e-01 6.98490500e-01 -1.03170764e+00 1.16409111e+00 2.18370870e-01 -1.71976626e+00 2.99331993e-01 -4.50070202e-01 2.65139580e-01 4.86123353e-01 9.50696170e-01 -4.70106333e-01 1.00579512e+00 4.21442837e-01 8.17882538e-01 -3.13286573e-01 7.98140347e-01 -9.51036990e-01 3.61673534e-01 -5.96900433e-02 -2.20481589e-01 2.44147778e-01 -8.82820189e-02 3.45420122e-01 1.58451903e+00 3.23330402e-01 5.43511987e-01 -6.81100935e-02 7.87856817e-01 -5.00873148e-01 2.78248668e-01 -3.06938410e-01 -1.43218398e-01 9.33589399e-01 1.28049719e+00 -2.08956212e-01 -4.34197485e-01 -6.29320621e-01 8.01544726e-01 8.97907436e-01 3.75923842e-01 -8.24454665e-01 -9.69124198e-01 5.91608286e-01 -1.74229711e-01 5.05334675e-01 -1.48614153e-01 -9.72437765e-03 -1.41663694e+00 2.77065158e-01 -5.34594774e-01 5.79617977e-01 -5.50775111e-01 -1.33692241e+00 8.29661548e-01 6.05952702e-02 -1.02606809e+00 -2.45757729e-01 -5.10654710e-02 -6.14065528e-01 1.01335490e+00 -1.63964486e+00 -1.18562329e+00 -1.12772034e-02 3.53826374e-01 5.33925354e-01 -3.24956961e-02 7.78096914e-01 7.59186685e-01 -9.38105762e-01 6.80328250e-01 -2.91992456e-01 6.81491077e-01 4.51789290e-01 -1.24534595e+00 3.54422927e-01 1.11474705e+00 3.75811130e-01 1.02283740e+00 4.79231566e-01 -8.64036083e-01 -8.71410787e-01 -1.07066953e+00 1.95383227e+00 -1.85981616e-01 6.51298106e-01 -1.83827057e-01 -1.14885783e+00 1.11958611e+00 4.44199830e-01 7.72554800e-02 8.22647095e-01 3.88599932e-01 -4.67844725e-01 -1.45320326e-01 -8.06653202e-01 5.81176341e-01 9.13741112e-01 -5.51388562e-01 -1.12752640e+00 3.00362855e-01 7.91645467e-01 -4.66716349e-01 -1.09534335e+00 5.39693356e-01 1.70903966e-01 -5.66138148e-01 8.52939487e-01 -4.50535119e-01 9.51587617e-01 -4.05819058e-01 -8.30162689e-02 -1.37779963e+00 -4.11326647e-01 -2.06521347e-01 -7.91515470e-01 2.04272461e+00 8.60942960e-01 -5.01617432e-01 3.64627481e-01 6.22948766e-01 -1.65938720e-01 -1.20855737e+00 -8.66074860e-01 -6.19285226e-01 1.27761401e-02 6.27969056e-02 8.60832274e-01 8.94864380e-01 4.18659925e-01 8.47093225e-01 -3.12763482e-01 1.70472115e-01 1.77776515e-01 3.55849862e-01 3.37260306e-01 -7.97638237e-01 -1.33433595e-01 -2.10578233e-01 -9.19398889e-02 -1.32618260e+00 2.36333489e-01 -1.04288006e+00 6.03829324e-02 -1.89573562e+00 5.20916820e-01 -6.85367167e-01 -4.43008840e-01 6.45133734e-01 -7.62378216e-01 -1.75188944e-01 8.37109759e-02 3.22562724e-01 -5.32152295e-01 8.09201002e-01 9.67914343e-01 -3.42663489e-02 4.51616459e-02 -1.41822919e-01 -1.04539216e+00 6.31404996e-01 7.26242244e-01 -8.39801252e-01 -2.83077389e-01 -7.25816071e-01 4.01133269e-01 3.85388546e-02 -9.18751061e-02 -7.08523989e-01 5.66633224e-01 -1.89153716e-01 8.12144279e-02 -7.47765541e-01 3.11148971e-01 -6.95907295e-01 3.41287628e-02 1.28450822e-02 -4.62555528e-01 1.75581798e-01 -1.46453366e-01 3.15643191e-01 -6.33076310e-01 -5.60685694e-01 4.48170871e-01 -8.25908780e-02 -3.73832494e-01 3.74529541e-01 2.87893843e-02 2.99094528e-01 9.31478024e-01 4.61540669e-01 -6.17880166e-01 -1.98915869e-01 -3.51988107e-01 2.80675799e-01 -9.56002399e-02 3.91892910e-01 6.27225757e-01 -1.43703949e+00 -1.07459295e+00 -3.03587556e-01 1.97506487e-01 4.30106521e-01 2.55063981e-01 6.58616543e-01 -5.46440333e-02 4.40330654e-01 4.50720876e-01 1.39205158e-01 -1.32774210e+00 5.55144191e-01 1.39662484e-02 -8.06571484e-01 -6.46068275e-01 1.30257213e+00 6.51919246e-02 -2.47541383e-01 5.52887209e-02 -2.73071557e-01 -6.02790415e-01 3.30450237e-01 7.17925131e-01 1.50515184e-01 5.32888696e-02 -9.26608145e-01 -5.59287786e-01 4.48460519e-01 -6.57214403e-01 1.22068316e-01 1.47835505e+00 -2.01707095e-01 -2.65206635e-01 3.80437046e-01 1.20462358e+00 2.60998875e-01 -6.98401153e-01 -6.95381880e-01 3.21963072e-01 -3.90445560e-01 -4.01373766e-02 -5.81691742e-01 -1.29771566e+00 6.96099579e-01 -4.37087417e-01 1.93708524e-01 1.03015554e+00 4.99827057e-01 1.19885826e+00 2.40620270e-01 1.53656185e-01 -8.28469276e-01 -3.30076605e-01 5.66189349e-01 9.79178309e-01 -1.03268600e+00 3.37711126e-01 -8.92782688e-01 -8.81697416e-01 8.44650865e-01 7.17981875e-01 -1.09852701e-01 5.31660795e-01 2.99475402e-01 -1.86634585e-01 -2.45304182e-01 -8.67447197e-01 -3.26508611e-01 3.55138779e-01 1.79639459e-01 9.99506712e-01 4.11268063e-02 -7.90721059e-01 1.04937124e+00 -1.61823720e-01 -1.86430216e-01 3.68689954e-01 9.06906724e-01 -1.65658250e-01 -1.31588399e+00 2.17807338e-01 3.75131965e-01 -7.78109848e-01 -5.69243670e-01 -3.83517355e-01 5.50416350e-01 1.44158185e-01 1.06738007e+00 -8.94656703e-02 -4.29003656e-01 3.78190994e-01 6.48484081e-02 1.22240894e-01 -1.02798986e+00 -7.44514883e-01 -2.14678213e-01 4.94224995e-01 -2.21165910e-01 -5.98033965e-01 -7.60991395e-01 -1.42118108e+00 -1.73231274e-01 -5.97679198e-01 5.82497239e-01 2.65958548e-01 1.11699498e+00 4.94617522e-01 7.33733237e-01 5.65202713e-01 -3.00997823e-01 -1.97443947e-01 -1.27125299e+00 -5.69986641e-01 2.00660184e-01 1.13389850e-01 -7.72747397e-01 -3.33200544e-01 -1.40220121e-01]	[9.267608642578125, 8.669413566589355]
539c882e-ef01-42ec-b9a3-237306a0c70a	automatic-sleep-stage-classification-with-1	2302.03227	null	https://arxiv.org/abs/2302.03227v1	https://arxiv.org/pdf/2302.03227v1.pdf	Automatic Sleep Stage Classification with Cross-modal Self-supervised Features from Deep Brain Signals	The detection of human sleep stages is widely used in the diagnosis and intervention of neurological and psychiatric diseases. Some patients with deep brain stimulator implanted could have their neural activities recorded from the deep brain. Sleep stage classification based on deep brain recording has great potential to provide more precise treatment for patients. The accuracy and generalizability of existing sleep stage classifiers based on local field potentials are still limited. We proposed an applicable cross-modal transfer learning method for sleep stage classification with implanted devices. This end-to-end deep learning model contained cross-modal self-supervised feature representation, self-attention, and classification framework. We tested the model with deep brain recording data from 12 patients with Parkinson's disease. The best total accuracy reached 83.2% for sleep stage classification. Results showed speech self-supervised features catch the conversion pattern of sleep stages effectively. We provide a new method on transfer learning from acoustic signals to local field potentials. This method supports an effective solution for the insufficient scale of clinical data. This sleep stage classification model could be adapted to chronic and continuous monitor sleep for Parkinson's patients in daily life, and potentially utilized for more precise treatment in deep brain-machine interfaces, such as closed-loop deep brain stimulation.	['Luming Li', 'Yanan Sui', 'Yue Chen', 'Chen Gong']	2023-02-07	null	null	null	null	['automatic-sleep-stage-classification']	['medical']	[ 6.71096593e-02 -1.56498060e-01 -2.39769757e-01 -4.35406387e-01 -6.37798190e-01 -1.15010723e-01 -3.16262767e-02 -5.78644156e-01 -6.23006761e-01 7.52179444e-01 4.65789258e-01 -4.36942540e-02 -1.63477752e-02 -3.77190232e-01 9.44260955e-02 -8.78122449e-01 -1.87185317e-01 5.21354914e-01 2.15160996e-01 -2.26108804e-01 2.52307266e-01 2.59319663e-01 -1.34650242e+00 5.44998169e-01 1.04800713e+00 1.21906495e+00 8.98621202e-01 3.04257780e-01 -7.97304977e-03 3.93485636e-01 -8.76979709e-01 4.90963876e-01 -3.30266058e-01 -5.26680231e-01 -5.89968026e-01 -2.77357221e-01 -3.00621599e-01 -2.20677465e-01 -3.32059622e-01 1.16375411e+00 1.16105378e+00 -1.85328797e-01 6.88875377e-01 -1.08190036e+00 -4.35434520e-01 2.43386939e-01 -1.38034329e-01 1.00984490e+00 4.29665834e-01 2.93447554e-01 4.69502598e-01 -4.16795522e-01 -1.15425885e-01 6.09574735e-01 7.67643809e-01 1.30315542e+00 -9.01766717e-01 -1.05626285e+00 -5.65133214e-01 8.70164871e-01 -9.12439406e-01 -6.84615076e-01 6.10917866e-01 -6.41169786e-01 1.35217416e+00 2.32480913e-02 1.35703003e+00 1.35482371e+00 1.12674820e+00 5.13446212e-01 1.25891232e+00 -1.09602302e-01 5.56171954e-01 1.13078639e-01 3.89369398e-01 2.70597577e-01 -2.21727371e-01 1.33045018e-01 -7.56403744e-01 5.88753745e-02 4.44301784e-01 3.51379514e-01 -3.78929079e-01 3.39991122e-01 -1.20047629e+00 6.76844656e-01 4.60005373e-01 7.89514959e-01 -3.92924339e-01 -2.98674315e-01 4.54331279e-01 3.41142297e-01 6.48924232e-01 2.71003485e-01 -5.36869407e-01 -6.43921733e-01 -1.15397251e+00 -5.96876323e-01 3.87052178e-01 5.87747753e-01 2.52845854e-01 -8.10808837e-02 -3.18681031e-01 1.04173398e+00 4.81348157e-01 8.54304552e-01 1.58375168e+00 -7.66222060e-01 6.81576729e-02 6.49266899e-01 -2.76747495e-01 -1.45301148e-01 -1.09984636e+00 -1.79788440e-01 -8.45904589e-01 2.78631896e-01 -3.60702515e-01 -3.11177839e-02 -7.98865795e-01 1.44814372e+00 -2.96753675e-01 -1.50537416e-02 1.15453228e-01 7.19669580e-01 8.51217270e-01 4.96681750e-01 7.20517859e-02 -4.54031408e-01 1.64582932e+00 -6.22608304e-01 -1.07156050e+00 -8.59864116e-01 4.27455813e-01 -7.37365335e-02 1.05529189e+00 6.02110147e-01 -8.74364018e-01 -3.76307458e-01 -9.10229146e-01 1.54793724e-01 1.74580961e-02 2.22883642e-01 4.77199972e-01 6.57614410e-01 -1.26091003e+00 5.77379107e-01 -1.60497677e+00 -6.19205654e-01 7.40154028e-01 1.14717698e+00 -4.28643972e-01 7.11867094e-01 -1.06517637e+00 1.15844965e+00 -9.02979895e-02 2.63689965e-01 -7.82812655e-01 -3.93604338e-01 -5.38583636e-01 -2.36927420e-02 -6.85785115e-01 -9.47250426e-01 1.20782769e+00 -4.33503240e-01 -1.61123192e+00 1.27727342e+00 -5.63262403e-01 -3.61294627e-01 -4.26493913e-01 -1.14660405e-01 -7.74443090e-01 2.83448279e-01 5.35125732e-01 3.62747371e-01 8.98718774e-01 -9.57257673e-02 -5.16100705e-01 -1.14785743e+00 -7.99660861e-01 3.55048617e-03 -5.77709556e-01 2.68274367e-01 5.01329482e-01 -1.21298730e-01 4.11530808e-02 -9.03913677e-01 1.81282356e-01 1.29349837e-02 1.22989722e-01 -6.16280079e-01 6.63912475e-01 -5.76554835e-01 1.22597051e+00 -2.29798913e+00 2.07389653e-01 -3.79465789e-01 5.43031156e-01 1.74784318e-01 2.68199623e-01 5.11716530e-02 -2.00408340e-01 -3.33724260e-01 -2.49161661e-01 -2.36404493e-01 -2.50369459e-01 2.32001394e-01 1.30488247e-01 6.54744029e-01 -2.98785716e-01 9.91356194e-01 -5.64001679e-01 -2.08320096e-01 2.50853002e-01 1.52521566e-01 -4.28166389e-01 3.75622004e-01 6.05798066e-01 6.80724859e-01 -2.30208024e-01 4.44019139e-01 1.97856382e-01 -3.48205924e-01 -6.14287317e-01 -4.13309842e-01 -5.09255640e-02 6.72355115e-01 -2.17194349e-01 2.14348912e+00 -5.51472187e-01 9.24640298e-01 -6.54335842e-02 -1.12026298e+00 7.39795506e-01 4.21663195e-01 8.04532230e-01 -1.04267788e+00 4.92111027e-01 3.07750553e-01 2.38226414e-01 -1.05057931e+00 -4.80602831e-01 -7.10556209e-01 7.62231797e-02 2.32913420e-01 2.48398140e-01 -1.12806326e-02 -2.99776644e-01 -3.70671302e-01 1.44196320e+00 -6.72261775e-01 3.54623049e-01 -4.41997498e-01 3.53885621e-01 -3.76791537e-01 6.37776434e-01 1.98580801e-01 -6.90331936e-01 4.24193144e-01 3.19519565e-02 -6.42709956e-02 -3.32689226e-01 -1.16282904e+00 -3.21650118e-01 8.56534958e-01 1.93591621e-02 -2.48471171e-01 -6.43294036e-01 -2.32505649e-01 -4.29602295e-01 5.20345926e-01 -5.03987491e-01 -9.22887146e-01 -1.27167672e-01 -7.07347393e-01 4.28829640e-01 7.04160690e-01 5.42053759e-01 -1.64531088e+00 -7.00383723e-01 3.08560610e-01 -4.43056852e-01 -9.42716300e-01 -4.11213517e-01 8.98373902e-01 -1.22775614e+00 -9.21883106e-01 -8.91550899e-01 -1.30840564e+00 2.65575469e-01 -7.77139664e-02 4.13629323e-01 -7.25339413e-01 -2.37449527e-01 4.60345715e-01 -2.46590346e-01 -4.08958793e-01 -2.55380601e-01 2.09678188e-02 6.80695593e-01 -2.73358256e-01 1.07020843e+00 -1.17116225e+00 -1.14817083e+00 3.78668398e-01 -1.84355557e-01 -2.82311976e-01 6.78865254e-01 6.86115384e-01 2.92579859e-01 -2.01524064e-01 7.98810422e-01 -8.42428654e-02 1.00323474e+00 -5.11488974e-01 -2.29359306e-02 -7.22961873e-02 -7.09486902e-01 7.04991259e-03 3.34642798e-01 -4.26355183e-01 -7.79098392e-01 -2.62683064e-01 -5.73019922e-01 -2.57645637e-01 -2.60724157e-01 1.26865491e-01 -1.83451772e-01 1.59229398e-01 9.52994466e-01 6.90609455e-01 3.20663452e-01 -4.71886337e-01 -3.99000168e-01 1.58235621e+00 7.95801103e-01 2.54562050e-01 -9.73653644e-02 2.66985565e-01 -4.55911666e-01 -1.08827591e+00 -5.37041366e-01 -8.69158506e-01 -4.20919806e-01 -1.58206180e-01 1.32902968e+00 -1.07786274e+00 -7.23685622e-01 9.16332185e-01 -9.35924113e-01 -6.86335146e-01 -3.30605954e-01 1.04735076e+00 -8.47077131e-01 3.46008927e-01 -6.71287656e-01 -5.63950121e-01 -1.08574188e+00 -1.14297032e+00 1.25036716e+00 1.94950312e-01 -4.99438286e-01 -9.86135840e-01 6.20712519e-01 4.12644148e-01 5.83485365e-01 -5.84940195e-01 7.65605032e-01 -5.45001864e-01 4.66772854e-01 -5.16673084e-03 3.10040146e-01 6.23900890e-01 8.24220836e-01 -9.15750384e-01 -1.15382278e+00 -2.38495916e-01 9.97865796e-01 -1.60178304e-01 5.01552582e-01 8.33269060e-01 8.19574177e-01 3.29113901e-02 -6.08855963e-01 5.32644391e-01 7.20490098e-01 7.66602576e-01 9.87592399e-01 3.96157473e-01 4.26200747e-01 -1.97046306e-02 -7.18817115e-02 3.83688688e-01 1.99504867e-01 5.08075476e-01 6.67571276e-02 3.29638213e-01 -1.87935904e-01 3.14017653e-01 1.05389357e+00 1.20465088e+00 1.71534851e-01 2.22442999e-01 -8.01229060e-01 3.89681101e-01 -1.42426896e+00 -1.04252660e+00 6.64384216e-02 1.82168782e+00 7.94325709e-01 6.34769648e-02 2.46223584e-01 3.45194906e-01 6.45720065e-01 -4.41963524e-01 -8.92760336e-01 -2.83559352e-01 3.23156089e-01 7.01340318e-01 4.36893292e-02 -9.45221558e-02 -5.72342932e-01 6.87282979e-01 6.46683645e+00 6.40109658e-01 -1.57365882e+00 8.13346148e-01 -2.91564941e-01 -4.80161041e-01 1.96537942e-01 -6.19322479e-01 -7.93152094e-01 1.14657497e+00 1.55336785e+00 6.91727474e-02 5.95521927e-01 6.59811199e-01 7.43670583e-01 -2.36653581e-01 -1.28151882e+00 1.80285573e+00 -5.17940521e-02 -8.19912493e-01 -6.84186876e-01 2.74202049e-01 7.19286427e-02 7.00422645e-01 -1.97507769e-01 3.92684549e-01 -7.00828552e-01 -7.71241605e-01 3.26425821e-01 7.16359794e-01 1.22776794e+00 -2.46721908e-01 5.65770805e-01 6.41700149e-01 -1.02643144e+00 -5.03808260e-01 -1.54317796e-01 -1.14100046e-01 2.46957302e-01 2.76568025e-01 -6.09527349e-01 -3.85499328e-01 9.68267560e-01 1.33781457e+00 -4.61754590e-01 1.07224715e+00 -5.17913438e-02 7.99481928e-01 -3.70395720e-01 -2.62126356e-01 -3.12251806e-01 -6.94592521e-02 3.51133436e-01 7.82935023e-01 6.44718707e-01 7.40719661e-02 -5.41396379e-01 8.65662277e-01 5.07215381e-01 -5.02969086e-01 -6.94162786e-01 -7.23676980e-02 9.43561569e-02 1.00409138e+00 -6.43863559e-01 8.35366100e-02 -2.84357578e-01 1.32333028e+00 -2.33272426e-02 -9.68401879e-02 -5.62868357e-01 -2.28706986e-01 4.79836851e-01 1.50211051e-01 -1.66447982e-01 -1.13590531e-01 -5.94135880e-01 -1.33141422e+00 1.25908747e-01 -6.05726182e-01 4.05960456e-02 -1.11806870e+00 -1.43181098e+00 8.64639878e-01 3.36630596e-03 -1.46383417e+00 -2.76136637e-01 -7.89082289e-01 -1.11108780e+00 6.57364786e-01 -9.64113295e-01 -5.72548091e-01 -4.05468047e-01 1.17594635e+00 7.80272782e-01 -7.50633717e-01 1.17971921e+00 4.79547501e-01 -5.17823756e-01 3.29887956e-01 5.88752888e-02 -2.62802124e-01 8.06055188e-01 -1.06949198e+00 -7.58979246e-02 3.31576884e-01 -2.69399017e-01 5.53121269e-01 3.04458618e-01 -4.74188417e-01 -1.05336761e+00 -6.54870331e-01 7.39286482e-01 -2.93785691e-01 6.08142376e-01 -3.63916248e-01 -6.11949682e-01 2.73070872e-01 4.34604794e-01 -3.99943948e-01 1.06309664e+00 -1.57952219e-01 5.53070784e-01 -6.65884435e-01 -1.20075023e+00 2.42316887e-01 1.02857220e+00 -8.90136838e-01 -1.30570054e+00 5.54345489e-01 6.26815259e-02 1.38725415e-01 -7.75402486e-01 2.91063875e-01 5.55206418e-01 -8.29448938e-01 3.61746609e-01 -1.29153609e-01 -4.59408760e-02 1.73186257e-01 9.75547079e-03 -1.56903696e+00 -5.64209819e-01 -5.76527119e-01 -9.29745734e-02 6.73078239e-01 1.57335699e-01 -9.00084615e-01 7.72668064e-01 6.01875067e-01 -7.18344808e-01 -5.86651087e-01 -1.29343545e+00 -7.17067122e-01 -4.06479947e-02 -5.30433416e-01 1.95396580e-02 2.50097993e-03 8.55374217e-01 7.92824268e-01 -8.75010043e-02 -3.01152728e-02 1.84999064e-01 -4.70698655e-01 -4.34249602e-02 -1.42170370e+00 -7.05653578e-02 -5.23935020e-01 -8.59194100e-01 -8.69877100e-01 4.65792000e-01 -1.26748657e+00 2.16355070e-01 -2.07947636e+00 4.40251052e-01 -9.65028554e-02 -6.66035831e-01 5.51552176e-01 2.41324142e-01 2.08116367e-01 -3.97350460e-01 5.06248176e-01 -3.38199854e-01 8.94518554e-01 1.17661357e+00 -4.59242642e-01 -4.94648337e-01 5.83783865e-01 -6.93820059e-01 6.70740068e-01 1.14309013e+00 -7.51686811e-01 -6.88650548e-01 -1.92708537e-01 -7.95226321e-02 2.36875489e-01 1.67451113e-01 -1.62709737e+00 6.10524952e-01 4.85832900e-01 3.48846436e-01 -3.90550971e-01 5.47712266e-01 -7.83919096e-01 -1.20502889e-01 7.70937264e-01 1.53240990e-02 -2.22500950e-01 2.26621583e-01 4.04562235e-01 -5.32911643e-02 -2.02199325e-01 7.62530029e-01 -1.64956018e-01 -7.55423486e-01 3.32927704e-01 -1.23279369e+00 6.71611577e-02 8.98145258e-01 -7.26496756e-01 -1.89275160e-01 -1.19759560e-01 -1.32381511e+00 -6.73948824e-02 -4.36161086e-02 4.45299447e-01 8.37840557e-01 -1.36932456e+00 -1.86173841e-01 7.52616465e-01 1.39875501e-01 -3.32801372e-01 2.54914552e-01 1.25947988e+00 -1.76022127e-01 4.89218503e-01 -8.96491826e-01 -1.06618226e+00 -1.04738712e+00 2.16766804e-01 6.58537567e-01 2.37592027e-01 -8.58425379e-01 7.65240073e-01 1.71940953e-01 1.34789959e-01 3.07522684e-01 -7.60895848e-01 -5.71436226e-01 2.12470666e-01 6.23935401e-01 2.73759216e-01 5.82835555e-01 -4.66933906e-01 -8.72349024e-01 5.69865048e-01 4.93153855e-02 -9.90012810e-02 1.52363658e+00 -1.98065698e-01 -1.25851378e-01 8.16167295e-01 1.46343958e+00 -4.80425507e-01 -7.28548944e-01 2.92394698e-01 -3.38116437e-01 4.05916452e-01 5.01306772e-01 -9.54713285e-01 -1.28625190e+00 1.19138050e+00 1.82368219e+00 7.89333060e-02 1.46610653e+00 3.40043843e-01 1.29880011e+00 5.25193870e-01 7.37474263e-01 -9.87829268e-01 1.24386534e-01 1.16582349e-01 8.40215027e-01 -1.18205512e+00 -3.32762599e-01 5.09713948e-01 -6.39584839e-01 1.21521401e+00 3.12898815e-01 -1.76190957e-01 1.13741028e+00 2.79515713e-01 7.57537708e-02 -5.06760418e-01 -4.37424719e-01 4.93140556e-02 2.20290333e-01 9.70323384e-01 1.84608057e-01 1.18501075e-01 -2.93855995e-01 1.32480597e+00 -4.15710479e-01 5.22724628e-01 1.99783996e-01 8.57906401e-01 -7.00129986e-01 -9.26687062e-01 -7.84865320e-02 1.06041670e+00 -3.87019306e-01 -1.60075083e-01 -2.09426787e-03 5.16359881e-02 1.14811905e-01 1.20832264e+00 1.64760992e-01 -6.96865320e-01 4.24574345e-01 2.79880643e-01 7.83184290e-01 -1.05457771e+00 -5.19441009e-01 7.37116709e-02 -4.16871339e-01 -5.88192523e-01 -6.14561081e-01 -5.45763195e-01 -1.34570193e+00 2.45229691e-01 -2.72760540e-01 2.22192407e-02 5.60427606e-01 1.14535534e+00 6.14634633e-01 6.68069065e-01 5.61223924e-01 -1.13774419e+00 -3.03964406e-01 -1.47514808e+00 -9.99594867e-01 -8.80219564e-02 6.82720184e-01 -9.00334001e-01 -6.31509840e-01 -7.54012400e-03]	[13.536161422729492, 3.466477394104004]
02da2dce-41d5-40a0-af68-5defa8d64f7a	black-box-dissector-towards-erasing-based	2105.00623	null	https://arxiv.org/abs/2105.00623v3	https://arxiv.org/pdf/2105.00623v3.pdf	Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack	Previous studies have verified that the functionality of black-box models can be stolen with full probability outputs. However, under the more practical hard-label setting, we observe that existing methods suffer from catastrophic performance degradation. We argue this is due to the lack of rich information in the probability prediction and the overfitting caused by hard labels. To this end, we propose a novel hard-label model stealing method termed \emph{black-box dissector}, which consists of two erasing-based modules. One is a CAM-driven erasing strategy that is designed to increase the information capacity hidden in hard labels from the victim model. The other is a random-erasing-based self-knowledge distillation module that utilizes soft labels from the substitute model to mitigate overfitting. Extensive experiments on four widely-used datasets consistently demonstrate that our method outperforms state-of-the-art methods, with an improvement of at most $8.27\%$. We also validate the effectiveness and practical potential of our method on real-world APIs and defense methods. Furthermore, our method promotes other downstream tasks, \emph{i.e.}, transfer adversarial attacks.	['Feiyue Huang', 'Yan Wang', 'Rongrong Ji', 'Yongjian Wu', 'Hong Liu', 'Jie Li', 'Yixu Wang']	2021-05-03	null	https://openreview.net/forum?id=5jaqt-Hsqir	https://openreview.net/pdf?id=5jaqt-Hsqir	neurips-2021-12	['self-knowledge-distillation']	['computer-vision']	[ 5.19766808e-01 2.02631578e-01 -4.12903309e-01 -1.47112787e-01 -1.05299926e+00 -9.05000031e-01 2.91510612e-01 -4.08465296e-01 -1.94724470e-01 7.37788916e-01 -3.83970201e-01 -7.33641148e-01 2.49229684e-01 -5.67370772e-01 -1.07272041e+00 -7.24360704e-01 6.88963756e-02 2.94947714e-01 3.66763920e-01 6.73386529e-02 4.00408916e-02 1.19436746e-02 -1.01530755e+00 3.07037741e-01 6.86621726e-01 1.01724505e+00 -3.54546189e-01 2.96146631e-01 8.11204389e-02 9.09398258e-01 -8.80960703e-01 -9.76785600e-01 4.61586297e-01 1.03416681e-01 -7.05838025e-01 -7.20992327e-01 1.04936562e-01 -5.88255167e-01 -4.78788316e-01 1.17803705e+00 4.53636587e-01 -3.70113701e-01 2.32103661e-01 -1.60445774e+00 -2.88657933e-01 1.16375959e+00 -4.65657771e-01 -3.04063976e-01 -9.33854878e-02 4.84122008e-01 8.21572304e-01 -3.82185876e-01 4.61675525e-01 1.10142243e+00 7.55188167e-01 8.66117477e-01 -1.42691910e+00 -1.45434999e+00 -1.43278673e-01 -4.43523787e-02 -1.44529092e+00 -4.23814505e-01 6.34043694e-01 -1.08592354e-01 8.74153435e-01 3.15530121e-01 -2.26949304e-01 1.60205817e+00 2.70845622e-01 5.81437171e-01 1.79759121e+00 -2.14418143e-01 3.01158726e-01 4.05196965e-01 3.23603243e-01 7.16493785e-01 3.31687778e-01 7.63179064e-01 -4.55522388e-01 -8.51106763e-01 -5.40076569e-02 4.21299078e-02 -2.13680416e-01 -9.95982289e-02 -7.14221597e-01 6.56057537e-01 1.04423061e-01 -2.25691259e-01 1.73654363e-01 6.05952263e-01 5.45150340e-01 2.52869666e-01 2.46755973e-01 2.98289895e-01 -7.13376760e-01 -3.79902005e-01 -8.64270389e-01 -6.59795478e-02 1.20916986e+00 9.96184587e-01 4.25365835e-01 -8.66606310e-02 -2.50272989e-01 2.94265628e-01 3.14661235e-01 7.49058485e-01 2.00639423e-02 -8.51849198e-01 4.23593730e-01 1.66547239e-01 -1.08951911e-01 -5.03632843e-01 7.59331277e-03 -4.52711672e-01 -4.13630992e-01 1.85160667e-01 4.05552715e-01 -2.74571717e-01 -7.95125246e-01 2.13857555e+00 2.21750751e-01 5.26068747e-01 -9.82785672e-02 3.93735379e-01 1.84410542e-01 4.76992279e-01 3.26960534e-01 4.05442789e-02 1.48703694e+00 -1.09417701e+00 -6.25403702e-01 -2.19486505e-01 6.35868371e-01 -7.07330644e-01 1.13348854e+00 5.94882667e-01 -9.72047925e-01 -1.95230260e-01 -1.09343910e+00 2.07714319e-01 -4.48113650e-01 -1.62203863e-01 7.50492811e-01 1.22995245e+00 -6.69217706e-01 4.47439790e-01 -7.80267715e-01 4.83255625e-01 6.47224903e-01 5.87026775e-01 -1.96602657e-01 1.69551164e-01 -1.28113019e+00 5.61820090e-01 3.24474394e-01 -4.27085072e-01 -1.26261771e+00 -8.84947717e-01 -6.49335146e-01 2.70324796e-01 7.83806622e-01 -3.30191135e-01 1.26360106e+00 -3.84630173e-01 -1.70916164e+00 6.59220457e-01 2.20264457e-02 -5.71491241e-01 4.22077656e-01 -1.75575837e-01 -4.04846519e-01 3.37150916e-02 -5.79787850e-01 5.18166244e-01 1.23704314e+00 -1.78539181e+00 -4.27556962e-01 -7.79693723e-02 2.85119742e-01 -6.65444255e-01 -6.69252396e-01 1.04443520e-01 -3.62638682e-01 -9.11986053e-01 -5.21200955e-01 -1.34916043e+00 1.40840873e-01 -3.75909150e-01 -8.45329463e-01 1.62772819e-01 1.04813325e+00 -6.74805582e-01 1.59404635e+00 -2.33156419e+00 -1.83795020e-01 4.30812418e-01 4.45852637e-01 6.51188433e-01 -1.62112832e-01 3.58787835e-01 7.84687921e-02 5.01213729e-01 -2.71670401e-01 -7.23856688e-01 4.04429644e-01 7.44783655e-02 -1.15428007e+00 2.12519795e-01 1.65009215e-01 1.03786552e+00 -7.16512918e-01 -4.02032107e-01 -1.63848564e-01 5.28500199e-01 -5.48716068e-01 2.86215574e-01 -4.88993764e-01 4.30474967e-01 -2.89970525e-02 8.36718500e-01 1.00433981e+00 -3.69904906e-01 3.62273663e-01 -5.04782163e-02 4.24165070e-01 6.26464963e-01 -8.35153639e-01 1.45646119e+00 -5.06319702e-01 8.65470320e-02 1.16169177e-01 -2.57478952e-01 5.38250923e-01 2.31315687e-01 -5.85706811e-03 -5.04056036e-01 4.23888475e-01 2.77172685e-01 -4.27839765e-03 -1.97774805e-02 3.97090107e-01 -5.95299974e-02 -3.91009897e-01 8.50803852e-01 -1.99611440e-01 1.23245222e-02 -3.98360312e-01 2.68524617e-01 1.51934838e+00 1.44327492e-01 -1.97747961e-01 1.39296129e-01 3.17081124e-01 -3.59867692e-01 6.87358975e-01 9.98412788e-01 -3.11340779e-01 -3.17375138e-02 6.81861579e-01 1.50414258e-01 -8.33847225e-01 -1.06742537e+00 -1.76681206e-01 1.07938874e+00 2.88186044e-01 -7.38629103e-01 -1.12926686e+00 -1.38509357e+00 2.10563555e-01 9.92025673e-01 -4.32007223e-01 -7.63676107e-01 -5.42488635e-01 -5.96837699e-01 1.40115213e+00 5.12956381e-01 5.29859841e-01 -7.02387810e-01 -2.66753405e-01 -8.28910917e-02 -8.99035037e-02 -1.28301144e+00 -4.41358894e-01 4.01361376e-01 -4.99632537e-01 -7.61305332e-01 -2.40710918e-02 -4.29782212e-01 5.55880129e-01 1.68018162e-01 7.71880448e-01 1.46966383e-01 -7.37054124e-02 -1.28172396e-03 -2.28652537e-01 -3.06794375e-01 -8.81487608e-01 3.51359457e-01 -8.41804966e-02 -2.93283135e-01 5.28505266e-01 -5.50739706e-01 -3.69828165e-01 6.20329916e-01 -1.12305927e+00 -2.32127681e-01 6.40907586e-01 1.06272221e+00 4.81113881e-01 3.91653925e-01 3.97733003e-01 -1.25863159e+00 4.57718402e-01 -6.74955547e-01 -8.98801804e-01 2.86108553e-01 -8.37627947e-01 3.04456919e-01 1.07139623e+00 -8.78698587e-01 -1.00179803e+00 -2.47524157e-01 -2.19834507e-01 -5.39723158e-01 -3.42138708e-02 -2.14403555e-01 -3.26847166e-01 -4.90435004e-01 3.20867389e-01 1.39434278e-01 -4.84725088e-02 -4.49996620e-01 5.00608087e-01 9.39218104e-01 4.44928586e-01 -8.81476700e-01 1.26807451e+00 6.23748004e-01 -3.10310815e-02 9.24974903e-02 -8.00376296e-01 7.46790767e-02 2.72005796e-01 2.76081681e-01 4.87786829e-01 -6.50170803e-01 -1.39991069e+00 8.19821954e-01 -9.11627293e-01 -7.57116020e-01 -2.01044247e-01 5.05931228e-02 -3.30469906e-01 6.36381269e-01 -9.97880101e-01 -8.92870784e-01 -6.64679587e-01 -1.51397121e+00 1.17087948e+00 4.60537337e-02 4.36348543e-02 -7.84991264e-01 -1.92493007e-01 7.67675996e-01 5.12601018e-01 -1.97473973e-01 1.20639837e+00 -1.00527489e+00 -7.16045260e-01 -3.65471631e-01 -2.08482474e-01 8.11653376e-01 -4.79734808e-01 -3.73295963e-01 -1.43263698e+00 -6.62080050e-01 2.01608941e-01 -6.81871474e-01 8.21747839e-01 -4.92472440e-01 1.69319785e+00 -4.00810659e-01 -5.02669573e-01 8.05193424e-01 1.17917109e+00 1.05429173e-01 7.17586040e-01 1.65715553e-02 6.31003857e-01 1.54546306e-01 4.47512984e-01 3.21296215e-01 2.27026433e-01 7.56712973e-01 6.17251217e-01 -7.55937770e-03 -1.25623733e-01 -6.29984975e-01 7.80945837e-01 6.76890433e-01 6.61247373e-01 -4.05625343e-01 -6.63898408e-01 -3.73757295e-02 -1.50807154e+00 -6.71743810e-01 1.39970377e-01 2.41572499e+00 1.32418072e+00 7.10687518e-01 -1.55463636e-01 1.91311359e-01 5.56176662e-01 1.13371693e-01 -5.56200981e-01 -5.15781760e-01 -1.51611853e-03 7.09563255e-01 1.14697015e+00 3.28555673e-01 -1.03023911e+00 1.24525976e+00 6.00315142e+00 1.57849050e+00 -9.18935478e-01 6.33892477e-01 4.91439372e-01 3.88823487e-02 -3.57169688e-01 4.92846072e-01 -1.24454057e+00 1.13228786e+00 1.11110222e+00 2.88056254e-01 9.48959053e-01 8.28480244e-01 -4.79661167e-01 1.23885177e-01 -1.04644179e+00 5.72695494e-01 1.21958151e-01 -9.63611186e-01 -3.86776119e-01 3.96652907e-01 6.86483026e-01 -3.56640399e-01 5.53980052e-01 6.98754489e-01 6.47663772e-01 -8.81056905e-01 7.69970953e-01 3.63620579e-01 1.10529423e+00 -7.36835897e-01 6.82319343e-01 4.11450475e-01 -7.46499836e-01 -3.36025983e-01 -9.92417801e-03 2.88783163e-01 2.17740670e-01 4.75382388e-01 -8.34400654e-01 2.25524411e-01 4.80877787e-01 -8.42493176e-02 -4.36037749e-01 5.30447423e-01 -7.41492331e-01 1.31275666e+00 -4.65986252e-01 2.52312452e-01 7.10815042e-02 4.50746357e-01 4.69526738e-01 1.08583522e+00 -1.16423130e-01 -2.37523243e-01 6.24561198e-02 1.11171710e+00 -5.56509495e-01 -5.72775185e-01 -4.13767874e-01 -2.68994331e-01 9.68292236e-01 1.31239414e+00 -1.91596836e-01 -2.24351093e-01 -2.27153212e-01 9.13889945e-01 2.65618354e-01 1.22761577e-01 -1.64490759e+00 -4.57980752e-01 5.97987115e-01 -2.87240185e-03 3.01743716e-01 -2.43706003e-01 -2.27320209e-01 -9.41407084e-01 -1.70193668e-02 -1.23351824e+00 3.15717638e-01 -3.80134821e-01 -1.35962284e+00 3.49153757e-01 -4.74905856e-02 -8.37324321e-01 7.01453462e-02 -5.02414584e-01 -4.19386983e-01 7.21261799e-01 -1.73627877e+00 -1.27158213e+00 4.65539247e-02 4.01565671e-01 -1.15380101e-01 -1.37245402e-01 8.81837845e-01 5.03601491e-01 -6.44101202e-01 1.61679900e+00 2.06708968e-01 -1.63621884e-02 9.89632308e-01 -9.53176975e-01 5.07299960e-01 7.39462972e-01 -2.60482132e-01 9.21383202e-01 1.88443765e-01 -8.62093985e-01 -1.57076418e+00 -1.01553333e+00 5.03883421e-01 -5.98886490e-01 9.22550917e-01 -8.66055071e-01 -7.66796708e-01 7.41797626e-01 -1.27771825e-01 -6.72537163e-02 1.15466762e+00 -3.79740298e-01 -1.14584696e+00 -3.12909135e-03 -1.46476603e+00 6.03842318e-01 1.05073321e+00 -6.97124600e-01 -2.16185436e-01 2.16814712e-01 1.24627459e+00 -4.06523198e-01 -9.72492814e-01 5.54318368e-01 5.12241066e-01 -5.75469315e-01 1.02721870e+00 -6.03720129e-01 1.92442641e-01 -1.74382001e-01 -2.20045134e-01 -7.83129573e-01 1.02439955e-01 -1.30898929e+00 -8.42760623e-01 1.40837133e+00 3.78359824e-01 -9.94857609e-01 7.59009659e-01 6.03419006e-01 1.41624033e-01 -5.58947206e-01 -9.14417803e-01 -1.13023555e+00 2.20632598e-01 -5.12599647e-01 8.75977039e-01 8.51978123e-01 3.55560053e-03 6.03762120e-02 -7.67051339e-01 2.58534312e-01 8.74164522e-01 -9.21532437e-02 9.33615744e-01 -6.99367642e-01 -8.33850801e-01 -1.07721798e-01 9.11227092e-02 -1.06442642e+00 6.66559219e-01 -9.36340392e-01 -4.96513881e-02 -3.54654849e-01 3.20361555e-01 -9.23433721e-01 -4.02755946e-01 1.02486920e+00 -3.14280391e-01 3.16760123e-01 3.84880155e-01 3.65261972e-01 -6.35911226e-01 2.35784441e-01 9.20952022e-01 -7.33376741e-02 2.09467281e-02 -1.24710709e-01 -8.01178873e-01 6.51201785e-01 8.98397565e-01 -1.05427945e+00 -2.60912180e-01 -2.68427193e-01 3.55604202e-01 -3.01930338e-01 5.30226827e-01 -9.53661680e-01 7.89148510e-02 1.55052152e-02 -3.77445847e-01 -1.26653984e-01 5.06318212e-01 -1.09551156e+00 1.84181944e-01 7.20870137e-01 -4.21740055e-01 -2.62870133e-01 3.00741732e-01 5.93037784e-01 4.55785453e-01 -3.55181545e-01 8.03262532e-01 3.42895269e-01 -2.84256965e-01 1.12420902e-01 6.50830939e-02 2.68276453e-01 1.30691791e+00 1.34407669e-01 -1.22527802e+00 -1.25107601e-01 -2.44857222e-01 2.89685056e-02 6.66370571e-01 2.85204172e-01 1.34863675e-01 -9.28894699e-01 -1.81510195e-01 4.75555658e-01 2.57190093e-02 -3.68161470e-01 9.58867446e-02 9.73612905e-01 -1.31332889e-01 1.93625838e-01 1.91567585e-01 -1.13729417e-01 -1.23248231e+00 8.61492336e-01 -3.46027650e-02 -6.92313313e-01 -3.49005550e-01 7.90315092e-01 -9.35243145e-02 -2.91482836e-01 6.05766535e-01 -3.06362845e-02 7.24202514e-01 -6.69651210e-01 4.40522701e-01 5.60981929e-01 -1.20159686e-01 -3.44469070e-01 -3.20189208e-01 1.60932839e-01 -3.57796431e-01 -8.12655911e-02 7.87756026e-01 2.78270930e-01 -2.09155411e-01 -1.08824536e-01 1.18328500e+00 5.37036419e-01 -1.24754977e+00 -3.95410061e-01 -3.16663027e-01 -5.62182426e-01 -2.35225949e-02 -1.36962664e+00 -9.81405675e-01 1.04053390e+00 5.38450241e-01 2.48182759e-01 1.01442575e+00 -1.39197126e-01 1.66236234e+00 3.75311196e-01 7.85483003e-01 -9.18370664e-01 -2.15734970e-02 3.54596466e-01 -3.36219743e-02 -1.03750157e+00 -3.53427798e-01 -7.67032206e-01 -5.22211313e-01 5.17762601e-01 5.52841127e-01 2.47881815e-01 6.05521917e-01 9.59166706e-01 -1.85463473e-01 1.44424438e-01 -7.72977054e-01 2.32717812e-01 -2.72086889e-01 6.07272208e-01 -3.69713157e-01 2.29276091e-01 -2.07514659e-01 1.10862851e+00 8.36337358e-03 8.68042037e-02 1.73076570e-01 1.30128121e+00 -1.23997211e-01 -1.65325868e+00 -4.55089003e-01 1.86090663e-01 -8.30604017e-01 -3.62708837e-01 -4.19067681e-01 4.71626073e-01 3.08075905e-01 1.10455143e+00 -3.84742409e-01 -1.02647662e+00 -3.28387730e-02 3.53818744e-01 2.18593583e-01 -4.41716373e-01 -1.10618079e+00 -2.79030323e-01 5.81241548e-02 -7.10170507e-01 3.73155385e-01 -1.04635097e-02 -1.35433745e+00 -8.18867266e-01 -7.18040705e-01 -1.50421914e-02 7.81001210e-01 6.05100572e-01 8.90938282e-01 4.55873579e-01 7.78998375e-01 -3.68035167e-01 -1.39019895e+00 -5.86505115e-01 -3.59496891e-01 4.92327690e-01 -1.02265939e-01 -7.69976616e-01 -6.95980549e-01 -1.24924719e-01]	[5.852485179901123, 7.664951801300049]
8d66d154-5e63-431d-b0e2-667e059c41a4	rescaling-egocentric-vision	2006.13256	null	https://arxiv.org/abs/2006.13256v4	https://arxiv.org/pdf/2006.13256v4.pdf	Rescaling Egocentric Vision	This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head-mounted cameras. Compared to its previous version, EPIC-KITCHENS-100 has been annotated using a novel pipeline that allows denser (54% more actions per minute) and more complete annotations of fine-grained actions (+128% more action segments). This collection enables new challenges such as action detection and evaluating the "test of time" - i.e. whether models trained on data collected in 2018 can generalise to new footage collected two years later. The dataset is aligned with 6 challenges: action recognition (full and weak supervision), action detection, action anticipation, cross-modal retrieval (from captions), as well as unsupervised domain adaptation for action recognition. For each challenge, we define the task, provide baselines and evaluation metrics	['Davide Moltisanti', 'Giovanni Maria Farinella', 'Michael Wray', 'Jian Ma', 'Will Price', 'Jonathan Munro', 'Toby Perrett', 'Hazel Doughty', 'Evangelos Kazakos', 'Antonino Furnari', 'Dima Damen']	2020-06-23	null	null	null	null	['action-anticipation']	['computer-vision']	[ 4.67153877e-01 3.44629884e-02 -3.25481147e-01 -4.04306531e-01 -7.71163642e-01 -5.09148777e-01 7.64744282e-01 -7.69591749e-01 -6.30827367e-01 5.69922268e-01 1.12029672e+00 5.60488820e-01 2.99194336e-01 -1.63919106e-02 -8.26879740e-01 -5.86847067e-01 -3.04233730e-01 4.22978014e-01 2.34093428e-01 1.44682840e-01 1.52653337e-01 2.73948967e-01 -1.63747787e+00 6.51325703e-01 -3.47853489e-02 9.58502710e-01 -9.55832303e-02 1.13386607e+00 8.12783957e-01 1.36469424e+00 -4.79582399e-01 -3.11247617e-01 3.90798926e-01 -3.05626422e-01 -1.13197613e+00 4.39736784e-01 1.05666721e+00 -1.05037677e+00 -9.03691769e-01 5.05515993e-01 5.26296318e-01 3.10585052e-01 4.39669400e-01 -1.59846234e+00 -5.67608058e-01 2.45283872e-01 -3.58300686e-01 5.21733701e-01 8.65121126e-01 7.99758792e-01 7.39036918e-01 -6.81691468e-01 1.06312084e+00 1.44614482e+00 6.16045952e-01 8.26389372e-01 -7.03028500e-01 -3.74759853e-01 2.62060255e-01 6.88189209e-01 -9.23475087e-01 -1.05486679e+00 1.96050629e-01 -5.88662624e-01 1.58975005e+00 -1.07763074e-01 9.71238792e-01 2.28938222e+00 5.90398833e-02 1.54212093e+00 6.18395030e-01 -1.13979504e-01 1.71104968e-01 -5.70498049e-01 -1.51710078e-01 3.51094514e-01 -2.59124070e-01 -8.35105106e-02 -9.93620872e-01 3.35232854e-01 7.12178349e-01 4.91610654e-02 -2.45894670e-01 -4.68183607e-01 -1.88744283e+00 1.92671984e-01 6.14497289e-02 1.56648140e-02 -6.30035341e-01 5.92883766e-01 1.05677414e+00 4.21428010e-02 2.91807324e-01 3.07862163e-01 -7.66091108e-01 -1.07982421e+00 -6.38276875e-01 4.46301043e-01 4.35892075e-01 1.26694930e+00 2.71267891e-01 3.17172892e-02 -7.31716931e-01 4.91884142e-01 3.04187331e-02 6.82760835e-01 6.04299605e-01 -1.56866968e+00 6.90072954e-01 2.68335670e-01 4.30358887e-01 -4.10961688e-01 -5.63050568e-01 1.52445897e-01 -2.52447098e-01 -2.01934949e-01 4.65436965e-01 -2.11637974e-01 -9.69626546e-01 1.74133778e+00 3.10036898e-01 4.99266058e-01 1.58663020e-01 1.05935884e+00 7.36907542e-01 2.32320264e-01 3.16372484e-01 4.57674079e-02 1.31904697e+00 -1.57460332e+00 -6.97564185e-01 -4.38046426e-01 7.96629548e-01 -3.17734122e-01 1.00935709e+00 4.62686718e-01 -1.02489150e+00 -6.88747227e-01 -6.88588619e-01 -2.46935070e-01 -3.54206264e-01 4.60953176e-01 7.76553273e-01 2.20329389e-01 -1.13400674e+00 3.41480941e-01 -1.09259760e+00 -8.94760191e-01 7.44347453e-01 -3.86854522e-02 -8.54949474e-01 -9.75020751e-02 -9.78467286e-01 9.07623231e-01 3.35014880e-01 3.65893357e-02 -1.53952289e+00 -5.54527998e-01 -1.17471206e+00 -3.71966660e-01 4.40761596e-01 -7.19933927e-01 1.65494001e+00 -1.30732965e+00 -1.53337383e+00 1.21276343e+00 -6.58893818e-03 -9.89208341e-01 7.55003691e-01 -9.26698387e-01 -4.87668812e-01 5.61197877e-01 5.08488297e-01 1.20826101e+00 8.91329110e-01 -1.59270495e-01 -6.79849625e-01 -3.88259232e-01 4.13432419e-01 3.95705014e-01 -1.42576937e-02 3.91565651e-01 -6.99660540e-01 -6.55669749e-01 -3.82282317e-01 -1.26726449e+00 6.51805252e-02 -1.07222259e-01 -2.09429830e-01 -1.90477550e-01 8.03149581e-01 -9.21990156e-01 7.10042953e-01 -2.24656749e+00 2.14964882e-01 -7.97499657e-01 -4.33894135e-02 2.32513666e-01 -4.30929363e-01 3.65118116e-01 -3.30006480e-01 -5.78018606e-01 4.89771441e-02 -5.43868184e-01 1.67243555e-01 3.20282072e-01 -2.92200446e-01 6.48405969e-01 2.84855932e-01 1.31388938e+00 -1.17792237e+00 -3.72968346e-01 5.71445584e-01 2.06826001e-01 -5.20013332e-01 1.39173865e-01 -1.55618146e-01 7.93104053e-01 -1.56420648e-01 1.18076372e+00 2.51589060e-01 -9.79013368e-02 -1.66778669e-01 -2.44321346e-01 1.41734928e-01 4.82798070e-02 -8.67715240e-01 2.24761510e+00 -1.18521765e-01 1.08838224e+00 -2.46531695e-01 -8.46236229e-01 9.54675302e-02 3.90650272e-01 9.31492329e-01 -7.39046872e-01 -1.18314341e-01 -3.71068418e-01 -5.35159767e-01 -1.07879257e+00 4.84021157e-01 5.27016699e-01 -3.39797497e-01 1.93550646e-01 4.98485595e-01 2.55148560e-01 5.93857288e-01 2.90633440e-01 1.75160182e+00 9.74022269e-01 3.16477150e-01 2.96548873e-01 4.35236901e-01 1.49077386e-01 5.99728286e-01 7.17400908e-01 -1.04293287e+00 8.58788371e-01 4.21182752e-01 -7.23238468e-01 -8.42093349e-01 -8.85898888e-01 2.13537365e-01 1.45599389e+00 -2.04512373e-01 -5.40679395e-01 -8.87791991e-01 -1.05185449e+00 -8.18165019e-02 4.22988921e-01 -9.67219174e-01 -9.47039872e-02 -6.50594473e-01 -1.92475542e-01 8.51373255e-01 1.07645941e+00 9.86934006e-01 -1.69234765e+00 -1.04858589e+00 5.83753064e-02 -5.59495747e-01 -1.75688577e+00 -5.31548262e-01 -2.39498869e-01 -5.91120064e-01 -1.53176200e+00 -9.30984139e-01 -2.49353036e-01 2.52360344e-01 2.92340845e-01 1.47301233e+00 -7.79243290e-01 -4.54830617e-01 1.41950727e+00 -6.87507272e-01 -3.84571135e-01 1.59515008e-01 -2.74394900e-01 3.67388010e-01 1.40330419e-01 8.62076521e-01 -4.17451650e-01 -8.22360039e-01 2.62036294e-01 -4.65336531e-01 4.37555909e-02 9.54375923e-01 5.45080006e-01 4.09423232e-01 -8.34666550e-01 2.96397656e-01 -3.65478992e-01 -2.22510383e-01 -4.61513966e-01 -2.13277325e-01 1.79017022e-01 1.14579290e-01 -3.67956251e-01 8.92159194e-02 -3.61804932e-01 -1.14382958e+00 5.26561558e-01 1.05201907e-01 -8.17795753e-01 -6.46160722e-01 -2.63535529e-01 -1.90976575e-01 2.70624846e-01 7.06825316e-01 3.84164900e-01 -2.09854797e-01 -3.61665249e-01 6.08722627e-01 5.68100989e-01 1.05613720e+00 -2.67081469e-01 2.36071110e-01 8.31610203e-01 -2.07818463e-01 -7.54678667e-01 -1.01988721e+00 -8.13040972e-01 -1.21872532e+00 -5.97740710e-01 1.48815703e+00 -1.61286819e+00 -6.64491475e-01 9.73443091e-01 -9.56946492e-01 -7.85491407e-01 -4.98314381e-01 7.07916617e-01 -1.28083289e+00 4.07777160e-01 -4.85056579e-01 -5.83733082e-01 -1.96570456e-01 -8.16160738e-01 1.73526680e+00 -4.88212798e-03 -4.55984592e-01 -6.68848515e-01 3.83831024e-01 9.55574453e-01 4.18658787e-03 6.41160548e-01 -3.20650071e-01 -4.13668275e-01 -4.89629388e-01 -2.65155017e-01 -1.00311294e-01 5.74673951e-01 -1.51945099e-01 -1.18779950e-01 -1.07408524e+00 -1.55075371e-01 -3.47328752e-01 -9.91558135e-01 9.69306350e-01 5.94352126e-01 1.04752111e+00 -2.42860243e-01 -2.00204745e-01 6.00245595e-01 6.61683619e-01 -3.80190136e-03 1.04600000e+00 5.85561335e-01 8.00712407e-01 3.96501124e-01 1.08893466e+00 7.31240749e-01 4.32097584e-01 7.91247904e-01 6.31012797e-01 4.01806712e-01 -2.21997112e-01 -1.25412330e-01 1.02185965e+00 1.53570129e-02 -4.57430214e-01 -3.75070516e-03 -7.58358598e-01 8.97912800e-01 -2.07859993e+00 -1.48675430e+00 -2.02725478e-03 1.87365806e+00 5.21191776e-01 -1.68292850e-01 4.89815980e-01 -2.32379109e-01 4.24290121e-01 5.82149386e-01 -9.04022753e-01 -6.11198656e-02 -1.48112714e-01 -2.19784632e-01 5.20311415e-01 -1.14080496e-01 -1.85123062e+00 1.02849567e+00 6.90634823e+00 3.17561805e-01 -6.72474265e-01 1.73640326e-01 3.05164903e-01 -7.03434706e-01 8.10244799e-01 -1.43552631e-01 -7.42207646e-01 5.21697879e-01 1.10652292e+00 4.16585803e-01 2.96642393e-01 1.23942065e+00 3.75527710e-01 -3.87765318e-01 -1.42972326e+00 1.32147694e+00 5.72180688e-01 -1.07194996e+00 -3.61749560e-01 -1.64083555e-01 8.71130884e-01 6.64138675e-01 -2.50873029e-01 8.95680368e-01 2.28997916e-01 -6.86866283e-01 9.35384691e-01 8.16120803e-01 8.00698817e-01 -1.46345556e-01 5.63506186e-01 6.44702390e-02 -1.04411435e+00 -3.04217607e-01 -1.48805261e-01 -2.91955262e-01 2.90978342e-01 -5.95982894e-02 -6.46632075e-01 3.69958997e-01 1.13983035e+00 1.82388377e+00 -9.26310778e-01 7.45716035e-01 -3.83333266e-01 3.44249904e-01 4.12417091e-02 4.12551194e-01 3.98980647e-01 6.90213293e-02 6.10426784e-01 1.45160556e+00 1.87497269e-02 4.39102203e-02 6.59093708e-02 -2.08859099e-03 6.02729507e-02 -4.12536770e-01 -8.49450111e-01 -2.27081567e-01 -1.00544803e-02 1.12233567e+00 -2.52345711e-01 -7.33784616e-01 -5.93792021e-01 1.57551849e+00 1.80015296e-01 4.75045592e-01 -1.21201289e+00 1.04894497e-01 1.04605782e+00 -1.07907727e-01 3.69662464e-01 -9.09344330e-02 4.29610461e-01 -1.48624027e+00 1.58006206e-01 -1.04674959e+00 7.02505291e-01 -1.41643715e+00 -9.07528996e-01 2.07336210e-02 2.70491898e-01 -1.60250878e+00 -7.56772459e-01 -7.12487400e-01 -2.36856103e-01 1.10228792e-01 -1.11205566e+00 -1.42448413e+00 -6.59717798e-01 8.68910670e-01 1.11162817e+00 -1.90550119e-01 7.62221396e-01 3.26059043e-01 -6.87955081e-01 2.67004877e-01 -2.04504907e-01 4.02672410e-01 1.17459905e+00 -1.25919878e+00 6.20593846e-01 8.82004201e-01 2.74389625e-01 7.34797418e-02 5.60459435e-01 -4.05044854e-01 -1.44029975e+00 -1.29171455e+00 6.40091598e-01 -1.38146091e+00 6.89179420e-01 -3.25601548e-01 -1.20551847e-01 1.43023551e+00 2.39348292e-01 3.10972363e-01 4.07208741e-01 -1.83383539e-01 -3.37037295e-01 7.65148178e-02 -8.35598826e-01 6.45793438e-01 1.76862681e+00 -5.43185532e-01 -6.95410013e-01 8.48851085e-01 4.11842495e-01 -6.37304723e-01 -7.05088496e-01 3.65482420e-01 9.48293626e-01 -1.15526628e+00 1.04341531e+00 -9.66995358e-01 6.36035144e-01 -1.96733803e-01 -1.97611853e-01 -8.17108095e-01 -2.81333447e-01 -6.28795862e-01 -6.51999950e-01 8.54922831e-01 -2.44764909e-01 -1.19351529e-01 7.81569541e-01 4.58455712e-01 -4.48539257e-01 -4.20529693e-01 -1.01073933e+00 -8.88664782e-01 -6.80372536e-01 -7.52398789e-01 1.21399820e-01 7.73378551e-01 -1.62775591e-01 1.29344091e-01 -7.88719475e-01 -1.58538803e-01 3.70960414e-01 -3.58515501e-01 1.41711605e+00 -6.71658695e-01 -2.94193357e-01 -1.82498828e-01 -1.05295217e+00 -1.37281573e+00 2.68608212e-01 -2.07053661e-01 -8.77559837e-03 -1.52017391e+00 3.18398505e-01 7.09639132e-01 -1.15997851e-01 8.28753829e-01 1.15184046e-01 5.45724809e-01 1.23904012e-01 2.71760821e-01 -1.53787637e+00 6.40463829e-01 1.00763857e+00 -1.16387688e-01 2.01514482e-01 -1.64438933e-01 -1.77628100e-01 9.47511971e-01 3.28101844e-01 -7.07760975e-02 -3.71284693e-01 -5.12241125e-01 -8.52624699e-02 -1.21198386e-01 7.72224903e-01 -1.48416603e+00 -6.12311587e-02 -1.70800507e-01 5.76028764e-01 -8.21756363e-01 7.11401165e-01 -5.75071514e-01 1.45658348e-02 2.58406520e-01 -3.48205775e-01 -6.44779652e-02 1.62285373e-01 8.38938475e-01 -1.00959755e-01 2.01727539e-01 2.95314372e-01 -3.42837065e-01 -1.57910132e+00 2.29265332e-01 -4.07885462e-01 3.39757770e-01 1.44213688e+00 -4.25406128e-01 -3.83299500e-01 -5.15539527e-01 -1.12874305e+00 2.96336561e-01 3.80231142e-01 9.03022349e-01 2.85524845e-01 -1.51421773e+00 -7.19511211e-01 -9.51891541e-02 6.74861610e-01 -2.46852875e-01 7.20600426e-01 1.20604897e+00 -4.68173772e-01 7.53720582e-01 -6.23144746e-01 -7.26389468e-01 -1.29161406e+00 4.82947707e-01 1.86084837e-01 -1.94412649e-01 -8.26852858e-01 9.94565964e-01 1.45748764e-01 -1.23913296e-01 3.79529595e-01 -4.36571270e-01 -3.26968223e-01 2.83295870e-01 8.49171877e-01 6.69322252e-01 -2.79822320e-01 -9.38102722e-01 -7.36228824e-01 3.98394853e-01 1.85823947e-01 -1.78415671e-01 1.23108435e+00 -2.47683287e-01 3.07893336e-01 4.81337965e-01 1.08837903e+00 -5.54152906e-01 -2.08526444e+00 -7.45511204e-02 -2.13699579e-01 -6.70363307e-01 -3.62555772e-01 -8.59083414e-01 -8.12886536e-01 6.44827664e-01 7.50556886e-01 -4.30048615e-01 1.11479723e+00 1.23918958e-01 8.00415576e-01 6.38174415e-01 4.61987644e-01 -1.52390611e+00 6.38028920e-01 7.18175054e-01 1.16730618e+00 -1.60100853e+00 -5.34201413e-03 2.49023601e-01 -1.13486314e+00 8.96240830e-01 8.78508687e-01 -1.56886280e-01 1.29626751e-01 -3.40630263e-01 -2.90702209e-02 -2.68588185e-01 -8.20942998e-01 -3.89887691e-01 9.12526622e-02 9.00391459e-01 3.33514102e-02 -2.15405840e-02 2.45285571e-01 3.59778494e-01 7.16992244e-02 2.32279986e-01 4.65591431e-01 1.06218743e+00 5.24401218e-02 -3.37896585e-01 -9.72633511e-02 1.71499461e-01 -2.98646837e-01 2.29354948e-01 -5.40516734e-01 7.58466303e-01 1.79711953e-01 8.84875536e-01 2.85638601e-01 -2.67581522e-01 5.31870008e-01 3.20303530e-01 6.07704759e-01 -5.40319264e-01 -2.38655522e-01 -2.88450211e-01 4.77910191e-01 -1.54748535e+00 -1.02422047e+00 -1.22614634e+00 -7.75519192e-01 1.00917511e-01 3.61000896e-01 -6.10887766e-01 4.31015611e-01 9.89951253e-01 6.85644090e-01 5.46109617e-01 2.31156513e-01 -1.41638303e+00 -3.25010151e-01 -1.40344512e+00 -3.50324035e-01 6.58795357e-01 2.20827058e-01 -8.04536283e-01 -4.30119365e-01 6.58776462e-01]	[8.242668151855469, 0.5423344969749451]
a36e5427-4082-4296-9a9f-8a4101c2b294	automatic-speech-disentanglement-for-voice	2306.12259	null	https://arxiv.org/abs/2306.12259v1	https://arxiv.org/pdf/2306.12259v1.pdf	Automatic Speech Disentanglement for Voice Conversion using Rank Module and Speech Augmentation	Voice Conversion (VC) converts the voice of a source speech to that of a target while maintaining the source's content. Speech can be mainly decomposed into four components: content, timbre, rhythm and pitch. Unfortunately, most related works only take into account content and timbre, which results in less natural speech. Some recent works are able to disentangle speech into several components, but they require laborious bottleneck tuning or various hand-crafted features, each assumed to contain disentangled speech information. In this paper, we propose a VC model that can automatically disentangle speech into four components using only two augmentation functions, without the requirement of multiple hand-crafted features or laborious bottleneck tuning. The proposed model is straightforward yet efficient, and the empirical results demonstrate that our model can achieve a better performance than the baseline, regarding disentanglement effectiveness and speech naturalness.	['Ning Chen', 'Shijun Wang', 'Zhonghua Liu']	2023-06-21	null	null	null	null	['voice-conversion', 'disentanglement', 'voice-conversion']	['audio', 'methodology', 'speech']	[-3.73495137e-03 -1.56616181e-01 -1.77664384e-01 -9.29833278e-02 -9.18925881e-01 -8.64309669e-01 6.55732334e-01 -3.02175730e-01 -2.31596738e-01 5.19649327e-01 4.97705370e-01 -5.36500931e-01 3.23270261e-01 -5.07151783e-01 -2.19300315e-01 -6.89597011e-01 2.93249547e-01 1.07630156e-02 5.36828721e-03 -1.96011126e-01 -2.48762876e-01 2.43759155e-01 -1.55675137e+00 -1.32468387e-01 9.73638952e-01 9.03320968e-01 2.00584367e-01 1.01886511e+00 -8.93194228e-03 5.17325997e-01 -8.94634426e-01 -2.23389626e-01 9.19269398e-02 -7.13547587e-01 -4.66423213e-01 8.15299600e-02 1.69474289e-01 -2.21176937e-01 -3.14187497e-01 1.07209909e+00 8.00296783e-01 8.50815549e-02 5.30069351e-01 -1.09502840e+00 -6.75695002e-01 7.32986212e-01 -2.14302525e-01 1.77180603e-01 2.96190977e-01 2.19959542e-01 1.15951931e+00 -8.23584735e-01 -2.24998936e-01 1.40115273e+00 2.57680565e-01 6.49132133e-01 -1.40105474e+00 -1.11562765e+00 1.35166243e-01 1.41665772e-01 -1.20957851e+00 -9.75424409e-01 1.01266491e+00 -3.25003594e-01 7.27486491e-01 7.53977716e-01 6.58937335e-01 1.28538907e+00 -3.27000499e-01 5.93211770e-01 1.14365590e+00 -3.86912763e-01 1.18947640e-01 2.44500056e-01 7.72239342e-02 4.64728385e-01 -3.12919468e-02 3.32410991e-01 -5.07929265e-01 -6.40498549e-02 6.93714082e-01 -4.14551198e-01 -7.38008440e-01 -1.92678496e-01 -1.28346765e+00 7.05681860e-01 -4.27718507e-03 1.57426462e-01 -1.65017247e-02 -2.34916404e-01 4.10828620e-01 4.05357599e-01 3.05821061e-01 4.85365748e-01 -3.27239573e-01 -4.17905807e-01 -7.80043721e-01 -5.66096529e-02 8.61410737e-01 1.12144780e+00 4.38737661e-01 6.16593421e-01 -2.25376338e-01 1.07368815e+00 3.05678874e-01 7.07919478e-01 8.64413559e-01 -7.41141438e-01 6.36364162e-01 8.91975537e-02 1.52465119e-03 -8.76227200e-01 -1.84416667e-01 -4.09237236e-01 -8.52944732e-01 7.99391195e-02 1.51124015e-01 -4.28140670e-01 -7.84858227e-01 2.00697708e+00 1.59452155e-01 3.00245076e-01 1.42375514e-01 1.11183572e+00 9.81494904e-01 7.40402579e-01 -1.71816185e-01 -4.86736298e-01 1.57412708e+00 -1.37757778e+00 -1.13824880e+00 -3.03557068e-01 -1.66977420e-01 -1.06455004e+00 1.48513150e+00 3.71192932e-01 -1.11136425e+00 -7.28796780e-01 -1.43915546e+00 -6.86111450e-02 4.54533212e-02 4.83359337e-01 5.84095895e-01 1.11149335e+00 -7.15238929e-01 2.13437334e-01 -6.17986679e-01 3.81063044e-01 -4.78539430e-02 3.08087379e-01 -3.99566084e-01 4.41596329e-01 -1.35082364e+00 5.77301562e-01 8.99030045e-02 9.98136029e-02 -9.94030356e-01 -5.12735009e-01 -9.50414717e-01 2.94692487e-01 5.05369365e-01 -6.70532644e-01 1.48648739e+00 -7.88138330e-01 -2.28846526e+00 2.55742490e-01 -1.93446174e-01 1.00497864e-01 4.57396060e-01 -2.76157171e-01 -8.47394109e-01 -1.03970714e-01 -2.80960858e-01 1.76049858e-01 1.31039667e+00 -1.13701952e+00 -3.11374545e-01 -8.32967684e-02 -9.53469723e-02 2.02292874e-01 -7.19501674e-01 1.94182042e-02 -6.45148873e-01 -1.02726150e+00 1.30971000e-01 -9.16286647e-01 2.57079780e-01 -3.73236567e-01 -7.32190728e-01 4.06113565e-02 5.98930776e-01 -6.66390061e-01 1.42791712e+00 -2.31980991e+00 3.76535594e-01 -3.29629272e-01 4.06605393e-01 4.63608623e-01 -3.58950615e-01 2.37441063e-01 -1.49038464e-01 2.91172236e-01 -1.16367768e-02 -7.91374028e-01 4.46288958e-02 -9.58824938e-04 -4.71739978e-01 3.35002333e-01 1.01831175e-01 5.35563409e-01 -8.79147589e-01 -3.42299998e-01 2.13910013e-01 5.46348751e-01 -6.31841123e-01 5.45840085e-01 1.08826220e-01 4.70890880e-01 -1.22736312e-01 2.03416824e-01 7.40265965e-01 1.85215279e-01 2.19470024e-01 -3.01666021e-01 -2.10182950e-01 9.86811280e-01 -1.05285358e+00 1.44345570e+00 -6.67326450e-01 8.56160462e-01 2.93824434e-01 -5.14809489e-01 1.01816559e+00 7.67942488e-01 4.57675420e-02 -3.62070262e-01 2.50396430e-01 1.39217809e-01 3.20025742e-01 -4.78897750e-01 3.06407511e-01 -3.21056008e-01 -1.10751987e-02 4.33402807e-01 5.74573129e-02 -5.71112037e-01 -2.53934532e-01 -2.33707428e-01 7.58348465e-01 -3.67360294e-01 3.65895897e-01 3.36356983e-02 7.07975626e-01 -6.14014626e-01 7.02196121e-01 3.03938776e-01 -3.90176535e-01 8.17969799e-01 4.11711365e-01 3.05169404e-01 -8.50714147e-01 -1.27050078e+00 1.95516899e-01 9.43291068e-01 1.67101696e-01 -4.98160243e-01 -7.64895737e-01 -3.52080137e-01 -2.74123222e-01 7.89137959e-01 -2.99073547e-01 -4.10808146e-01 -5.84347785e-01 -3.99186432e-01 9.45881784e-01 4.29800779e-01 2.46168137e-01 -8.43373179e-01 -9.12753716e-02 -5.19125164e-02 -5.13332844e-01 -1.12206256e+00 -1.22103846e+00 3.09064472e-03 -5.43265939e-01 -7.19257593e-01 -6.12728655e-01 -7.63606131e-01 2.68111140e-01 6.63564205e-01 6.85171843e-01 -2.74332076e-01 6.58857673e-02 -2.54341781e-01 -3.62634093e-01 -3.87847275e-01 -5.51822424e-01 1.35899216e-01 2.75942147e-01 1.38483301e-01 1.48711698e-02 -8.85968387e-01 -4.39603835e-01 4.48902220e-01 -7.07491934e-01 2.26762682e-01 4.24956292e-01 8.31099331e-01 1.57290146e-01 1.07473187e-01 5.27199149e-01 -5.33849180e-01 1.00378788e+00 -1.59386143e-01 -3.04826349e-01 -1.32516697e-01 -5.70750356e-01 1.46900058e-01 9.65165734e-01 -8.85560632e-01 -1.00788033e+00 -1.78718075e-01 -1.59102291e-01 -6.47071183e-01 -1.42520308e-01 2.45551199e-01 -7.60298789e-01 3.05741817e-01 4.19007003e-01 3.73465002e-01 1.05813168e-01 -7.25365996e-01 6.10241830e-01 1.08385301e+00 6.34419739e-01 -4.17054296e-01 9.86421168e-01 -5.48112765e-02 -5.32193363e-01 -9.21282887e-01 -6.36057198e-01 -2.31497601e-01 -4.72342700e-01 1.64034829e-01 5.45967579e-01 -9.78295445e-01 -7.66437054e-01 3.50263059e-01 -1.25497055e+00 1.06572710e-01 -1.17020048e-01 7.72068501e-01 -5.54602027e-01 4.95552629e-01 -5.74544907e-01 -8.32395971e-01 -2.50615329e-01 -1.32926250e+00 9.14830804e-01 2.12582219e-02 -2.32404217e-01 -5.94288766e-01 5.53485453e-02 6.67655289e-01 4.32316989e-01 -2.04084396e-01 9.66366708e-01 -5.50280094e-01 -1.83016390e-01 -9.36858729e-02 2.13196296e-02 7.00388730e-01 7.41972744e-01 7.86537826e-02 -1.36225760e+00 -3.36904973e-01 2.42356092e-01 -1.42483070e-01 7.85273492e-01 -1.10368602e-01 9.00174201e-01 -7.78521657e-01 1.79333314e-01 6.70009851e-01 6.35586202e-01 3.18732470e-01 3.43317598e-01 -2.12008908e-01 7.48103201e-01 6.19802952e-01 2.23774284e-01 3.07356924e-01 3.71012896e-01 8.59373152e-01 2.69567043e-01 -6.29829615e-02 -4.99828160e-01 -4.19749647e-01 6.94216251e-01 1.62254107e+00 -2.22416390e-02 -3.77765089e-01 -3.76710564e-01 4.42274272e-01 -1.35411334e+00 -9.79390025e-01 1.44296899e-01 2.18773580e+00 1.26538038e+00 1.66425243e-01 2.60981470e-01 6.56122267e-01 6.55212402e-01 4.87674534e-01 -5.04795730e-01 -3.46318543e-01 1.17194444e-01 1.05080470e-01 -7.18260631e-02 8.24344575e-01 -9.66499686e-01 9.08835351e-01 6.61440563e+00 8.86950314e-01 -1.46782422e+00 4.62186895e-02 4.77155996e-03 -3.39067638e-01 -5.88808656e-01 -2.08974376e-01 -3.51007998e-01 4.55569088e-01 8.48363101e-01 -3.75786126e-01 7.54848123e-01 5.99066257e-01 4.03451085e-01 4.80550110e-01 -1.23816359e+00 1.16659749e+00 2.91141924e-02 -7.39753127e-01 4.17026952e-02 -1.51224285e-01 1.62378401e-01 -4.18060809e-01 3.18304151e-01 3.69606346e-01 7.00536519e-02 -1.11107671e+00 1.08736122e+00 3.55640762e-02 1.01024902e+00 -6.82368457e-01 2.69502014e-01 4.06690776e-01 -1.25662386e+00 4.02824767e-02 -6.17429689e-02 -1.37943044e-01 4.15690690e-02 3.86041313e-01 -9.06656027e-01 4.81274813e-01 1.47708744e-01 2.80505091e-01 -1.94294840e-01 6.86210871e-01 -5.46150446e-01 9.50003266e-01 1.60916746e-01 -1.81990638e-01 -3.35602641e-01 -7.49899372e-02 9.36976492e-01 1.09948826e+00 2.12925330e-01 -1.34887905e-05 1.64499402e-01 8.71688366e-01 -3.48540209e-02 1.32910296e-01 -2.23349214e-01 -4.24081624e-01 9.14195359e-01 1.18833828e+00 -1.30709231e-01 -1.83288693e-01 -4.16259021e-01 1.01896870e+00 1.13101006e-01 3.62084597e-01 -8.83314908e-01 -6.24615073e-01 1.19769919e+00 -2.31385559e-01 2.08652288e-01 -4.54270571e-01 -2.13273749e-01 -1.42384040e+00 -1.75453667e-02 -1.21339536e+00 -2.50153244e-01 -6.07703567e-01 -1.18030536e+00 1.10208249e+00 -3.70898992e-01 -1.33806694e+00 -3.71065468e-01 -3.58569771e-01 -4.29176748e-01 1.14919734e+00 -1.44454098e+00 -9.10776913e-01 -2.96594232e-01 5.70232213e-01 8.18943918e-01 -2.28334263e-01 1.10931277e+00 3.71633083e-01 -9.52825606e-01 1.06028378e+00 -1.97452590e-01 1.68073386e-01 7.50694275e-01 -1.28818345e+00 5.49339235e-01 6.72528744e-01 2.43246078e-01 6.76394761e-01 8.78892839e-01 -1.14852741e-01 -1.27371168e+00 -8.44074607e-01 8.67059708e-01 -2.34588519e-01 6.79225624e-01 -7.27440357e-01 -6.69970930e-01 3.97130460e-01 2.92071104e-01 3.18885222e-02 9.71762538e-01 1.21436596e-01 -6.96610093e-01 -1.70632929e-01 -7.18673110e-01 8.81494761e-01 7.99042106e-01 -9.99923229e-01 -7.12376297e-01 -2.61439770e-01 1.28477645e+00 -3.51867348e-01 -5.79536319e-01 1.34758562e-01 7.07098782e-01 -8.72949541e-01 9.89968479e-01 -5.63824236e-01 1.19267754e-01 -3.94943416e-01 -1.32720858e-01 -1.63117290e+00 -4.15918350e-01 -1.00902975e+00 -2.72614807e-01 1.47366238e+00 4.90819842e-01 -7.19598711e-01 2.10964456e-01 2.76365995e-01 -2.42216572e-01 -3.15214247e-01 -9.05591488e-01 -1.01644742e+00 -2.58092000e-03 -5.89505911e-01 8.70208740e-01 9.57290292e-01 1.04094878e-01 8.96586537e-01 -6.25061512e-01 3.86645824e-01 6.31964132e-02 2.51763254e-01 8.30262065e-01 -1.17731297e+00 -5.88718057e-01 -5.83547056e-01 -2.69415453e-02 -1.16866231e+00 2.18446985e-01 -6.57112122e-01 2.48552740e-01 -8.97878468e-01 3.05679254e-02 -4.09160197e-01 -1.75708488e-01 4.27525848e-01 -4.68408167e-01 -8.68252739e-02 4.33109522e-01 2.23480895e-01 3.46878022e-02 9.65207815e-01 1.49769604e+00 -3.09583902e-01 -4.14912641e-01 3.52909476e-01 -9.32587922e-01 5.56474924e-01 7.85876751e-01 -3.60662341e-01 -7.81870782e-01 -5.00790179e-01 -3.55474055e-01 3.73198718e-01 1.32722184e-01 -7.32712150e-01 8.15331116e-02 -2.58946508e-01 -1.22831486e-01 -1.03875682e-01 8.07598531e-01 -6.59536362e-01 1.56746984e-01 1.52713388e-01 -4.32831973e-01 2.05713790e-02 3.54218781e-01 5.75453460e-01 -4.44725960e-01 -6.36448339e-02 6.20480180e-01 2.77293116e-01 -8.02556127e-02 1.77204713e-01 -4.64234799e-01 -8.74493569e-02 6.70604646e-01 1.22069381e-01 -2.17366174e-01 -6.11252427e-01 -6.83223546e-01 -1.81072026e-01 1.04028866e-01 8.42738926e-01 5.30017734e-01 -1.46588671e+00 -6.57602668e-01 5.68743408e-01 -1.54697776e-01 -2.75867760e-01 1.01934887e-01 5.18035948e-01 -9.91266742e-02 5.54943860e-01 1.16147541e-01 -2.20380723e-01 -1.45735848e+00 7.64682114e-01 2.80625343e-01 2.03352496e-02 -3.24241191e-01 7.77438045e-01 2.69938290e-01 -5.73732138e-01 3.30973148e-01 -3.73772413e-01 -2.67673790e-01 1.16015889e-01 5.85365713e-01 4.59878802e-01 -4.13564928e-02 -7.29233265e-01 -3.44782740e-01 4.89969820e-01 2.26383492e-01 -5.07309854e-01 9.06558156e-01 -2.54251689e-01 6.76941201e-02 5.85320652e-01 1.30869639e+00 8.19317520e-01 -1.13087368e+00 -2.17098519e-01 -4.69800115e-01 -5.85767150e-01 2.40922511e-01 -6.86580181e-01 -1.10165203e+00 1.10620463e+00 3.05054456e-01 4.13219541e-01 1.35423589e+00 -2.41911307e-01 8.83449078e-01 5.82926907e-02 1.58580929e-01 -7.46793747e-01 3.00961256e-01 4.43708241e-01 1.11960304e+00 -9.41033661e-01 -3.32025766e-01 -9.31324363e-01 -7.08299577e-01 1.00290191e+00 5.52172601e-01 2.48350769e-01 7.36289978e-01 3.91878843e-01 2.95438588e-01 3.83020699e-01 -8.24505627e-01 -2.26170123e-01 5.99662185e-01 6.18632078e-01 5.99666774e-01 4.53829139e-01 -1.61162630e-01 1.09347188e+00 -8.86359036e-01 -5.81867337e-01 4.30825114e-01 2.12642878e-01 -3.29436094e-01 -1.22136784e+00 -4.07636464e-01 -2.36322042e-02 -3.93817782e-01 -3.06376159e-01 -4.80457634e-01 5.31534076e-01 1.11407170e-03 1.49216306e+00 8.08515996e-02 -8.42092991e-01 6.26930416e-01 -4.86007631e-02 3.08548838e-01 -7.46774077e-01 -4.07284617e-01 4.57714111e-01 2.17636690e-01 -1.79672331e-01 -7.34834000e-02 -5.11663020e-01 -9.90567029e-01 -3.33629489e-01 -7.77744889e-01 2.97859997e-01 4.94291633e-01 7.42211640e-01 2.98309684e-01 8.28433990e-01 1.11304545e+00 -6.85516775e-01 -8.50413144e-01 -1.28094578e+00 -5.62415063e-01 1.28552973e-01 1.00322926e+00 -6.14006937e-01 -5.37422240e-01 -1.13239624e-02]	[14.934476852416992, 6.437119483947754]
11b100fb-77a0-4ec3-b21e-1235523e0b8b	predicting-emotion-from-music-videos	2202.10453	null	https://arxiv.org/abs/2202.10453v1	https://arxiv.org/pdf/2202.10453v1.pdf	Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses	Although media content is increasingly produced, distributed, and consumed in multiple combinations of modalities, how individual modalities contribute to the perceived emotion of a media item remains poorly understood. In this paper we present MusicVideos (MuVi), a novel dataset for affective multimedia content analysis to study how the auditory and visual modalities contribute to the perceived emotion of media. The data were collected by presenting music videos to participants in three conditions: music, visual, and audiovisual. Participants annotated the music videos for valence and arousal over time, as well as the overall emotion conveyed. We present detailed descriptive statistics for key measures in the dataset and the results of feature importance analyses for each condition. Finally, we propose a novel transfer learning architecture to train Predictive models Augmented with Isolated modality Ratings (PAIR) and demonstrate the potential of isolated modality ratings for enhancing multimodal emotion recognition. Our results suggest that perceptions of arousal are influenced primarily by auditory information, while perceptions of valence are more subjective and can be influenced by both visual and auditory information. The dataset is made publicly available.	['Kat Agres', 'Gemma Roig', 'Dorien Herremans', 'Dimos Makris', 'Phoebe Chua']	2022-02-19	null	null	null	null	['multimodal-emotion-recognition', 'multimodal-emotion-recognition']	['computer-vision', 'speech']	[ 4.45709080e-02 -4.38584179e-01 -2.16536641e-01 -2.97480643e-01 -6.82140648e-01 -7.04967976e-01 5.06774366e-01 5.63456655e-01 -4.51792508e-01 1.98734283e-01 7.97641695e-01 5.36551952e-01 9.97234657e-02 -4.57811266e-01 -4.92876679e-01 -4.95687902e-01 -5.10768332e-02 -4.57293838e-01 -4.82735574e-01 -1.63126558e-01 3.03153634e-01 3.99323367e-02 -2.12986374e+00 8.60965848e-01 2.94484466e-01 1.65654755e+00 -1.39922976e-01 7.87003160e-01 -1.31698444e-01 8.95159245e-01 -5.36642849e-01 -2.55859196e-01 -1.90938041e-01 -5.16356707e-01 -4.12673950e-01 1.82375476e-01 4.70856547e-01 -2.37894386e-01 -5.29226251e-02 7.09004343e-01 6.55841291e-01 3.94182771e-01 8.45822752e-01 -1.50118899e+00 -5.09402096e-01 6.78383768e-01 -3.23500037e-01 3.32146995e-02 8.15436065e-01 -9.60348770e-02 1.10062766e+00 -1.01001525e+00 5.30848444e-01 9.96609092e-01 4.34741497e-01 2.60538369e-01 -9.65653241e-01 -7.04858005e-01 1.35489792e-01 6.68426216e-01 -1.10695505e+00 -5.53060353e-01 1.01217198e+00 -7.73476243e-01 7.73022711e-01 4.33670729e-01 1.05997300e+00 1.38985419e+00 -1.67404953e-02 7.33813405e-01 1.03876686e+00 -2.68636614e-01 1.65289372e-01 4.91379738e-01 -1.76874891e-01 2.17635855e-01 -5.94692290e-01 -1.64803341e-01 -1.17128730e+00 -1.35485217e-01 2.47909471e-01 -1.76209569e-01 -1.69537917e-01 -7.49155954e-02 -1.21439564e+00 7.44619429e-01 1.98900670e-01 1.06151126e-01 -7.08172679e-01 2.45659903e-01 8.14857244e-01 4.43303317e-01 5.35923302e-01 3.03674459e-01 -3.84064376e-01 -8.22551608e-01 -5.98819435e-01 -2.67183006e-01 5.01855016e-01 4.39893454e-01 5.20797312e-01 2.40860343e-01 -3.05097461e-01 1.30286181e+00 2.19604269e-01 4.64784414e-01 4.82238442e-01 -1.04788458e+00 -4.29398865e-02 4.18557912e-01 -4.45178524e-02 -1.32884836e+00 -4.77977663e-01 7.93910027e-02 -3.45234632e-01 2.57793851e-02 -2.95492373e-02 -2.77092040e-01 -3.05818528e-01 1.88358819e+00 2.03487635e-01 4.76265028e-02 -2.80657023e-01 9.81192291e-01 1.24079835e+00 7.28916526e-01 5.86089611e-01 -4.53113288e-01 1.46666920e+00 -6.67523205e-01 -1.08726311e+00 7.84427151e-02 2.27831975e-01 -8.68961453e-01 1.29238462e+00 6.27848685e-01 -1.23389256e+00 -8.17223012e-01 -8.57214034e-01 3.54311578e-02 -4.76917148e-01 5.03229611e-02 5.76291442e-01 5.74165225e-01 -9.41769063e-01 2.72675514e-01 -2.95111150e-01 -2.91251004e-01 3.59498382e-01 7.38835931e-02 -4.07055974e-01 4.58975196e-01 -1.11255074e+00 7.11921394e-01 4.52996977e-02 -1.29141182e-01 -7.46552944e-01 -7.07530499e-01 -9.04267311e-01 -4.04656213e-03 -1.26447767e-01 -2.50732034e-01 1.39864910e+00 -1.67993116e+00 -1.50228930e+00 6.66344225e-01 -1.52349085e-01 2.80138373e-01 -6.00226074e-02 -3.43141377e-01 -7.05154300e-01 6.51157022e-01 -2.79911339e-01 7.97273517e-01 9.64449465e-01 -1.25331986e+00 -4.41088706e-01 -3.41371804e-01 -1.57507077e-01 5.37963867e-01 -9.74686325e-01 2.35935912e-01 -2.66240031e-01 -5.59794486e-01 -2.76771516e-01 -6.77458286e-01 3.04823339e-01 2.72153839e-02 -2.64301021e-02 -5.75800836e-02 5.36768734e-01 -6.60502136e-01 1.29645729e+00 -2.75020432e+00 2.25685656e-01 1.56378940e-01 5.88166267e-02 -4.24096882e-01 -3.03890824e-01 7.38612175e-01 -1.40940368e-01 1.52561381e-01 3.44941765e-01 -2.99919844e-01 2.47936904e-01 -3.24276239e-01 -7.27411434e-02 1.79617032e-01 7.21446425e-02 7.36483157e-01 -8.44998300e-01 -4.83510822e-01 2.58195698e-01 1.00175035e+00 -6.03226960e-01 2.56035745e-01 -5.35280770e-03 4.62009370e-01 -4.24771234e-02 6.68562055e-01 2.79517174e-01 2.04539508e-01 4.47526363e-05 -6.26506209e-01 -2.66791761e-01 -3.63117345e-02 -9.33692694e-01 1.44135392e+00 -5.47127247e-01 1.09074807e+00 2.54763395e-01 -3.73797774e-01 8.01721811e-01 6.25173986e-01 7.68558741e-01 -1.04747438e+00 5.36856353e-01 -3.15047771e-01 -1.62612155e-01 -9.54767466e-01 7.86822796e-01 -2.36475348e-01 -3.28550607e-01 4.28119093e-01 8.34699124e-02 -6.67854622e-02 3.88208441e-02 1.16066284e-01 5.59716880e-01 -1.78597346e-01 2.50153542e-01 4.02750254e-01 6.84359223e-02 -2.80306488e-01 1.44112423e-01 2.89851844e-01 -4.31564480e-01 4.15278912e-01 4.98402894e-01 2.39997834e-01 -6.75487220e-01 -9.82831478e-01 -5.30959293e-02 1.88195872e+00 2.09926918e-01 -6.33536220e-01 -3.43298972e-01 2.59228349e-02 -9.96493548e-02 6.10257387e-01 -7.85216391e-01 -3.98996532e-01 3.29399973e-01 -2.45555952e-01 3.30130279e-01 5.20577908e-01 -3.51214176e-03 -1.53460348e+00 -5.12217820e-01 -1.15373909e-01 -7.25466967e-01 -1.01078546e+00 -5.42819798e-01 -8.99008512e-02 -4.06710446e-01 -7.98040509e-01 -2.67739594e-01 -6.35589242e-01 1.01088554e-01 9.99017656e-02 1.02588081e+00 -4.88035142e-01 -2.82089353e-01 1.30075932e+00 -5.71627796e-01 -5.66238344e-01 -1.05605841e-01 -4.84319627e-01 9.90851149e-02 4.70669240e-01 3.85946721e-01 -3.80182713e-01 -7.32840359e-01 -2.37522572e-02 -9.53521490e-01 -9.42725390e-02 2.21526057e-01 1.69631958e-01 5.76130867e-01 -1.29660144e-01 6.40738904e-01 -2.50717819e-01 9.31673825e-01 -8.77389610e-01 4.74828780e-01 -3.58163446e-01 -1.50309235e-01 -8.23327601e-01 3.21019143e-02 -8.16181898e-01 -1.15053141e+00 -1.12134561e-01 -1.31789848e-01 -5.52806258e-01 -3.45761418e-01 8.35430622e-01 -1.22681726e-02 7.40444940e-03 4.87963647e-01 -1.61475137e-01 5.49371578e-02 -2.14598879e-01 3.74884695e-01 9.48689222e-01 3.80506098e-01 -2.97831893e-01 5.69955334e-02 3.58636796e-01 -3.33552271e-01 -1.19415009e+00 -5.05708873e-01 -5.71994960e-01 -2.61975616e-01 -1.20095372e+00 1.01335526e+00 -1.34165454e+00 -1.02034485e+00 3.75015020e-01 -6.05933905e-01 -3.18041414e-01 -1.94521263e-01 7.28231788e-01 -5.82970500e-01 8.99984539e-02 -8.27883005e-01 -9.98003364e-01 -2.65629530e-01 -8.18942666e-01 8.79157484e-01 1.39511421e-01 -8.63892078e-01 -8.04183662e-01 9.40105841e-02 4.19263870e-01 4.10802692e-01 3.30823153e-01 7.53671646e-01 -4.75929052e-01 3.25947404e-01 -2.51865029e-01 -1.15735285e-01 2.15901539e-01 2.47965604e-02 2.38436073e-01 -1.26945317e+00 1.01481996e-01 -2.21949533e-01 -8.55398893e-01 7.02689230e-01 5.37324786e-01 1.28953111e+00 -3.07296723e-01 2.19911560e-01 8.73092636e-02 1.19950807e+00 1.68125719e-01 5.01360297e-01 1.53670505e-01 6.48205698e-01 7.69480526e-01 7.02811003e-01 9.18588042e-01 5.66159666e-01 5.43696344e-01 5.57874024e-01 4.46568383e-03 1.53481603e-01 -1.60636872e-01 8.52064431e-01 1.06073499e+00 -7.79285561e-04 -1.79126598e-02 -4.28170830e-01 3.83354664e-01 -1.44922435e+00 -1.18530297e+00 -1.34999514e-01 1.98093069e+00 7.63586223e-01 -4.47204947e-01 5.14997125e-01 2.83528894e-01 4.34613764e-01 6.93417341e-02 -3.13973099e-01 -8.81112754e-01 -2.56168962e-01 -9.22936015e-03 -3.32448214e-01 1.84122458e-01 -1.17017949e+00 4.34936911e-01 6.94890785e+00 4.47594941e-01 -1.37339950e+00 4.04265011e-03 4.38215405e-01 -7.27038801e-01 -4.32403594e-01 -6.30069852e-01 1.32358432e-01 3.30824345e-01 1.12550199e+00 9.46694165e-02 4.54899549e-01 6.98207378e-01 5.55012584e-01 -2.02101722e-01 -1.07498956e+00 1.26921248e+00 3.93502623e-01 -5.75372279e-01 -1.45564929e-01 -2.56222337e-01 4.17401284e-01 -1.61450893e-01 5.26112735e-01 4.72349942e-01 -7.35399008e-01 -8.10940623e-01 1.00216198e+00 7.34407544e-01 9.16820943e-01 -7.98922002e-01 4.98562634e-01 -2.24999472e-01 -1.11549783e+00 -2.38149956e-01 1.00533970e-01 -3.42166036e-01 5.83341047e-02 1.33392423e-01 -3.90251994e-01 -9.38317180e-02 8.77716362e-01 8.41400146e-01 -4.83696312e-01 8.19735289e-01 1.79989308e-01 6.40245497e-01 1.44574344e-01 -1.81724295e-01 -3.22384089e-01 2.72414591e-02 3.56021762e-01 1.51219165e+00 4.85512614e-01 7.18859807e-02 4.14813086e-02 5.09232700e-01 -6.56119660e-02 7.05710828e-01 -4.04769599e-01 -6.87327862e-01 5.10141969e-01 1.65518463e+00 -5.70562065e-01 -1.43405259e-01 -5.93534231e-01 8.24444234e-01 -4.40544263e-02 4.78306562e-01 -8.03472698e-01 -1.08537860e-01 7.27485538e-01 -2.21007437e-01 1.35468870e-01 8.40467289e-02 -1.51368737e-01 -8.79944265e-01 -2.15988949e-01 -8.47679853e-01 5.04756749e-01 -1.33435750e+00 -1.41908908e+00 3.39678824e-01 -2.33222425e-01 -1.38087952e+00 -8.88819527e-03 -3.99566948e-01 -3.87536347e-01 4.24903184e-01 -1.19946992e+00 -8.47657502e-01 -6.51417911e-01 6.74317837e-01 4.49815363e-01 1.11215599e-01 9.33087051e-01 4.65022743e-01 -3.32134843e-01 4.47591215e-01 -3.78306627e-01 -1.07198656e-01 1.22776628e+00 -8.89691472e-01 -8.63927960e-01 -1.02108628e-01 4.62924922e-03 1.36194617e-01 6.28251135e-01 -2.78495610e-01 -1.48565936e+00 -7.19759047e-01 5.91303229e-01 -2.41712362e-01 7.16415465e-01 1.84858358e-03 -5.21127641e-01 3.50527078e-01 6.65571988e-01 -5.18281460e-01 1.74015188e+00 4.00088876e-01 -5.40331185e-01 7.86679909e-02 -9.65188503e-01 5.35880744e-01 5.20955026e-01 -9.25343215e-01 -3.13278854e-01 -3.49087507e-01 5.60114324e-01 7.65900612e-02 -1.21545208e+00 3.47989708e-01 1.08753979e+00 -9.48806703e-01 7.33452916e-01 -4.84933138e-01 1.02301633e+00 1.44617232e-02 -5.41751683e-01 -1.58454549e+00 -3.36731166e-01 -7.83832744e-03 -2.49643013e-01 1.35758209e+00 3.02108526e-01 1.69007983e-02 1.56716228e-01 4.74352658e-01 -9.75003392e-02 -2.99202859e-01 -5.72221220e-01 1.32806838e-01 -3.13005000e-01 -1.02499044e+00 2.04166532e-01 1.23194778e+00 7.93829143e-01 5.38677216e-01 -3.85164529e-01 -1.73640192e-01 6.13365881e-02 -5.00211399e-03 4.74029392e-01 -1.18597639e+00 -1.23622669e-02 -8.03167284e-01 -4.06933546e-01 -1.72274411e-01 -8.41628108e-03 -8.26134562e-01 -3.64449471e-02 -1.38545287e+00 5.19386351e-01 3.45207095e-01 -7.62014508e-01 3.29716682e-01 -7.48026073e-02 7.07861602e-01 3.90565097e-01 -1.04523048e-01 -8.37600470e-01 6.69586301e-01 1.14645183e+00 -2.03823403e-01 -3.61262023e-01 -3.74948144e-01 -8.14230978e-01 6.58492327e-01 6.83907032e-01 1.73467398e-01 -3.42867166e-01 -1.13074623e-01 7.70963848e-01 2.12151766e-01 3.39750886e-01 -8.68858874e-01 -1.44973263e-01 1.86088905e-02 6.68213308e-01 -5.10316312e-01 1.01413548e+00 -8.49494994e-01 9.18397158e-02 -1.35315359e-01 -8.12045336e-01 -4.11551856e-02 5.95373869e-01 4.58614230e-01 -4.38475400e-01 2.17887878e-01 5.59172869e-01 2.97315449e-01 -8.54337215e-01 7.47542381e-02 -9.50939238e-01 -1.64925858e-01 8.19406569e-01 -2.37947792e-01 5.13120368e-02 -1.13183200e+00 -1.22590733e+00 -1.24615490e-01 1.57814860e-01 8.77617121e-01 7.79172122e-01 -1.69600010e+00 -5.72102487e-01 -2.41548885e-02 4.95262355e-01 -1.08843327e+00 8.43901217e-01 1.11007428e+00 2.51452327e-01 -1.23874582e-01 -5.25863111e-01 -5.71979165e-01 -1.49180746e+00 5.64157069e-01 -1.26736850e-01 6.82636738e-01 8.64477456e-02 7.08884120e-01 5.51753938e-02 -1.22298822e-01 4.67708617e-01 1.14399724e-01 -9.06163812e-01 1.05917585e+00 7.85374999e-01 4.83911157e-01 -2.70260960e-01 -1.02549481e+00 -8.95671248e-02 4.54418480e-01 4.57031786e-01 -3.96468490e-01 1.21563542e+00 -5.10125637e-01 -1.34327188e-01 1.34406447e+00 1.39790905e+00 1.52180314e-01 -7.72099674e-01 1.51793202e-02 -4.60150331e-01 -2.01002389e-01 1.60534665e-01 -9.38507020e-01 -1.08954859e+00 9.28750813e-01 8.33830118e-01 2.91304320e-01 1.45096362e+00 -3.81270796e-02 5.27827322e-01 -4.04883660e-02 -1.22270145e-01 -1.43565691e+00 6.88273668e-01 3.03372085e-01 8.74390543e-01 -1.15450466e+00 -3.54947031e-01 -2.14081153e-01 -1.29574776e+00 1.01207054e+00 5.77935874e-01 3.45065027e-01 8.42942357e-01 1.19242407e-01 3.21974248e-01 -1.18625134e-01 -9.35082436e-01 -2.36475065e-01 6.17609084e-01 5.37315428e-01 9.28530514e-01 2.12449744e-01 -1.01968162e-01 1.18207204e+00 -3.65994930e-01 -1.58454105e-01 5.38918018e-01 7.32584178e-01 -3.22586894e-01 -4.17536974e-01 -4.15627569e-01 5.07321119e-01 -5.79680085e-01 8.09989646e-02 -8.20214808e-01 3.38927269e-01 1.08539566e-01 1.28180623e+00 4.79183078e-01 -7.49736428e-01 2.88459718e-01 3.40565950e-01 5.07607400e-01 -3.02986979e-01 -7.47833967e-01 4.61093843e-01 2.32178003e-01 -6.13016069e-01 -7.17142820e-01 -7.32559443e-01 -1.20539188e+00 -5.79247922e-02 1.03210866e-01 6.88762963e-02 9.71000373e-01 6.83228910e-01 4.84365195e-01 7.76422739e-01 7.11630464e-01 -1.13920367e+00 2.39020765e-01 -1.14707315e+00 -6.38477325e-01 6.69757426e-01 2.34021828e-01 -6.08572721e-01 -5.17408133e-01 2.97794104e-01]	[13.305747985839844, 5.134044170379639]
322fb979-30a5-4860-bc83-786f49aa11b6	darf-boosting-radiance-fields-from-sparse	2305.19201	null	https://arxiv.org/abs/2305.19201v1	https://arxiv.org/pdf/2305.19201v1.pdf	DäRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation	Neural radiance fields (NeRF) shows powerful performance in novel view synthesis and 3D geometry reconstruction, but it suffers from critical performance degradation when the number of known viewpoints is drastically reduced. Existing works attempt to overcome this problem by employing external priors, but their success is limited to certain types of scenes or datasets. Employing monocular depth estimation (MDE) networks, pretrained on large-scale RGB-D datasets, with powerful generalization capability would be a key to solving this problem: however, using MDE in conjunction with NeRF comes with a new set of challenges due to various ambiguity problems exhibited by monocular depths. In this light, we propose a novel framework, dubbed D\"aRF, that achieves robust NeRF reconstruction with a handful of real-world images by combining the strengths of NeRF and monocular depth estimation through online complementary training. Our framework imposes the MDE network's powerful geometry prior to NeRF representation at both seen and unseen viewpoints to enhance its robustness and coherence. In addition, we overcome the ambiguity problems of monocular depths through patch-wise scale-shift fitting and geometry distillation, which adapts the MDE network to produce depths aligned accurately with NeRF geometry. Experiments show our framework achieves state-of-the-art results both quantitatively and qualitatively, demonstrating consistent and reliable performance in both indoor and outdoor real-world datasets. Project page is available at https://ku-cvlab.github.io/DaRF/.	['Seungryong Kim', 'SungJin Cho', 'Min-Seop Kwak', 'Seokju Cho', 'Honggyu An', 'Seonghoon Park', 'Jiuhn Song']	2023-05-30	null	null	null	null	['monocular-depth-estimation', 'novel-view-synthesis']	['computer-vision', 'computer-vision']	[ 9.32848528e-02 -2.22805291e-01 1.02316223e-01 -4.80895102e-01 -6.73443854e-01 -5.93101084e-01 4.85672534e-01 -6.50373340e-01 -2.04360455e-01 6.35686219e-01 2.73670167e-01 -2.69116331e-02 6.88088778e-03 -9.20374393e-01 -8.33186269e-01 -6.67821288e-01 2.86980659e-01 -2.62510870e-02 8.68780166e-02 -4.17699009e-01 6.61978126e-02 8.02401423e-01 -1.52654016e+00 5.16081639e-02 9.28202450e-01 1.08285868e+00 5.25419772e-01 6.14390075e-01 2.27464601e-01 6.87856853e-01 -2.54796118e-01 -3.09561104e-01 8.21288884e-01 -4.86191548e-02 -3.87744665e-01 4.20589745e-02 7.72627652e-01 -9.38784301e-01 -8.56144607e-01 9.95898902e-01 6.68949068e-01 1.49753988e-01 2.82235324e-01 -1.04785824e+00 -6.12644374e-01 -2.28939995e-01 -6.14718735e-01 -9.83437151e-02 5.09379804e-01 1.56806454e-01 7.55237579e-01 -1.08857656e+00 5.26674986e-01 1.07657707e+00 6.83649719e-01 5.31465530e-01 -1.01879275e+00 -6.51823401e-01 2.69552529e-01 -1.30130630e-02 -1.43412602e+00 -4.61057097e-01 1.04956830e+00 -1.40792444e-01 1.06181431e+00 9.93443131e-02 5.61759830e-01 1.12455893e+00 1.03374710e-02 6.27304554e-01 1.03021610e+00 -1.31739736e-01 1.32442668e-01 -1.68056190e-01 -5.01099408e-01 5.15525222e-01 1.15879357e-01 3.39542627e-01 -5.23769021e-01 1.60244554e-01 1.24812222e+00 1.96932629e-01 -8.85376751e-01 -4.86153573e-01 -1.15848291e+00 6.02391541e-01 9.70267534e-01 9.16431472e-02 -3.07531536e-01 1.69807836e-01 -1.62812889e-01 1.70488700e-01 5.44277072e-01 4.25472796e-01 -7.16487169e-01 2.34349430e-01 -6.52499616e-01 1.90824062e-01 3.52073461e-01 1.04874325e+00 1.02534986e+00 1.12446740e-01 3.80729437e-01 9.50944424e-01 3.21118027e-01 8.05816352e-01 1.76051065e-01 -1.25521815e+00 5.73785603e-01 5.63111424e-01 1.66034773e-01 -1.12624693e+00 -5.00670016e-01 -5.31318128e-01 -1.03548205e+00 3.16736221e-01 2.96908140e-01 4.57004383e-02 -9.45832312e-01 1.89606702e+00 5.58405697e-01 1.44531250e-01 1.35553762e-01 1.12657106e+00 9.38857198e-01 6.17252886e-01 -6.35137022e-01 1.35212213e-01 9.82520163e-01 -8.23151231e-01 -4.76037830e-01 -5.07455528e-01 2.25932658e-01 -6.95406020e-01 9.74622309e-01 5.20803154e-01 -9.93728161e-01 -5.70627987e-01 -1.04062665e+00 -5.17572582e-01 -1.73411563e-01 -2.23924872e-02 7.00047910e-01 3.88158888e-01 -1.24268627e+00 2.96041250e-01 -7.33805776e-01 -1.49592072e-01 3.47721249e-01 2.62510747e-01 -5.85157752e-01 -7.67265737e-01 -1.04284751e+00 5.18746734e-01 4.92327809e-02 3.81267190e-01 -8.16039979e-01 -6.49657011e-01 -1.08821166e+00 -1.87801555e-01 4.55950499e-01 -1.09464967e+00 1.02124810e+00 -6.61801636e-01 -1.55469644e+00 5.92970550e-01 -4.26399186e-02 -4.41006459e-02 5.86522341e-01 -4.73504782e-01 -1.61101833e-01 3.39657694e-01 8.10023304e-03 9.57568824e-01 6.94440424e-01 -1.48409247e+00 -3.70163172e-01 -6.09260976e-01 4.97411817e-01 5.70349216e-01 -1.34441093e-01 -4.94569570e-01 -6.07906103e-01 -5.15590787e-01 6.79996014e-01 -6.91806614e-01 -2.37648383e-01 3.26978296e-01 -2.43734255e-01 1.89869717e-01 6.02544606e-01 -6.00468516e-01 6.09333754e-01 -2.02158904e+00 1.44058928e-01 -1.23308651e-01 3.07274491e-01 3.02540939e-02 -1.81314901e-01 3.48710507e-01 8.01918805e-02 -1.70832694e-01 -2.14417502e-01 -5.63796759e-01 -1.13623381e-01 4.07576919e-01 -2.28181750e-01 6.55477047e-01 6.23088852e-02 7.85335481e-01 -9.68564510e-01 -3.54809090e-02 6.46167159e-01 8.92773628e-01 -7.11613834e-01 3.78871560e-01 -1.07207827e-01 8.40260148e-01 -2.50696212e-01 7.70983458e-01 1.17244375e+00 -3.20099324e-01 1.09737385e-02 -4.85807300e-01 -1.55132100e-01 1.62577137e-01 -1.32063675e+00 2.15045834e+00 -6.73007071e-01 4.76316065e-01 1.36757314e-01 -6.00802898e-01 8.33038032e-01 8.18258375e-02 4.07658517e-01 -9.93169546e-01 1.01331919e-01 3.61712575e-01 -3.85856152e-01 -4.13490802e-01 5.44220150e-01 -1.48504823e-01 2.02848405e-01 -7.31902197e-02 1.47805139e-02 -5.84087551e-01 -2.55997390e-01 7.76477829e-02 8.81813288e-01 5.37752926e-01 2.87005961e-01 2.45209187e-01 4.29454207e-01 -4.34419811e-01 8.30767751e-01 5.02208769e-01 2.28000600e-02 1.06557500e+00 -1.02834731e-01 -4.37005699e-01 -9.75326717e-01 -1.21458733e+00 -3.33693773e-01 4.25666720e-01 4.56610054e-01 -1.85413152e-01 -3.96577209e-01 -4.81638163e-01 -1.42102256e-01 4.23402160e-01 -5.05325019e-01 9.93431881e-02 -5.52309453e-01 -6.56145930e-01 1.37199968e-01 5.25410533e-01 1.06048799e+00 -5.12056351e-01 -6.70240939e-01 1.61096323e-02 -4.46111858e-01 -1.60984874e+00 -1.73169687e-01 1.00445049e-03 -8.64821732e-01 -1.05678260e+00 -9.09473419e-01 -3.79689276e-01 5.41975558e-01 8.85338783e-01 1.18205440e+00 -1.59758255e-01 -9.30090398e-02 3.53398860e-01 -3.25408578e-01 -9.33115780e-02 3.09497509e-02 -1.77874535e-01 -1.27633557e-01 -1.14244416e-01 -1.36346221e-01 -1.01864111e+00 -1.23586679e+00 5.48578858e-01 -1.02681017e+00 3.66148919e-01 5.07274568e-01 7.80373693e-01 4.80414033e-01 -9.03734565e-02 2.77722389e-01 -4.41458732e-01 -2.67963111e-01 -4.08851057e-01 -7.33793080e-01 -1.84973449e-01 -3.69692564e-01 -3.25323552e-01 6.65377736e-01 4.42451686e-02 -1.19475865e+00 4.85997535e-02 -3.88426334e-01 -6.47777319e-01 -2.93653548e-01 1.70998186e-01 -4.18850869e-01 -3.50176245e-01 6.54369056e-01 2.21353382e-01 -3.19539279e-01 -4.34310555e-01 2.99640059e-01 4.26502824e-01 6.97207808e-01 -3.94913763e-01 9.51048136e-01 9.56648648e-01 1.39554441e-01 -7.50163615e-01 -1.05379283e+00 -5.06056964e-01 -6.49829865e-01 -2.05795318e-01 7.62479424e-01 -1.47601163e+00 -4.76298273e-01 7.32324064e-01 -1.07667625e+00 -4.75947589e-01 -4.83645461e-02 5.72060227e-01 -4.81695771e-01 5.30636072e-01 -3.98679793e-01 -6.16485715e-01 -1.08413771e-01 -1.00017190e+00 1.43567932e+00 2.97601908e-01 3.61618996e-01 -8.90154243e-01 6.86026877e-03 5.10747373e-01 2.49692768e-01 5.11989653e-01 4.72769260e-01 3.76265496e-01 -1.16846395e+00 8.29467643e-03 -4.91875261e-01 6.41290426e-01 2.47648329e-01 -3.60005766e-01 -1.36476958e+00 -3.78325880e-01 2.16632783e-01 -2.50530720e-01 8.23506236e-01 4.69616413e-01 1.02242172e+00 1.99789833e-02 3.62441652e-02 1.40872526e+00 1.82660246e+00 2.75602564e-02 7.60601401e-01 3.72837633e-01 1.05815542e+00 5.43234050e-01 4.76741672e-01 5.04969239e-01 7.38559902e-01 8.00124466e-01 9.27882075e-01 -3.63836229e-01 -3.95787984e-01 -3.23006094e-01 9.52600688e-02 6.06767416e-01 -2.05919698e-01 -4.74080294e-01 -7.33734906e-01 4.10556078e-01 -1.69370019e+00 -6.54536664e-01 2.79714223e-02 2.24081087e+00 5.70162177e-01 -1.60783380e-01 -3.39473665e-01 9.65302512e-02 1.58725500e-01 4.45062250e-01 -6.68747425e-01 1.99874893e-01 -5.45208037e-01 5.78543320e-02 5.58961630e-01 4.79175776e-01 -8.12900841e-01 6.87865496e-01 4.83519506e+00 4.52729076e-01 -1.21980703e+00 5.14322408e-02 5.50367534e-01 -7.96767771e-02 -5.38399875e-01 -1.24390334e-01 -6.05061769e-01 1.57634348e-01 3.72458994e-01 4.67122763e-01 6.04122698e-01 6.39484465e-01 1.65296853e-01 -3.15145135e-01 -9.53924239e-01 1.38666511e+00 1.80891454e-01 -1.17570496e+00 -1.59452513e-01 1.28183335e-01 1.13031483e+00 4.87488776e-01 4.80780043e-02 2.63601430e-02 2.29579911e-01 -9.23886955e-01 5.94854057e-01 4.93273944e-01 9.74346340e-01 -5.55820942e-01 6.84491992e-01 4.48047251e-01 -1.16672742e+00 -9.66318250e-02 -5.77981055e-01 -1.75666735e-01 1.94767416e-01 8.40613842e-01 -5.91977298e-01 1.08224499e+00 9.15877044e-01 1.07806480e+00 -3.71297598e-01 8.97278845e-01 -5.40326953e-01 -7.53430426e-02 -4.88338113e-01 6.01631403e-01 9.58775803e-02 -1.44919977e-01 3.94194603e-01 6.15734398e-01 5.47862113e-01 2.42307976e-01 3.77882309e-02 9.13461864e-01 -2.20499143e-01 -1.97683260e-01 -8.02950084e-01 5.70123494e-01 3.76544625e-01 1.30653918e+00 -4.62065697e-01 2.22190171e-02 -5.79655290e-01 1.12273371e+00 3.30952376e-01 6.18386328e-01 -7.33187973e-01 -8.70279595e-02 7.60582864e-01 1.88176006e-01 2.51326561e-01 -5.20871758e-01 -2.27107659e-01 -1.57274938e+00 2.66637295e-01 -6.86140418e-01 3.94551270e-02 -1.25655282e+00 -1.22488451e+00 6.40186965e-01 -2.40953788e-02 -1.38013566e+00 -6.42010719e-02 -7.40245402e-01 -2.41559550e-01 8.73104811e-01 -2.21903753e+00 -1.19904792e+00 -1.03383374e+00 7.71645308e-01 4.62255210e-01 2.97465026e-01 6.07102394e-01 5.14814913e-01 -3.25371295e-01 3.17440271e-01 1.03967085e-01 -5.73790409e-02 8.16162705e-01 -1.16617417e+00 5.66419780e-01 9.08784449e-01 -1.81646682e-02 4.15729165e-01 4.43478376e-01 -3.75618666e-01 -1.56201446e+00 -1.11654055e+00 4.88438964e-01 -3.96795422e-01 5.11668809e-02 -4.63936776e-01 -6.42812133e-01 5.61254442e-01 -8.75141993e-02 4.65638548e-01 3.07187021e-01 -2.42571548e-01 -4.46483493e-01 -2.15457126e-01 -1.13702774e+00 5.47681749e-01 1.50466681e+00 -6.36316180e-01 -1.60342261e-01 3.12545717e-01 7.50486493e-01 -8.37014377e-01 -8.66393030e-01 8.11978161e-01 4.80773866e-01 -1.54974151e+00 1.35942709e+00 3.13145101e-01 5.52300990e-01 -6.02120936e-01 -7.63095260e-01 -1.27459049e+00 -4.92489450e-02 -5.17762423e-01 -9.73832086e-02 9.84169722e-01 -1.46699637e-01 -9.38212335e-01 6.90125704e-01 2.57332414e-01 -4.30707991e-01 -7.86876619e-01 -8.90793085e-01 -6.29840493e-01 -9.66329053e-02 -5.91403306e-01 7.03911185e-01 9.89309788e-01 -7.98428118e-01 2.59259313e-01 -4.70612466e-01 5.59024155e-01 7.51191080e-01 1.51249051e-01 1.13115489e+00 -9.77527320e-01 -3.64836216e-01 -4.78957035e-02 -3.39997828e-01 -1.72099364e+00 -1.10112950e-01 -6.32109404e-01 5.87917678e-02 -1.75983477e+00 -1.18658200e-01 -4.44422781e-01 6.37406111e-02 1.84493348e-01 -2.67112963e-02 5.81040740e-01 1.70633554e-01 2.42617428e-01 -2.35700697e-01 9.13711905e-01 1.62961698e+00 1.87317371e-01 -9.15409103e-02 -1.86640784e-01 -5.41593194e-01 8.86526287e-01 6.31364584e-01 -1.53418913e-01 -6.46068215e-01 -9.18666601e-01 5.71739972e-01 2.66948789e-01 6.96602345e-01 -1.18093526e+00 6.77436441e-02 -1.34054527e-01 7.45688200e-01 -6.93867862e-01 8.18992317e-01 -8.94276679e-01 2.38864779e-01 -4.48876955e-02 2.35559016e-01 9.12286062e-03 7.97015950e-02 5.97705960e-01 -2.57950544e-01 1.43356860e-01 8.53289187e-01 -3.68919969e-01 -8.60563874e-01 5.82168758e-01 3.31779391e-01 7.17642009e-02 6.23668492e-01 -4.68537629e-01 -4.99018878e-01 -6.37094855e-01 -2.69733578e-01 1.18079297e-01 8.88576865e-01 2.36768767e-01 8.79272461e-01 -1.27466273e+00 -5.41582704e-01 5.34959972e-01 2.01210618e-01 7.53060877e-01 6.89984620e-01 7.60791242e-01 -6.34498715e-01 1.22054458e-01 -8.12565461e-02 -8.39253068e-01 -8.34638238e-01 3.22946697e-01 6.13527477e-01 -3.06599140e-02 -8.15140247e-01 9.98022139e-01 7.40819633e-01 -7.85847068e-01 7.42010102e-02 -5.19706130e-01 1.52610347e-01 -3.83815467e-01 3.30837190e-01 1.48911148e-01 1.31246343e-01 -6.05347693e-01 -2.55348623e-01 1.01688492e+00 1.58518389e-01 4.40558605e-02 1.41116083e+00 -5.89141250e-01 1.78058311e-01 1.91169590e-01 1.32902563e+00 1.29852042e-01 -1.81096160e+00 -3.94921780e-01 -6.44906223e-01 -1.00296474e+00 3.19907486e-01 -7.65050948e-01 -1.17507529e+00 9.59718287e-01 5.10798633e-01 -3.26636761e-01 1.49494076e+00 -1.58155173e-01 1.01193130e+00 4.06858474e-01 6.25201344e-01 -6.99291587e-01 2.15524480e-01 5.79180896e-01 9.12473798e-01 -1.58492172e+00 1.02198206e-01 -5.99839628e-01 -1.25690117e-01 1.16255152e+00 6.08674586e-01 -1.53603613e-01 5.33880591e-01 2.10588239e-02 2.36320242e-01 -2.08041489e-01 -3.55249822e-01 -4.78348695e-02 2.86498994e-01 5.98739862e-01 1.18947551e-01 -1.61647886e-01 3.94667625e-01 1.20548934e-01 -2.54467726e-01 -5.64231686e-02 5.08858979e-01 8.92701387e-01 -1.61233157e-01 -8.48578751e-01 -3.77094477e-01 -1.23920754e-01 -1.54064462e-01 -1.79770410e-01 4.95110862e-02 9.61191058e-01 2.07632065e-01 8.20652187e-01 -7.28295520e-02 -3.98078859e-01 3.89060736e-01 -4.97267723e-01 7.73630083e-01 -4.23955560e-01 -1.55632392e-01 2.12967783e-01 -2.06405316e-02 -9.08446252e-01 -6.74289942e-01 -4.43786412e-01 -1.00694859e+00 -3.19403172e-01 -1.83699548e-01 -4.76798892e-01 7.65070736e-01 7.46847808e-01 3.94789100e-01 4.75149393e-01 9.40905333e-01 -1.21163356e+00 -3.61284524e-01 -7.32148111e-01 -4.71062332e-01 3.03372413e-01 6.55175924e-01 -7.10911989e-01 -5.52137911e-01 -3.25782567e-01]	[9.06135082244873, -2.6754562854766846]
8742fe6b-75ed-44a4-ae1b-ff858b350c7a	disarm-detecting-the-victims-targeted-by	null	null	https://openreview.net/forum?id=Woi12EDR_fj	https://openreview.net/pdf?id=Woi12EDR_fj	DISARM: Detecting the Victims Targeted by Harmful Memes	Internet memes have emerged as an increasingly popular means of communication on the web. Although memes are typically intended to elicit humour, they have been increasingly used to spread hatred, trolling, and cyberbullying, as well as to target specific individuals, communities, or society on political, socio-cultural, and psychological grounds. While previous work has focused on detecting harmful, hateful, and offensive memes in general, identifying whom these memes attack (i.e., the `victims') remains a challenging and underexplored area. We attempt to address this problem in this paper. To this end, we create a dataset in which we annotate each meme with its victim(s) such as the name of the targeted person(s), organization(s), and community(ies). We then propose DISARM (Detecting vIctimS targeted by hARmful Memes), a framework that uses named-entity recognition and person identification to detect all entities a meme is referring to, and then, incorporates a novel contextualized multimodal deep neural network to classify whether the meme intends to harm these entities. We perform several systematic experiments on three different test sets, corresponding to entities that are (i) all seen while training, (ii) not seen as a harmful target while training, and (iii) not seen at all while training. The evaluation shows that DISARM significantly outperforms 10 unimodal and multimodal systems. Finally, we demonstrate that DISARM is interpretable and comparatively more generalizable, and that it can reduce the relative error rate of harmful target identification by up to 9% absolute over multimodal baseline systems.	['Anonymous']	2022-01-16	null	null	null	acl-arr-january-2022-1	['person-identification']	['computer-vision']	[-1.10074796e-01 -1.16459969e-02 5.03797270e-02 7.86130875e-02 -3.54402751e-01 -8.53702545e-01 9.35269237e-01 4.86239731e-01 -4.88265276e-01 7.24176109e-01 3.30897778e-01 -3.82654704e-02 4.78516579e-01 -8.51950467e-01 -4.15455997e-01 -6.01195097e-01 1.60647571e-01 3.65739852e-01 9.65554640e-02 -3.38459074e-01 4.44583148e-01 2.60367721e-01 -1.03358018e+00 3.42891961e-01 7.99474537e-01 6.30104721e-01 -6.44277990e-01 4.06708807e-01 -1.97274871e-02 1.12674868e+00 -1.14146006e+00 -1.00153816e+00 -3.75535131e-01 -4.62373197e-01 -9.91109252e-01 -2.87599526e-02 5.82852244e-01 -2.41415098e-01 -5.69465578e-01 1.17206025e+00 5.63573122e-01 6.85565844e-02 7.50792980e-01 -1.15348208e+00 -1.04346895e+00 5.98475814e-01 -7.28543282e-01 3.01435351e-01 5.79515338e-01 1.57409266e-01 6.41796291e-01 -8.05875778e-01 6.97857857e-01 1.39866912e+00 4.98333752e-01 7.52172887e-01 -1.11033738e+00 -7.26502717e-01 -1.54103994e-01 -8.09914258e-04 -1.40961802e+00 -3.74817431e-01 8.01833689e-01 -6.79352641e-01 3.35355639e-01 3.48256350e-01 2.15693355e-01 1.82201600e+00 4.18124311e-02 6.73415005e-01 8.43929946e-01 -1.36259839e-01 3.34532559e-02 4.88296658e-01 3.36793184e-01 6.35013938e-01 1.76191539e-01 -3.39897126e-01 -6.02127790e-01 -5.74151576e-01 8.31075683e-02 -2.40863636e-01 -3.94068599e-01 1.81117520e-01 -1.11672390e+00 1.03615618e+00 6.89129114e-01 4.56393540e-01 -3.76713187e-01 1.03174997e-02 6.69383764e-01 4.25679609e-02 6.00132763e-01 6.42636478e-01 3.75940055e-01 -1.10102799e-02 -5.55940986e-01 1.86858386e-01 1.14843786e+00 3.11495006e-01 4.94010508e-01 -2.28785664e-01 -2.48667985e-01 1.01084065e+00 -4.57395725e-02 6.87361658e-01 2.40809679e-01 -5.08865714e-01 5.30951321e-01 1.07552588e+00 3.82157743e-01 -1.86404335e+00 -5.14729917e-01 -2.74837822e-01 -9.25283194e-01 -4.01245475e-01 2.37034380e-01 -3.91665220e-01 -4.91514295e-01 1.90032160e+00 4.50025797e-01 -1.12759896e-01 -9.26661417e-02 1.03252757e+00 1.17335761e+00 8.26010585e-01 4.10406768e-01 8.84178579e-02 1.32757771e+00 -7.16134012e-01 -6.50054455e-01 -2.18323350e-01 6.67257428e-01 -6.77506804e-01 7.70003319e-01 -4.10353541e-02 -8.18899632e-01 -3.00351121e-02 -6.92744672e-01 1.61961373e-02 -9.24138546e-01 -9.59829912e-02 1.65627360e-01 8.81090820e-01 -7.23362982e-01 3.08842182e-01 -2.96281338e-01 -8.15742314e-01 2.86581665e-01 6.19611219e-02 -6.76671147e-01 2.42289245e-01 -1.58288062e+00 1.14105022e+00 4.28543359e-01 6.95043383e-03 -7.16484249e-01 -3.14766854e-01 -8.05362761e-01 -6.40488043e-02 2.88879365e-01 -4.70393002e-01 7.08525002e-01 -1.09147632e+00 -8.46368909e-01 1.34995770e+00 7.77143911e-02 -1.78190082e-01 3.60718489e-01 -2.36155406e-01 -8.35827410e-01 1.84709325e-01 3.48231137e-01 4.97013092e-01 7.93784857e-01 -1.48574507e+00 -2.65281558e-01 -5.25753498e-01 3.13193142e-01 1.20401129e-01 -1.12632084e+00 5.43838799e-01 -1.53272673e-01 -6.31791055e-01 -3.07145149e-01 -9.41999912e-01 5.16943216e-01 -4.26690698e-01 -1.22649491e+00 -3.12133998e-01 1.08721399e+00 -9.15300667e-01 1.57772326e+00 -2.12193274e+00 3.17465901e-01 1.63196295e-01 6.42214179e-01 5.32997668e-01 -6.08241074e-02 9.61970866e-01 1.07435629e-01 6.67436540e-01 -3.14310014e-01 -2.85450965e-01 5.62755801e-02 -1.90955579e-01 -2.29056567e-01 6.29775345e-01 1.45683438e-01 7.21958339e-01 -8.55698049e-01 -3.46313715e-01 -1.50520355e-01 5.02047420e-01 -3.62662859e-02 1.34459868e-01 2.12267026e-01 3.30146760e-01 -4.50601727e-01 6.16280198e-01 4.73038912e-01 -3.05807501e-01 1.47096068e-01 -8.71786922e-02 4.91571166e-02 3.32636498e-02 -7.40820467e-01 4.81011808e-01 -5.87053485e-02 9.72997308e-01 1.92696869e-01 -4.31711167e-01 8.95865440e-01 2.62876958e-01 7.70947412e-02 -5.34533262e-01 3.21153551e-01 1.52780026e-01 -3.25893998e-01 -7.77136981e-01 5.85947216e-01 -1.64748326e-01 -4.20557141e-01 7.54521787e-01 -2.64320225e-01 7.34853029e-01 1.46286711e-01 5.10385454e-01 1.30159855e+00 -4.65115637e-01 2.75053382e-01 1.39872774e-01 7.29067087e-01 -9.96711031e-02 2.05890507e-01 6.12045944e-01 -5.80466330e-01 3.13358396e-01 8.36765289e-01 -4.53026742e-01 -9.19114769e-01 -9.89342511e-01 1.67425111e-01 1.41848922e+00 5.42018831e-01 -1.26998723e-01 -8.07118118e-01 -1.04183674e+00 1.32976308e-01 8.34140658e-01 -8.02678168e-01 -3.72983992e-01 -4.77090120e-01 -7.04966724e-01 1.05067587e+00 6.01059310e-02 7.68239379e-01 -1.24984288e+00 -2.61180043e-01 -3.61441262e-02 -6.21756077e-01 -9.53531802e-01 -5.92181206e-01 -4.71685857e-01 -5.36983050e-02 -1.30267763e+00 -7.48238921e-01 -5.91789842e-01 6.12614691e-01 1.84114471e-01 1.01023614e+00 3.50283056e-01 2.35632971e-01 3.57346743e-01 -3.71783912e-01 -8.77066478e-02 -5.36353409e-01 3.33237559e-01 1.94468021e-01 4.92896378e-01 5.90637028e-01 -2.68378049e-01 -3.86396229e-01 4.37320709e-01 -1.05310118e+00 -2.72523552e-01 1.51301533e-01 6.60210013e-01 -4.64220434e-01 -1.69195130e-01 5.93979120e-01 -1.21903515e+00 1.07264221e+00 -9.99067545e-01 2.34833762e-01 3.66116434e-01 6.10785559e-02 -5.59213161e-01 6.54204071e-01 -7.10388899e-01 -8.15386593e-01 -5.33687890e-01 5.41617945e-02 -1.75953597e-01 -4.26668346e-01 5.47322989e-01 -4.97914366e-02 -1.14586353e-01 9.76373792e-01 7.14743286e-02 -2.08662078e-01 -3.02221000e-01 7.73762837e-02 1.10326970e+00 3.04490954e-01 -4.34256077e-01 1.07202733e+00 4.19564635e-01 -3.78430665e-01 -9.26327765e-01 -9.01946902e-01 -5.43834507e-01 -2.89456367e-01 -6.25573754e-01 9.06281948e-01 -5.67301571e-01 -1.11195695e+00 6.70179665e-01 -1.49571764e+00 1.75493807e-01 7.16508269e-01 -2.98999064e-02 2.13875607e-01 5.13229489e-01 -9.15084362e-01 -9.44627285e-01 -5.00157952e-01 -6.15867496e-01 7.37587750e-01 2.94328064e-01 -6.11988068e-01 -1.16911781e+00 2.04541117e-01 6.28425419e-01 3.28929991e-01 6.68974400e-01 9.84531283e-01 -1.05188465e+00 -4.14258987e-03 -4.65614468e-01 -4.71715987e-01 7.25964382e-02 1.31932355e-03 1.25741716e-02 -8.36452067e-01 -2.28438675e-01 -2.49462157e-01 -5.71429849e-01 6.64004922e-01 -4.74902689e-01 4.68076766e-01 -8.07413638e-01 -5.15468955e-01 -1.24003358e-01 1.05731714e+00 7.56332129e-02 6.36562049e-01 5.22428036e-01 7.80390143e-01 1.00982499e+00 3.50151844e-02 3.80994588e-01 3.96459758e-01 6.01958573e-01 5.60841203e-01 4.57177870e-02 2.22247571e-01 -3.36557508e-01 6.82466984e-01 4.99634773e-01 3.25202420e-02 -5.87272108e-01 -1.25822031e+00 5.71705997e-01 -1.79929280e+00 -1.29099894e+00 -2.56520659e-01 1.81524110e+00 6.23872817e-01 -1.48564965e-01 4.38810438e-01 -2.65020490e-01 1.35673976e+00 3.96339208e-01 -4.39847678e-01 -4.33443159e-01 -2.32995689e-01 -3.65487337e-01 8.35090131e-02 2.25929990e-01 -1.37455845e+00 1.00194073e+00 5.15759468e+00 5.75477958e-01 -1.18268061e+00 3.10364604e-01 6.89311206e-01 4.06661164e-03 -6.83133602e-02 -4.65240747e-01 -5.71089089e-01 8.22679996e-01 7.85709381e-01 -2.45451313e-02 4.12954897e-01 5.86190939e-01 -1.23986360e-02 3.03889960e-02 -9.05894101e-01 1.03883922e+00 5.95647871e-01 -1.03590405e+00 7.35166892e-02 5.65633811e-02 6.06712997e-01 -3.74515593e-01 1.56366765e-01 5.04051983e-01 -1.41123354e-01 -9.88438845e-01 7.84401536e-01 4.48606223e-01 3.79302472e-01 -7.62421191e-01 9.62560177e-01 4.88235235e-01 -6.24898016e-01 -1.69981927e-01 -1.39278904e-01 1.00339688e-01 9.78945494e-02 3.47606927e-01 -4.06760097e-01 1.52760074e-01 6.25699997e-01 4.73238677e-01 -8.63864183e-01 8.41163158e-01 -4.19825613e-01 6.91722870e-01 -1.45006597e-01 -4.75801021e-01 3.93136770e-01 8.69719014e-02 8.62547219e-01 1.35937095e+00 -4.84271441e-03 1.50500432e-01 1.47201613e-01 9.91261661e-01 -4.68147069e-01 1.78730831e-01 -8.53347361e-01 -6.23994708e-01 5.42422891e-01 1.35260701e+00 -4.88264948e-01 -7.74023384e-02 -4.31117713e-02 1.19294357e+00 5.47832012e-01 5.64823687e-01 -9.98508096e-01 -5.57743847e-01 3.35395426e-01 1.13204956e-01 -2.37645954e-01 8.60096607e-03 -5.96178621e-02 -1.09733057e+00 -8.41149241e-02 -8.29351842e-01 5.05739868e-01 -7.35880494e-01 -1.79504216e+00 6.29284024e-01 -4.19601023e-01 -8.09082568e-01 9.89389420e-02 -5.02732754e-01 -7.62876809e-01 7.70093262e-01 -8.05976093e-01 -1.32756829e+00 -3.03320825e-01 3.09724450e-01 -1.36490956e-01 -1.79010987e-01 6.81774676e-01 3.98791403e-01 -1.14468670e+00 7.32475519e-01 -2.24228635e-01 8.25912058e-01 7.47063398e-01 -7.88856387e-01 -1.47876143e-01 6.50707066e-01 -2.25979298e-01 8.66517484e-01 7.25623906e-01 -8.02636683e-01 -1.07596612e+00 -9.84365702e-01 1.17450094e+00 -8.06876957e-01 9.62905407e-01 -3.39470208e-01 -9.30935800e-01 5.92433691e-01 4.38756526e-01 -5.66451371e-01 8.44530404e-01 2.53833354e-01 -6.29245102e-01 2.47847766e-01 -1.31047165e+00 7.88380861e-01 8.01014781e-01 -6.99608684e-01 -4.91874993e-01 4.81088877e-01 4.79477167e-01 -1.07742369e-01 -8.13128471e-01 3.51840742e-02 3.43468547e-01 -1.07111347e+00 6.13817096e-01 -9.93872821e-01 9.10776913e-01 2.67289905e-03 7.71253407e-02 -1.16362524e+00 -2.70710975e-01 -4.20033813e-01 -3.06361616e-01 1.67874861e+00 4.07891333e-01 -7.25612760e-01 5.73894858e-01 6.76764190e-01 1.64994851e-01 -5.56703568e-01 -9.06039298e-01 -4.27702308e-01 6.64702952e-02 1.27682671e-01 2.42956012e-01 1.65091145e+00 2.78624296e-01 7.63822556e-01 -6.99537933e-01 2.82552421e-01 6.34414077e-01 -1.98792592e-01 7.51453161e-01 -1.06958747e+00 3.34057093e-01 -6.45925522e-01 -3.88068229e-01 -4.90673751e-01 3.24393064e-01 -7.13598430e-01 -2.05847442e-01 -1.42286646e+00 6.74105048e-01 -1.78569858e-03 -6.98438361e-02 6.35156631e-01 -2.83944905e-01 5.40323079e-01 3.55379701e-01 3.76194298e-01 -7.56059051e-01 4.12556529e-01 8.04447055e-01 -4.34665591e-01 -1.04972452e-01 -2.90163487e-01 -7.54245400e-01 6.28393412e-01 6.88304424e-01 -3.84844780e-01 2.66469926e-01 -1.34929225e-01 6.08465672e-01 -1.49012357e-01 7.23547161e-01 -7.36261129e-01 1.66917518e-01 -6.69458508e-02 2.55693465e-01 -2.93254465e-01 3.29506844e-01 -5.19558012e-01 -1.11560978e-01 4.10894662e-01 -3.36634636e-01 -5.65182716e-02 8.69887322e-02 5.00530541e-01 -2.26958022e-01 -2.86764592e-01 9.26169813e-01 4.29481491e-02 -5.36232352e-01 5.56310900e-02 -5.55767953e-01 2.00668380e-01 1.17656684e+00 -1.75548252e-02 -1.01300454e+00 -7.21295536e-01 -7.09856510e-01 2.60111153e-01 4.89827156e-01 5.10277569e-01 5.87075233e-01 -1.31396019e+00 -8.38330209e-01 -4.02014047e-01 3.30241770e-01 -9.66686964e-01 3.60249996e-01 8.46930325e-01 -3.39349717e-01 2.08721757e-01 -2.62061097e-02 -1.97023019e-01 -1.20673943e+00 6.33693159e-01 4.11080927e-01 3.13987513e-03 -3.37513179e-01 6.69310153e-01 1.39372811e-01 -6.77520394e-01 2.54644454e-01 9.81665730e-01 -5.38438499e-01 4.35372829e-01 6.40457094e-01 6.62075222e-01 -3.80413294e-01 -1.38744569e+00 -4.78150308e-01 1.76490054e-01 -9.28967074e-02 3.07930321e-01 8.91915441e-01 -1.30377948e-01 -6.83546364e-01 4.70734715e-01 1.24194586e+00 1.48749813e-01 -1.73091963e-01 -1.20517053e-01 1.74749926e-01 -3.41794282e-01 -4.07264948e-01 -9.56834674e-01 -8.99034083e-01 8.26554000e-01 3.67990643e-01 8.88306737e-01 6.07671618e-01 1.36385024e-01 1.14093983e+00 3.29421908e-01 1.91708997e-01 -8.95228565e-01 4.53389525e-01 6.20113909e-01 1.02580190e+00 -1.22682440e+00 -3.61136556e-01 -4.04930413e-01 -7.55900383e-01 9.88808393e-01 9.50661063e-01 2.18604133e-01 2.67708033e-01 -5.06346881e-01 7.02346563e-02 -4.64212567e-01 -3.69985968e-01 1.04953581e-02 3.12851369e-01 3.72588038e-01 3.50785583e-01 1.21573634e-01 -3.58832777e-01 4.12328690e-01 9.83675867e-02 -6.26207352e-01 6.12756014e-01 6.05111897e-01 -5.22667170e-01 -4.43039626e-01 -7.60215163e-01 2.65170187e-01 -5.20941675e-01 6.11859560e-02 -1.34850192e+00 7.82501698e-01 2.27262735e-01 1.14483011e+00 -1.77660033e-01 -7.51891017e-01 2.67015398e-01 1.59561202e-01 -1.65585667e-01 -6.24511421e-01 -1.00301969e+00 -4.95211601e-01 4.99264330e-01 -1.63071588e-01 -2.81749010e-01 -2.43836984e-01 -9.76510763e-01 -1.04068947e+00 -2.25546405e-01 7.04208836e-02 3.72884065e-01 9.12862420e-01 3.42432320e-01 -3.42233367e-02 7.38417447e-01 -6.22347414e-01 -3.24948370e-01 -1.12229133e+00 -4.65665013e-01 9.53779161e-01 9.89357233e-02 -7.44249046e-01 -5.17891526e-01 -3.06072593e-01]	[8.499442100524902, 10.680249214172363]
ee6b4110-69e5-4c19-be45-8e205f868e42	valuing-distributed-energy-resources-for-non	2301.06636	null	https://arxiv.org/abs/2301.06636v2	https://arxiv.org/pdf/2301.06636v2.pdf	Valuing Distributed Energy Resources for Non-Wires Alternatives	Distributed energy resources (DER) as non-wires alternatives, regardless of owner, have the potential to reduce system operating costs and delay system upgrades. However, it is difficult to determine the appropriate economic signal to incentivize DER investors to install capacity that will benefit both the DER investors and the system operator. In an attempt to determine this co-optimal price signal, we present a bilevel optimization framework for determining the least cost solution to distribution system over-loads. A key output of the framework is a spatiotemporal price signal to DER owners that simultaneously guarantees the DER owners' required rate of return and minimizes the system operation costs. The framework is demonstrated with a case by which the system operator considers utility owned battery energy storage systems, traditional system upgrades, and energy purchase from DER owners. The results show that by valuing DER for non-wires alternatives the utility owned storage system sizes can be reduced, less hardware upgrades are necessary, and upfront capital costs as well as operating costs are reduced.	['Michael E. Webber', 'Nicholas D. Laws']	2023-01-16	null	null	null	null	['bilevel-optimization']	['methodology']	[-5.30480206e-01 4.30484325e-01 -3.54175657e-01 1.32100329e-01 -5.33772588e-01 -9.06518638e-01 1.60461560e-01 4.63258326e-02 -6.63200691e-02 1.04519403e+00 -9.42383260e-02 -5.24215937e-01 -5.00982225e-01 -9.53862965e-01 -4.26412135e-01 -8.20196867e-01 9.35965851e-02 3.08100909e-01 -4.27181512e-01 -2.68523723e-01 9.96593609e-02 8.78206015e-01 -1.20430529e+00 -5.72330058e-01 6.96465909e-01 1.50475204e+00 2.44253889e-01 -5.49231982e-03 5.48121333e-01 3.25949192e-01 -4.75033462e-01 2.23938134e-02 6.25314295e-01 -4.02166456e-01 -2.09505960e-01 -2.91656077e-01 -9.74039435e-01 -9.16304052e-01 -1.28716469e-01 1.01327145e+00 6.72124267e-01 3.32833827e-02 5.70300221e-01 -1.62069178e+00 -5.25427938e-01 9.64666486e-01 -2.17148766e-01 2.40059137e-01 -1.98846221e-01 1.19994367e-02 1.18930709e+00 -5.97201943e-01 1.41467184e-01 6.55349076e-01 5.75435050e-02 9.54094604e-02 -1.28525686e+00 -5.89478672e-01 -2.36760050e-01 1.97054505e-01 -1.49428535e+00 -6.34003937e-01 1.05583346e+00 -1.42059520e-01 1.55561233e+00 6.23969853e-01 1.12229383e+00 -1.77306458e-01 4.30599660e-01 4.63020742e-01 8.77917945e-01 -3.93675208e-01 6.16818249e-01 3.36589366e-01 -2.76353091e-01 -3.09535027e-01 8.78462195e-01 4.42563593e-02 9.14902613e-02 -5.98526234e-03 1.71451360e-01 -3.27542454e-01 -2.38340139e-01 -6.97680235e-01 -4.83619392e-01 4.24939036e-01 2.45702565e-01 4.25099045e-01 -5.71993351e-01 2.51581788e-01 1.78751871e-02 1.56851843e-01 2.18971133e-01 5.11470973e-01 -3.17176998e-01 -1.79259196e-01 -8.99402916e-01 -6.53419867e-02 7.70461679e-01 7.87724614e-01 3.85718882e-01 5.47657549e-01 1.42604306e-01 1.18636400e-01 1.89991653e-01 7.62930334e-01 2.15146452e-01 -9.42907095e-01 1.89185292e-01 3.94991040e-01 8.20406616e-01 -2.58681983e-01 -2.55275100e-01 -4.16684300e-01 -3.21866423e-01 2.77335882e-01 -1.95049196e-01 -4.15893227e-01 -1.07532263e-01 1.45021605e+00 -6.27541170e-02 -6.57242179e-01 9.68372151e-02 5.23090303e-01 -2.71898866e-01 7.80049086e-01 -2.64444619e-01 -6.65191174e-01 1.04622877e+00 -3.87215614e-01 -9.21437085e-01 2.03940570e-01 6.02819443e-01 -3.80766332e-01 5.15266657e-01 2.51321420e-02 -1.84771907e+00 2.60394305e-01 -1.34521472e+00 3.22827131e-01 -4.54006165e-01 2.19601557e-01 3.25467326e-02 6.60449445e-01 -1.04912937e+00 4.54812109e-01 -9.11227524e-01 -4.32990976e-02 3.44691485e-01 5.86550713e-01 4.68511790e-01 6.15894437e-01 -1.06908727e+00 1.57060087e+00 4.05729026e-01 4.40311521e-01 -7.34981716e-01 -8.53518903e-01 -5.17251194e-01 8.43765497e-01 1.51990443e-01 -2.90669680e-01 1.35075307e+00 -6.09172285e-01 -1.26678193e+00 -1.36527671e-02 3.42070192e-01 -6.66023433e-01 4.09366101e-01 3.95356536e-01 -2.12740779e-01 -1.37400813e-02 -1.07723743e-01 3.61964144e-02 -5.17859608e-02 -8.94696474e-01 -8.39348733e-01 -1.19342692e-01 -1.98894203e-01 2.67427325e-01 -6.22250140e-01 -3.42237800e-01 8.54421675e-01 -4.01795775e-01 -4.67402816e-01 -9.62798774e-01 3.88112366e-02 -3.10852498e-01 -3.52361441e-01 -5.03289640e-01 9.69131768e-01 -7.65845299e-01 1.05363667e+00 -2.00991964e+00 1.92956597e-01 3.69045168e-01 -4.13662702e-01 -3.79420847e-01 4.70670581e-01 6.67095900e-01 -3.20786119e-01 3.44585031e-01 2.66316444e-01 1.11929476e-01 6.66438162e-01 2.74578005e-01 -1.59920231e-01 3.87148172e-01 -1.85759552e-02 8.26515317e-01 -3.84365469e-01 2.82766342e-01 4.87778306e-01 -6.24855831e-02 -6.46584406e-02 1.09284513e-01 -1.61299720e-01 -3.05595160e-01 -3.80341172e-01 7.79379427e-01 4.40880805e-01 -7.59468302e-02 2.67682761e-01 -3.77860248e-01 -4.02587593e-01 1.48216799e-01 -1.27023244e+00 8.68276060e-01 -5.33838570e-01 5.60043573e-01 4.42082435e-01 -1.26925004e+00 5.77451646e-01 8.62370357e-02 9.23624575e-01 -9.90097821e-01 2.20305681e-01 4.98221964e-01 -1.10823795e-01 -2.65689254e-01 5.61632276e-01 -2.27090850e-01 -2.07596377e-01 5.42317510e-01 -4.97068197e-01 -6.65948018e-02 1.10890806e-01 5.82045950e-02 7.79488087e-01 -3.69111449e-01 2.42082223e-01 -1.01140785e+00 5.96029162e-02 2.74509098e-02 5.03846228e-01 -3.68894070e-01 1.91706479e-01 -7.78350174e-01 6.75940573e-01 2.38051698e-01 -1.38301063e+00 -9.57743168e-01 -1.97368622e-01 3.82557452e-01 5.05043924e-01 2.94856548e-01 -5.89445770e-01 -8.07901770e-02 6.12571120e-01 1.46011221e+00 -1.75737157e-01 -5.02103195e-02 -3.74542683e-01 -7.06401825e-01 -2.44367778e-01 7.10778356e-01 1.70546263e-01 -1.18216932e-01 -1.47879338e+00 1.94233522e-01 1.38463587e-01 -5.99936485e-01 -5.15280366e-01 6.57113314e-01 -4.91439342e-01 -7.03463376e-01 -8.27379644e-01 -1.54551297e-01 1.02617908e+00 8.15642625e-02 7.16591120e-01 -2.69832164e-01 -2.92436182e-01 4.65610743e-01 1.20493621e-01 -4.79536533e-01 8.89665410e-02 -6.19271807e-02 1.99825808e-01 -4.98119533e-01 -4.43762131e-02 -3.22523296e-01 -7.66315162e-01 3.26346755e-01 -4.48481888e-01 -8.49164873e-02 1.97370753e-01 5.78360140e-01 7.68362045e-01 9.91325200e-01 1.24281681e+00 -4.56120707e-02 6.88687027e-01 -6.91629410e-01 -1.29052949e+00 4.74266231e-01 -1.56282926e+00 2.54926592e-01 5.24320245e-01 4.98242602e-02 -1.01831734e+00 5.49017414e-02 5.17087221e-01 -2.13717341e-01 6.82068050e-01 2.79612392e-01 -8.09310973e-01 -1.52678207e-01 -3.67051810e-01 -2.71059130e-03 -8.12586863e-03 -4.87364829e-01 3.37031722e-01 4.78647679e-01 4.10713285e-01 -3.71507555e-01 8.17381084e-01 1.19633175e-01 3.06561112e-01 -3.30023408e-01 3.17125916e-01 3.80713552e-01 2.93619316e-02 -3.90597641e-01 5.20593941e-01 -1.16639602e+00 -1.04039872e+00 4.75834422e-02 -4.81430322e-01 -2.62610465e-01 -1.01155078e+00 3.14439267e-01 -3.63088369e-01 -2.91100014e-02 1.23131946e-01 -1.12115657e+00 -3.30160141e-01 -1.15685904e+00 1.48308292e-01 5.66035390e-01 -2.31704265e-01 -6.27449453e-01 -5.37031949e-01 3.44625488e-02 9.58775580e-01 4.75931168e-01 1.09789431e+00 -1.81482047e-01 -1.20642972e+00 -1.57032505e-01 1.81485757e-01 4.93094087e-01 4.20821190e-01 -9.13960487e-02 -1.42684922e-01 -1.02351332e+00 -4.15064916e-02 1.01312570e-01 -1.43983215e-01 5.79327047e-01 9.47412193e-01 -6.40265346e-01 -5.40862679e-01 2.20960081e-01 2.01656199e+00 9.09999609e-01 5.03937066e-01 4.69361484e-01 -2.41347209e-01 6.90597594e-01 6.17209911e-01 8.07927907e-01 6.16416335e-01 5.70735514e-01 4.55341548e-01 4.70989868e-02 4.58842993e-01 -1.80946589e-02 2.77645499e-01 3.77570391e-01 1.37788892e-01 -4.27119404e-01 -4.62970227e-01 8.64947557e-01 -1.59247696e+00 -7.13832974e-01 3.74990612e-01 2.09337711e+00 3.48074466e-01 1.80065870e-01 4.05275166e-01 2.98756033e-01 5.17908275e-01 -3.55340749e-01 -1.29080582e+00 -6.17981732e-01 -4.08644646e-01 5.17336279e-02 1.25640786e+00 1.54534981e-01 7.40580782e-02 -1.92107379e-01 6.27410269e+00 6.49573803e-01 -7.94371903e-01 1.49952129e-01 9.89464998e-01 -9.93583620e-01 -1.03068471e+00 3.31571162e-01 -6.47220433e-01 9.20119345e-01 1.56568730e+00 -1.61252749e+00 6.54637516e-01 9.15014923e-01 7.74114728e-01 -6.36642694e-01 -1.20180464e+00 5.13105035e-01 -4.88846451e-01 -1.61896789e+00 -7.13308275e-01 6.64738715e-01 6.24189258e-01 -2.72694230e-01 -1.71533808e-01 -5.36756292e-02 2.77490526e-01 -6.37012362e-01 1.25914049e+00 7.08636224e-01 5.64873695e-01 -1.46899700e+00 8.41026127e-01 2.30895996e-01 -1.48785162e+00 -5.85908830e-01 1.74583748e-01 -2.81877089e-02 8.29730272e-01 5.04487514e-01 -1.42528608e-01 2.50253677e-01 9.03597236e-01 -1.59334734e-01 6.07693866e-02 4.88006681e-01 2.10909352e-01 9.54812169e-02 -7.27033615e-01 -3.75662863e-01 -2.37042055e-01 -4.72272784e-01 9.65436623e-02 4.63480145e-01 8.29274416e-01 6.06422901e-01 -1.43786222e-01 1.18015230e+00 -1.55077249e-01 -2.38616720e-01 -4.71275359e-01 -3.97363812e-01 1.16396832e+00 1.11973095e+00 -8.05145741e-01 -1.17620461e-01 -1.60352230e-01 3.90213877e-01 -5.13585329e-01 3.33551407e-01 -7.01663136e-01 -8.14901292e-01 4.98725623e-01 4.53022599e-01 3.31807315e-01 -2.37978529e-02 -7.53841102e-01 -5.83063424e-01 2.59939969e-01 -8.22686478e-02 1.15906738e-01 -9.45934832e-01 -8.77811015e-01 -2.30165377e-01 3.66523623e-01 -8.97706032e-01 -5.98821342e-01 -2.40493178e-01 -7.11201310e-01 1.18571866e+00 -1.85743606e+00 -7.33126462e-01 4.44356613e-02 2.13225901e-01 2.33804673e-01 -2.83979207e-01 3.60316247e-01 4.95094180e-01 -9.83278632e-01 5.79200864e-01 8.69002938e-01 -4.57393169e-01 -3.05921465e-01 -1.12958837e+00 -4.88692909e-01 1.05320489e+00 -8.14061940e-01 1.51658386e-01 7.53576100e-01 -5.87045908e-01 -2.10321546e+00 -3.52755249e-01 5.95057249e-01 2.13232487e-01 9.13842142e-01 2.31235623e-02 -3.06461811e-01 4.36418653e-01 9.18284476e-01 -4.54687864e-01 6.20932698e-01 -7.23452508e-01 5.88154912e-01 -6.87937796e-01 -1.70986414e+00 3.06705028e-01 4.51139450e-01 -3.89580041e-01 -1.16865471e-01 6.45341873e-02 1.48364589e-01 -2.60553565e-02 -1.38164461e+00 3.15965772e-01 5.15303612e-01 -2.55009443e-01 7.34235644e-01 8.02261755e-03 -3.02399397e-01 -2.87594110e-01 -5.37544072e-01 -1.45817006e+00 -1.58472374e-01 -9.20541823e-01 -5.87820470e-01 1.51847625e+00 5.43592393e-01 -1.02409792e+00 5.70576608e-01 1.46542764e+00 -1.69903889e-01 -8.82145762e-01 -1.75087368e+00 -1.16230190e+00 4.12148535e-01 2.14101970e-01 1.11102724e+00 5.12131572e-01 5.99153996e-01 -1.30699202e-01 1.45301044e-01 2.03170210e-01 1.09118521e+00 1.56636387e-01 5.30535430e-02 -7.64378011e-01 2.90492480e-03 -7.39378810e-01 6.94349036e-02 -3.71741921e-01 3.34112793e-02 -7.55722880e-01 -2.14863464e-01 -1.70333529e+00 -8.18876922e-02 -5.50421119e-01 -6.34947658e-01 5.88733971e-01 7.32414424e-01 -4.93832082e-01 5.08903325e-01 3.82331073e-01 4.12023753e-01 8.07431996e-01 4.60641354e-01 -2.32071862e-01 -2.98433639e-02 -1.37884676e-01 -9.99549627e-01 4.60155815e-01 7.99806654e-01 -1.34857759e-01 -6.67823553e-01 -9.43356231e-02 4.78913337e-01 3.70831043e-01 2.70165503e-01 -5.86719215e-01 2.32583553e-01 -4.89413112e-01 1.79688707e-01 -1.03007877e+00 -7.54648820e-03 -1.38125205e+00 1.25133312e+00 8.63356173e-01 4.47111353e-02 3.80192131e-01 5.64986840e-02 2.76828766e-01 3.43915105e-01 -3.09867233e-01 8.08050990e-01 3.64313543e-01 -4.99670118e-01 -3.47641140e-01 -5.03721714e-01 -6.37835145e-01 2.00471354e+00 -2.98244089e-01 -6.97030365e-01 -1.94944069e-01 -5.78752220e-01 9.03518617e-01 6.95661545e-01 2.25156322e-01 1.21429816e-01 -1.36793244e+00 -1.81266353e-01 -3.02761912e-01 -4.11219031e-01 -2.64661998e-01 1.74636722e-01 4.40213799e-01 -2.69838780e-01 6.59689367e-01 -3.27572376e-01 -6.79946989e-02 -8.29145133e-01 3.04894030e-01 6.94412768e-01 9.33940113e-02 -3.94172937e-01 4.97018218e-01 -5.17161846e-01 7.40942717e-01 -1.17654622e-01 -5.08058012e-01 5.73915780e-01 5.37065506e-01 -1.17581477e-02 9.85436022e-01 1.38862744e-01 -1.49722576e-01 -4.21463013e-01 1.95979044e-01 4.05123025e-01 -1.07105762e-01 1.60667396e+00 -5.36222398e-01 -1.38720334e-01 1.85521841e-01 8.22229564e-01 -2.23639354e-01 -1.25304449e+00 2.05492139e-01 -1.52192246e-02 -3.66437912e-01 6.75182402e-01 -9.24574673e-01 -1.46124279e+00 1.82292312e-01 8.37876916e-01 8.90280485e-01 1.63270032e+00 -1.17812887e-01 8.30851614e-01 3.41830403e-01 6.89534366e-01 -1.78369474e+00 -4.55395430e-01 -4.57862735e-01 8.05154085e-01 -3.98786426e-01 2.81551719e-01 4.23700392e-01 -2.16040254e-01 8.32193613e-01 2.49975801e-01 -1.02818422e-01 1.02663827e+00 7.01214433e-01 -1.04208505e+00 1.80391774e-01 -5.74131131e-01 2.53285319e-01 -4.95028257e-01 1.63882587e-03 -1.27358943e-01 5.92783451e-01 -7.36318529e-01 9.74465489e-01 -2.39552371e-02 2.42169816e-02 1.00564229e+00 1.33433378e+00 -5.17778218e-01 -8.94480348e-01 -2.38590792e-01 7.50545681e-01 -2.70017207e-01 4.46490586e-01 1.29827634e-01 7.31005013e-01 2.64419675e-01 6.32717729e-01 4.22101319e-01 1.79326892e-01 9.65813160e-01 -9.65086818e-02 1.83093101e-01 9.16333124e-02 -6.50310591e-02 1.80416673e-01 2.96057165e-01 -1.33558735e-01 -1.97925866e-01 -8.92422676e-01 -1.64260554e+00 -6.91382051e-01 -8.82185757e-01 6.00074589e-01 1.04265916e+00 8.53082895e-01 6.45604908e-01 6.92160904e-01 1.27693212e+00 -7.20407248e-01 -9.59825158e-01 -3.67193580e-01 -1.26742482e+00 -3.48926753e-01 -1.56308282e-02 -5.80539405e-01 -7.62585700e-01 -2.37073660e-01]	[5.647950649261475, 2.450148344039917]
e3cde8b3-691c-4fe9-a007-7095398f68bc	infrared-image-super-resolution-via	2109.0096	null	https://arxiv.org/abs/2109.00960v1	https://arxiv.org/pdf/2109.00960v1.pdf	Infrared Image Super-Resolution via Heterogeneous Convolutional WGAN	Image super-resolution is important in many fields, such as surveillance and remote sensing. However, infrared (IR) images normally have low resolution since the optical equipment is relatively expensive. Recently, deep learning methods have dominated image super-resolution and achieved remarkable performance on visible images; however, IR images have received less attention. IR images have fewer patterns, and hence, it is difficult for deep neural networks (DNNs) to learn diverse features from IR images. In this paper, we present a framework that employs heterogeneous convolution and adversarial training, namely, heterogeneous kernel-based super-resolution Wasserstein GAN (HetSRWGAN), for IR image super-resolution. The HetSRWGAN algorithm is a lightweight GAN architecture that applies a plug-and-play heterogeneous kernel-based residual block. Moreover, a novel loss function that employs image gradients is adopted, which can be applied to an arbitrary model. The proposed HetSRWGAN achieves consistently better performance in both qualitative and quantitative evaluations. According to the experimental results, the whole training process is more stable.	['Guoming Pang', 'Qi Jiang', 'Qingzhong Wang', 'Zetao Jiang', 'Yongsong Huang']	2021-09-02	null	null	null	null	['infrared-image-super-resolution']	['computer-vision']	[ 5.38469434e-01 -2.03013957e-01 -5.24595529e-02 -2.02201590e-01 -9.91057098e-01 -1.16580211e-01 4.19562578e-01 -7.50171661e-01 -2.02642083e-01 8.69825602e-01 4.35739346e-02 -4.14655693e-02 -1.08046785e-01 -1.05097568e+00 -5.24353266e-01 -1.19629049e+00 6.08327925e-01 -1.72639534e-01 6.20965064e-02 -2.85888642e-01 -2.15278283e-01 3.84135932e-01 -1.29144490e+00 2.29167968e-01 1.15533268e+00 9.94684696e-01 3.73683304e-01 2.92849988e-01 1.32254781e-02 9.95958388e-01 -3.27579945e-01 -2.88719088e-01 4.31249827e-01 -7.79018044e-01 -6.00332558e-01 -1.88886330e-01 5.03277063e-01 -6.27945483e-01 -4.82208878e-01 1.21519852e+00 7.23542392e-01 2.25027740e-01 3.86213809e-01 -6.45396352e-01 -1.18662798e+00 4.12352830e-01 -8.65516365e-01 1.56448841e-01 4.48472574e-02 2.71153320e-02 6.65786743e-01 -4.78488564e-01 5.01048088e-01 1.15659308e+00 5.93899488e-01 7.72293627e-01 -1.27650523e+00 -7.06283629e-01 1.90035498e-03 2.09623396e-01 -1.32747579e+00 1.08711431e-02 8.64984930e-01 -1.68260589e-01 2.63159245e-01 3.51477742e-01 2.72516549e-01 1.10491288e+00 7.58465827e-02 5.83312571e-01 1.44655943e+00 -2.21288860e-01 7.23619908e-02 9.77877751e-02 -4.94963527e-01 3.41429889e-01 1.62569255e-01 1.99334607e-01 -1.02601968e-01 2.06871495e-01 1.31544316e+00 5.00829995e-01 -4.92036492e-01 7.95740783e-02 -9.08516467e-01 7.66634643e-01 8.45045447e-01 3.98626566e-01 -4.51891273e-01 -2.55709309e-02 4.41006571e-02 1.95685491e-01 8.08997273e-01 6.44999817e-02 -1.19751906e-02 4.32484299e-01 -7.30113626e-01 5.48206046e-02 2.06928235e-02 5.29336989e-01 7.75339067e-01 3.20053488e-01 -3.85411501e-01 1.12926960e+00 7.51167117e-03 5.70504129e-01 4.29771036e-01 -9.48532641e-01 2.18050569e-01 4.26643819e-01 1.14888206e-01 -7.93841779e-01 -1.24608129e-01 -5.00714898e-01 -1.44624162e+00 5.02378523e-01 -6.36270493e-02 -1.08026095e-01 -9.27168787e-01 1.61071265e+00 4.63687122e-01 2.35299900e-01 3.51930946e-01 1.16582417e+00 1.02297902e+00 8.14903617e-01 1.37095422e-01 -1.93012968e-01 1.17469585e+00 -8.62252295e-01 -7.55543649e-01 -1.64965242e-01 -4.66200374e-02 -6.60831869e-01 1.01791155e+00 2.78338403e-01 -1.10394084e+00 -8.28473389e-01 -9.19141531e-01 -2.80385286e-01 5.94802909e-02 1.28486887e-01 5.26648819e-01 2.71514058e-01 -9.75943804e-01 4.94228154e-01 -5.72553217e-01 -9.69423726e-02 4.91213173e-01 4.53768186e-02 -2.99222767e-01 -4.85873550e-01 -1.37481785e+00 6.72418535e-01 3.75429690e-01 3.31469566e-01 -7.00245321e-01 -6.09570265e-01 -8.76273096e-01 -2.28385553e-02 2.15986192e-01 -7.80897498e-01 8.73583257e-01 -9.96766388e-01 -1.84458721e+00 6.45937622e-01 6.34955068e-05 -1.73822775e-01 5.60136676e-01 -1.66164607e-01 -5.66674173e-01 3.00679058e-01 -5.31219020e-02 2.25744173e-01 1.10105073e+00 -1.50099325e+00 -4.64368671e-01 -3.91959727e-01 8.63418430e-02 2.59780347e-01 -1.33091465e-01 1.26995191e-01 1.40398846e-03 -7.22618639e-01 3.73789817e-02 -5.22785246e-01 -2.16251001e-01 -1.52191147e-01 -2.54648566e-01 -7.63247162e-02 9.61137295e-01 -1.01931739e+00 9.50852692e-01 -2.22830105e+00 2.49943599e-01 -1.22717731e-01 1.79859728e-01 4.60500985e-01 -1.06881328e-01 4.04322892e-02 -9.78876203e-02 1.89428434e-01 -3.06135058e-01 -1.07381061e-01 -3.57083440e-01 2.14031078e-02 -1.23946436e-01 3.19868684e-01 1.92883953e-01 9.39560652e-01 -8.50748062e-01 -3.73704135e-01 4.28373545e-01 9.65668857e-01 -4.86576557e-02 4.33334082e-01 -1.50066584e-01 9.62504327e-01 -6.61360979e-01 5.05424500e-01 1.04048848e+00 -2.73380101e-01 -9.33468863e-02 -5.05915403e-01 -3.14628869e-01 -3.70491385e-01 -6.84535444e-01 1.68824172e+00 -7.04871595e-01 2.46769205e-01 2.41411012e-02 -8.71495485e-01 1.10217977e+00 2.38160074e-01 3.47282678e-01 -1.07959032e+00 1.19095311e-01 9.43857208e-02 -5.43193877e-01 -5.13352811e-01 2.62082756e-01 -3.45505953e-01 4.18873668e-01 1.48115784e-01 -3.97853732e-01 -8.20278451e-02 -2.29476288e-01 -1.34774983e-01 8.16408098e-01 4.13156390e-01 2.42602155e-02 1.83971658e-01 6.63377047e-01 -2.55159914e-01 6.13169611e-01 3.84540409e-01 3.46109062e-01 9.31713223e-01 -5.64072207e-02 -5.12109756e-01 -1.14103031e+00 -9.95242000e-01 -3.05643886e-01 7.32075870e-01 4.47376758e-01 3.72982800e-01 -7.50416338e-01 -3.73593718e-01 -4.20834154e-01 3.96452159e-01 -5.79272568e-01 -3.20638537e-01 -4.79951292e-01 -9.24274445e-01 1.85621127e-01 5.14429927e-01 1.26397455e+00 -1.18435967e+00 -2.49597713e-01 1.14595607e-01 -3.26609015e-01 -1.17294097e+00 -2.52638191e-01 -4.04915124e-01 -9.25704062e-01 -7.48247564e-01 -1.08339977e+00 -7.78044820e-01 4.66820598e-01 6.62676752e-01 7.91800439e-01 -9.05894563e-02 -4.29805726e-01 1.59690287e-02 -5.27705252e-01 -8.75168219e-02 -2.90951461e-01 -5.06375171e-02 -3.27856332e-01 2.71873981e-01 2.04939350e-01 -5.32984912e-01 -1.02908337e+00 2.47627228e-01 -1.19798255e+00 1.42057344e-01 1.02331483e+00 1.07474291e+00 8.04787934e-01 3.14014018e-01 3.96905482e-01 -9.39869940e-01 2.80475855e-01 -2.85242587e-01 -5.87112188e-01 2.85507739e-01 -4.79863614e-01 -6.91577345e-02 7.75155365e-01 -2.50168085e-01 -1.74524963e+00 -1.73070028e-01 -2.30731308e-01 -4.72972363e-01 -1.25831008e-01 3.95945579e-01 -3.14219028e-01 -4.08328652e-01 6.66450977e-01 4.13851291e-01 1.56877935e-02 -6.43792450e-01 1.94371402e-01 7.26050913e-01 6.49590671e-01 -1.62103623e-01 1.18630838e+00 6.97684228e-01 -9.83060524e-02 -8.90411735e-01 -1.27039897e+00 -1.67647719e-01 -1.85342297e-01 4.76339757e-02 1.24334431e+00 -1.22971654e+00 -4.81027454e-01 6.43166363e-01 -9.98995602e-01 -5.18706679e-01 -2.05658793e-01 6.56624377e-01 -3.40317905e-01 3.64981651e-01 -7.02676117e-01 -7.75081933e-01 -6.89344764e-01 -8.85484040e-01 1.12763739e+00 7.34127522e-01 4.65663195e-01 -8.67205203e-01 1.16919456e-02 6.88014865e-01 8.38241696e-01 7.17634857e-01 7.42616951e-01 9.57905129e-02 -8.14742625e-01 -7.63512328e-02 -6.74888372e-01 7.76237607e-01 3.98093045e-01 -2.15843126e-01 -1.15280700e+00 -4.20564234e-01 8.28498304e-02 -3.24008673e-01 9.64004278e-01 4.56177115e-01 1.55789030e+00 -3.14181775e-01 5.03720082e-02 1.12251067e+00 1.75690687e+00 1.79108083e-01 1.23251772e+00 5.77214956e-01 9.69120145e-01 3.45451206e-01 5.95073402e-01 1.28856674e-01 7.80027211e-02 6.93885565e-01 5.85284114e-01 -7.82968819e-01 -1.46658644e-01 -9.28921551e-02 2.65661865e-01 3.93841952e-01 -7.14533389e-01 3.55200423e-03 -2.58846521e-01 1.05381295e-01 -1.70256627e+00 -1.31334448e+00 7.56541342e-02 2.19157791e+00 8.56760800e-01 -3.14266980e-01 -2.65830427e-01 -6.72175735e-02 8.40199232e-01 3.31216574e-01 -8.08238626e-01 9.56801921e-02 -2.64357030e-01 4.60656196e-01 4.68747973e-01 2.95686662e-01 -9.39228475e-01 7.53674209e-01 5.36533451e+00 9.45373535e-01 -1.34693515e+00 3.75331253e-01 7.60470927e-01 1.46020517e-01 -5.28513193e-01 -3.27593625e-01 -5.24461865e-01 4.46136892e-01 3.94153982e-01 -9.86037427e-04 6.79246545e-01 6.68713331e-01 3.29994917e-01 2.16242030e-01 -4.21616882e-01 1.04125512e+00 -4.68398891e-02 -1.01374459e+00 1.00456625e-01 -1.26219943e-01 9.60985243e-01 -1.02514409e-01 4.87872869e-01 9.50709805e-02 3.07547629e-01 -1.18090904e+00 1.64760873e-01 5.09466171e-01 1.30919266e+00 -9.60854292e-01 9.36298907e-01 5.04744239e-02 -1.17412734e+00 -5.64344637e-02 -8.40342343e-01 3.90896559e-01 3.75365540e-02 6.32528186e-01 -4.07281704e-02 1.10440695e+00 9.33939397e-01 7.63645113e-01 -2.11178079e-01 5.85163534e-01 -3.83900195e-01 3.30310136e-01 2.00476661e-01 5.15223205e-01 8.51378590e-02 -7.20049322e-01 2.30401888e-01 6.78672731e-01 4.79552656e-01 3.10229897e-01 -6.75793039e-04 1.01882005e+00 -1.59387484e-01 -3.92572470e-02 -4.42277908e-01 1.86632946e-01 1.52030453e-01 1.64166403e+00 -1.76952869e-01 -1.22081833e-02 -5.04989862e-01 1.20166528e+00 9.11585316e-02 8.22556555e-01 -8.74395847e-01 -4.34070736e-01 5.85218072e-01 3.17620486e-02 2.53804058e-01 8.07273090e-02 2.18200702e-02 -1.34817410e+00 1.90917924e-02 -8.11636508e-01 3.35449636e-01 -1.04515052e+00 -1.33645856e+00 9.53892410e-01 -1.88185334e-01 -1.35174739e+00 -1.66289229e-03 -3.06031227e-01 -6.82821929e-01 1.22938108e+00 -1.98512924e+00 -1.37997282e+00 -1.11770689e+00 6.79194212e-01 2.75851578e-01 4.76912111e-02 5.32003939e-01 2.94996738e-01 -6.84472024e-01 5.23409784e-01 4.78925079e-01 1.45822987e-01 5.42645216e-01 -9.45243537e-01 4.16187271e-02 9.10423219e-01 -2.28089124e-01 3.92693341e-01 4.60912973e-01 -4.28335130e-01 -1.13762331e+00 -1.55796814e+00 1.26976281e-01 6.19667768e-02 2.26593375e-01 -4.66419421e-02 -1.14074910e+00 5.70744455e-01 3.15491050e-01 2.61457175e-01 3.65525872e-01 -3.74924511e-01 -3.93344998e-01 -5.44179440e-01 -1.45868742e+00 4.72939104e-01 9.71054971e-01 -5.63519716e-01 -1.31022349e-01 2.95023203e-01 9.45307255e-01 -3.84753406e-01 -1.12250555e+00 6.69266224e-01 3.69641304e-01 -1.12641585e+00 1.17621374e+00 -2.18054265e-01 6.44384861e-01 -5.04324436e-01 2.21229289e-02 -1.31926048e+00 -6.27730906e-01 -3.66180867e-01 4.55388241e-02 1.24419487e+00 4.13444825e-02 -8.56518507e-01 5.56684077e-01 4.21150982e-01 -2.54231561e-02 -5.40719688e-01 -5.66110373e-01 -7.31325090e-01 -3.98560017e-02 4.61443573e-01 6.58810318e-01 9.76986766e-01 -8.27773213e-01 2.70179689e-01 -6.47209942e-01 2.45392904e-01 1.00000155e+00 1.95902646e-01 5.34540117e-01 -1.11013591e+00 -1.93292990e-01 -2.19320044e-01 -2.75306940e-01 -6.87878370e-01 4.64639664e-02 -5.60598254e-01 -3.63237597e-02 -1.83896780e+00 4.00582135e-01 -3.10438305e-01 -4.65269029e-01 4.18441415e-01 -4.56166029e-01 6.64107442e-01 -1.30797118e-01 2.76899278e-01 -3.04165006e-01 8.52105260e-01 1.60361731e+00 -3.44572037e-01 -8.35175216e-02 -4.41727228e-02 -8.20879757e-01 3.87835652e-01 1.02744877e+00 -6.51661977e-02 -3.42002809e-01 -5.95702112e-01 9.23575312e-02 -1.14553459e-01 5.15684426e-01 -8.57936323e-01 -4.34809476e-02 -2.11601526e-01 7.03388274e-01 -2.01241136e-01 2.07690790e-01 -7.91284204e-01 4.96010661e-01 3.28577757e-01 -2.30610758e-01 -4.05146629e-01 8.56180955e-03 5.58145523e-01 -3.86542559e-01 9.75812450e-02 1.18649542e+00 -2.28554502e-01 -6.52120590e-01 7.63523102e-01 1.51551127e-01 -1.11829035e-01 9.39531624e-01 -1.89642400e-01 -5.37064970e-01 -2.78971314e-01 -3.06308419e-01 -1.26549140e-01 6.34338737e-01 1.83068618e-01 7.34748125e-01 -1.45541334e+00 -1.04656661e+00 -1.02208722e-02 6.04217388e-02 5.95949054e-01 9.28218484e-01 7.38720655e-01 -6.07895315e-01 -1.19974189e-01 -1.60831809e-01 -4.13723499e-01 -1.09710586e+00 5.89317441e-01 3.60335112e-01 -2.30688572e-01 -8.74278307e-01 6.67015195e-01 5.12720287e-01 -2.54131377e-01 -1.90124020e-01 5.09272292e-02 -4.01674837e-01 -3.70983720e-01 9.22192454e-01 3.99983644e-01 -1.15238108e-01 -4.45912868e-01 1.37420490e-01 8.26484740e-01 -1.03708334e-01 2.92811424e-01 1.50782537e+00 -2.91758835e-01 -3.35511386e-01 1.24503814e-01 1.01139617e+00 -2.10452750e-01 -1.54057288e+00 -5.90547979e-01 -5.06028831e-01 -6.79379284e-01 3.99534464e-01 -6.65620029e-01 -1.47110057e+00 7.42048383e-01 7.68498600e-01 1.13282077e-01 1.60013723e+00 -8.79072100e-02 9.32343423e-01 -1.07500426e-01 4.54842120e-01 -7.21953213e-01 2.71133590e-03 8.64842907e-02 7.57348537e-01 -1.32913005e+00 -4.11485210e-02 -4.04955715e-01 -5.69138825e-01 9.82789218e-01 6.78843021e-01 1.88283157e-02 6.06792867e-02 -2.24982109e-02 2.77945250e-01 1.59827963e-01 -2.47695550e-01 -2.71976888e-01 1.92989618e-01 6.09587610e-01 4.04396325e-01 -1.67550460e-01 -2.29625225e-01 3.07632565e-01 3.22585285e-01 8.94286186e-02 2.02822149e-01 4.01484877e-01 -2.40220085e-01 -9.11895633e-01 -2.96751410e-01 3.66243631e-01 -6.20663941e-01 -2.33263001e-01 1.06506743e-01 6.51563287e-01 -2.50101406e-02 7.83226490e-01 -1.46639347e-01 -4.26120967e-01 1.67216241e-01 -4.80773121e-01 4.85235721e-01 -3.40541303e-01 -1.29591852e-01 -2.71574520e-02 -4.63412911e-01 -6.02172077e-01 -8.43029737e-01 -2.62830287e-01 -9.94074762e-01 -4.02844399e-01 -2.31056184e-01 1.08307391e-01 6.09962583e-01 7.71807730e-01 3.02885264e-01 7.78320432e-01 1.02623582e+00 -8.13797712e-01 -4.99850243e-01 -9.86634970e-01 -9.21406627e-01 4.13017213e-01 2.14434877e-01 -4.10142452e-01 -4.64073330e-01 1.51225766e-02]	[10.868151664733887, -2.0071334838867188]
fad909e0-88bc-46a0-be33-898bf9064bbe	open-domain-response-generation-guided-by	null	null	https://openreview.net/forum?id=6sXWzu3pWQE	https://openreview.net/pdf?id=6sXWzu3pWQE	Open Domain Response Generation Guided by Retrieved Conversations	Open domain response generation is the task of creating a response givena user query in any topics/domain. Limited by context and referenceinformation, responses generated by current systems are often "bland"or generic. In this paper, we combine a response generation model witha retrieval system that searches for relevant utterances and responses,and extracts keywords from the retrieved results to guide the responsegeneration. Our model uses a keyword extraction module to extract twotypes of keywords in an unsupervised fashion: (1) keywords in thequery not found in the retrieved utterances (DIFFKEY),and (2) overlapping keywords among the retrieved responses(SIMKEY). Given these keywords, we use a two-stage transformer thatfirst decides where to insert the keywords in the response, and thengenerates the full response given the location of the keywords. Thekeyword extraction module and the two-stage transformer are connected ina single network, and so our system is trained end-to-end.Experimental results on Cornell Movie-Dialog corpus, Douban and Weibodemonstrate that our model outperforms state-of-the-art systems in termsof ROUGE, relevance scores and human evaluation. Source code of ourmodel is available at: ANONYMISED.	['Anonymous']	2022-01-16	null	null	null	acl-arr-january-2022-1	['keyword-extraction']	['natural-language-processing']	[ 1.43756690e-02 4.07963306e-01 -2.35122576e-01 -4.59523946e-01 -1.58850443e+00 -8.96186352e-01 8.69042158e-01 4.62870933e-02 -7.42815793e-01 9.51361835e-01 6.09291613e-01 -1.13193132e-01 2.29246654e-02 -5.84520698e-01 -3.46728116e-01 -4.48226094e-01 4.95270342e-01 7.78289557e-01 6.84521616e-01 -6.84604287e-01 2.80414402e-01 1.34312719e-01 -1.02579856e+00 8.51062715e-01 8.13138902e-01 1.07221544e+00 1.98010609e-01 7.78581798e-01 -6.12168968e-01 8.55974019e-01 -8.20383608e-01 -5.53424120e-01 -6.98067397e-02 -6.39271259e-01 -1.41792893e+00 -6.06692769e-02 1.85996797e-02 -5.72561920e-01 -3.25690329e-01 7.39548504e-01 6.07995927e-01 3.35085094e-01 4.81296301e-01 -7.98344433e-01 -6.19626522e-01 8.80790293e-01 5.15584871e-02 8.02664608e-02 8.68526101e-01 -3.02082062e-01 9.01764274e-01 -1.42000508e+00 7.69776404e-01 1.30116022e+00 2.76250374e-02 7.37362444e-01 -1.12515879e+00 -6.02508783e-01 6.74585998e-02 -3.31010595e-02 -1.21824217e+00 -7.50986397e-01 5.91511011e-01 -2.37676218e-01 9.18406367e-01 5.07556617e-01 -1.98743358e-01 1.07516205e+00 1.56913087e-01 7.21121371e-01 6.96360171e-01 -4.72115666e-01 1.06401995e-01 6.50608659e-01 2.79454976e-01 -6.63549751e-02 -5.81400812e-01 -2.90505022e-01 -3.76347452e-01 -5.33380747e-01 1.66429773e-01 -2.82587353e-02 -2.18693152e-01 2.42579088e-01 -8.60760748e-01 1.04966962e+00 2.55665928e-01 1.41385645e-01 -7.04577506e-01 -2.56717831e-01 3.93259674e-01 7.38342285e-01 6.31503463e-01 4.48184669e-01 -2.41589919e-01 2.06981704e-01 -7.12769389e-01 8.37762833e-01 1.27331746e+00 1.14223981e+00 8.98192704e-01 -4.59627062e-01 -4.49551284e-01 1.41085923e+00 2.05227703e-01 6.29141867e-01 8.45904887e-01 -7.70786285e-01 6.96539164e-01 4.96277124e-01 7.05284119e-01 -9.60262656e-01 -1.91554844e-01 2.00182736e-01 -3.79097760e-01 -5.67398965e-01 2.14170486e-01 -6.56275988e-01 -6.26699328e-01 1.27676022e+00 4.43547964e-01 -7.36039758e-01 1.88190609e-01 1.14344037e+00 1.42213023e+00 8.19511294e-01 -6.74166754e-02 -1.01771004e-01 1.38034976e+00 -8.26732755e-01 -8.53002369e-01 -2.43180707e-01 4.37579334e-01 -1.16756666e+00 8.18945587e-01 6.69521019e-02 -1.22311330e+00 -4.41705406e-01 -5.48959553e-01 -1.78983018e-01 -3.98806900e-01 1.33699924e-01 4.10930812e-02 -7.53405765e-02 -1.25842798e+00 5.58627062e-02 1.20817631e-01 -5.77713847e-01 -4.54814345e-01 1.77685827e-01 -2.49460533e-01 5.37125841e-02 -1.74288619e+00 6.10820413e-01 2.30479553e-01 -2.45938972e-01 -8.89722824e-01 -1.42199129e-01 -5.39778054e-01 -1.55495152e-01 7.94519246e-01 -5.51004350e-01 1.79071021e+00 -6.78469121e-01 -1.42288041e+00 5.76035261e-01 -2.36932471e-01 -2.25249603e-01 3.16283524e-01 -2.27392033e-01 -4.40474242e-01 4.95825380e-01 3.25384706e-01 7.74338126e-01 7.18790710e-01 -1.08150744e+00 -8.14135611e-01 -1.86017215e-01 4.98032451e-01 4.71902728e-01 -8.27287212e-02 6.65515661e-01 -7.43933380e-01 -7.32199609e-01 2.19247505e-01 -9.00196552e-01 -2.26000354e-01 -5.50507605e-01 -6.85447693e-01 -8.61415803e-01 4.50693309e-01 -7.72064567e-01 1.45393956e+00 -2.00819421e+00 -1.02549233e-01 8.92152935e-02 -8.24798457e-03 2.12677717e-02 -2.02294275e-01 1.11231947e+00 1.29997656e-01 2.13363007e-01 2.11964935e-01 -1.17516346e-01 1.73259392e-01 -2.59012491e-01 -8.34771335e-01 -1.83046773e-01 3.61537151e-02 7.37753093e-01 -9.31181788e-01 -5.59976578e-01 -4.26054329e-01 -6.68814257e-02 -4.38471228e-01 8.82564604e-01 -6.11290336e-01 9.89574865e-02 -8.21063995e-01 4.22432989e-01 3.45542967e-01 -1.38106152e-01 -1.83398779e-02 1.66295737e-01 6.33252338e-02 8.19303095e-01 -1.04202521e+00 1.36082065e+00 -5.02273023e-01 6.59404323e-02 2.74624676e-01 -2.53995210e-01 8.01397502e-01 7.88679838e-01 2.95435876e-01 -6.46876037e-01 5.99033870e-02 4.58777159e-01 -4.52208489e-01 -8.84368658e-01 9.27765727e-01 2.33922377e-01 -7.87054718e-01 9.40054357e-01 -1.71340664e-03 -3.20670843e-01 3.76972139e-01 7.67702639e-01 1.04480672e+00 -3.33468132e-02 -3.01308855e-02 2.74378657e-02 7.32452452e-01 1.67074338e-01 8.91861692e-03 1.11848378e+00 3.84062946e-01 4.82040524e-01 3.58263910e-01 -5.14463037e-02 -7.50058115e-01 -5.87783694e-01 1.40407890e-01 1.56438935e+00 -1.20457202e-01 -2.27265880e-01 -7.23262072e-01 -7.50486195e-01 -1.52767584e-01 5.81680417e-01 -3.56411517e-01 2.15455852e-02 -5.40530682e-01 -3.53641771e-02 6.27178788e-01 2.49816790e-01 4.37526345e-01 -1.23464108e+00 -2.55828649e-01 4.71360981e-01 -8.66335690e-01 -1.14079559e+00 -1.14843297e+00 -1.05078891e-01 -2.90199041e-01 -8.18084419e-01 -8.02905679e-01 -9.62068737e-01 5.00375688e-01 3.17491144e-01 8.72495770e-01 1.76812857e-02 3.10020566e-01 2.84728676e-01 -7.31279373e-01 -1.15128428e-01 -5.77548862e-01 4.24547382e-02 -3.76606345e-01 1.82745848e-02 5.79278231e-01 -8.09017792e-02 -5.82544506e-01 5.17363310e-01 -1.02004552e+00 -3.48455727e-01 3.22609186e-01 8.75465512e-01 3.69970083e-01 -2.85039604e-01 8.25353026e-01 -9.16913450e-01 1.46078825e+00 -8.14380646e-01 -3.73537123e-01 3.88214916e-01 -4.79719579e-01 -1.19770356e-01 7.80096471e-01 -3.57428312e-01 -1.19358754e+00 -2.13298917e-01 -2.97660142e-01 1.35792838e-02 -3.79099190e-01 6.66493595e-01 -2.42930770e-01 4.51389611e-01 8.19905519e-01 1.99241430e-01 -3.24164659e-01 -7.11170554e-01 5.80811381e-01 1.20967758e+00 2.86172986e-01 -3.23629200e-01 2.64298797e-01 4.87829857e-02 -8.93024445e-01 -6.17554963e-01 -5.32543123e-01 -9.26133752e-01 -1.62173197e-01 -1.17830120e-01 7.48437881e-01 -8.58111620e-01 -4.38880503e-01 3.56669456e-01 -1.48015916e+00 7.87335560e-02 -1.15760542e-01 3.92411768e-01 -2.30853707e-01 8.71243477e-02 -8.85068953e-01 -8.33163083e-01 -7.39170194e-01 -8.71873915e-01 8.23723316e-01 2.00695992e-01 -6.05001032e-01 -7.59492159e-01 1.44148758e-02 2.92472571e-01 4.12343353e-01 -4.88387734e-01 9.76002038e-01 -1.57315433e+00 -2.86355793e-01 -5.58818281e-01 -2.94284858e-02 4.97636162e-02 -1.74169108e-01 -4.79313940e-01 -8.99332821e-01 6.43581823e-02 1.30060047e-01 -7.28817225e-01 6.57954156e-01 -1.94199070e-01 8.29019785e-01 -9.66190577e-01 -2.77519584e-01 -1.35390028e-01 1.02672434e+00 5.93849719e-01 3.53041559e-01 1.80445295e-02 1.60093516e-01 1.12847412e+00 6.98014915e-01 4.99399364e-01 7.73360491e-01 8.24385703e-01 1.34608019e-02 1.77224487e-01 1.34255871e-01 -4.06344086e-01 2.97753900e-01 4.94470775e-01 7.00662076e-01 -8.45328152e-01 -5.78034818e-01 7.00923443e-01 -1.75596845e+00 -8.61231387e-01 4.85812984e-02 2.13899517e+00 1.16371965e+00 -6.28997236e-02 2.61062473e-01 -4.70230788e-01 6.34110808e-01 4.88792174e-02 -3.82499933e-01 -5.72724402e-01 9.37318802e-02 -2.41952986e-02 6.65591434e-02 7.02542722e-01 -8.45521212e-01 1.06921041e+00 5.89894724e+00 5.36913514e-01 -8.95972192e-01 9.95701253e-02 6.48866773e-01 -3.62791233e-02 -6.63510501e-01 5.91786355e-02 -1.06836390e+00 3.61597389e-01 1.00827491e+00 -4.78676140e-01 4.09686685e-01 7.01771975e-01 2.67333537e-01 -1.56397238e-01 -1.06209564e+00 4.33716029e-01 4.31035757e-01 -9.11213517e-01 2.64258925e-02 -2.55429864e-01 1.87077224e-01 -1.72300301e-02 -1.56400785e-01 5.09041190e-01 7.77530074e-01 -4.40906674e-01 5.41530609e-01 4.10210639e-01 5.19775271e-01 -5.60994267e-01 1.00519240e+00 4.77166146e-01 -6.76491261e-01 -2.93601491e-02 -3.19225729e-01 5.76328516e-01 1.99236229e-01 1.27906784e-01 -1.39012003e+00 4.40370321e-01 7.75754273e-01 -7.45933689e-03 -2.20893100e-01 8.20332825e-01 -5.31938195e-01 4.01353419e-01 -1.11319341e-01 -3.87196809e-01 3.02262068e-01 4.38866206e-03 6.15876615e-01 1.30541968e+00 1.89509913e-01 4.72124457e-01 7.10230172e-01 6.03558838e-01 -3.20904166e-01 6.23511910e-01 -3.74310762e-01 -1.45075276e-01 8.71028125e-01 1.22878540e+00 -4.98571157e-01 -5.87155640e-01 -2.62028843e-01 8.50479841e-01 -2.06853487e-02 6.47276342e-01 -4.70539093e-01 -9.59054410e-01 4.63956110e-02 1.38833791e-01 3.21508646e-01 4.00892884e-01 3.27183068e-01 -9.11913693e-01 2.53443211e-01 -1.10435116e+00 7.17239261e-01 -8.75421226e-01 -1.17608929e+00 1.08818889e+00 3.39218020e-01 -9.88145173e-01 -1.05986857e+00 1.12701647e-01 -3.55247080e-01 1.24995017e+00 -1.39038110e+00 -7.71832228e-01 3.98333855e-02 6.25349641e-01 1.03574598e+00 1.15723293e-02 1.02045190e+00 3.01682800e-01 -2.69600809e-01 5.72389662e-01 -7.14373514e-02 3.12695473e-01 1.14541399e+00 -9.70413625e-01 4.53713030e-01 6.60998166e-01 -4.77809370e-01 9.68737841e-01 6.27611816e-01 -9.21412945e-01 -9.79839146e-01 -6.69390082e-01 1.77163208e+00 -1.75397336e-01 6.90102100e-01 -5.11950552e-01 -9.66215670e-01 2.34331995e-01 7.73498058e-01 -4.83674258e-01 7.77940691e-01 -1.85382321e-01 -2.41015613e-01 8.48779380e-02 -1.00789440e+00 5.21181166e-01 3.90828460e-01 -6.59411907e-01 -7.94164121e-01 7.55918980e-01 1.14365005e+00 -4.15772051e-01 -5.23434937e-01 -1.10354230e-01 4.76374686e-01 -5.05834222e-01 6.07313812e-01 -7.47234941e-01 3.61932993e-01 1.55862913e-01 -1.94163963e-01 -1.36406291e+00 -9.52710211e-02 -8.30208302e-01 -1.51260849e-02 1.25520051e+00 7.25218236e-01 -5.22786081e-01 3.52430463e-01 1.24295509e+00 -2.31929764e-01 -6.44783020e-01 -6.63792372e-01 -4.00901586e-01 2.02997059e-01 1.57774955e-01 9.32531655e-01 4.05786932e-01 4.18349147e-01 8.17636847e-01 -4.14217293e-01 -2.80476868e-01 -1.97927624e-01 1.79758817e-01 8.35897207e-01 -7.72834599e-01 -1.95974976e-01 -1.41878635e-01 3.92758280e-01 -1.57438147e+00 5.33309989e-02 -6.06508970e-01 4.47202235e-01 -1.57919931e+00 9.40663666e-02 -4.56918806e-01 3.27801816e-02 5.67951441e-01 -1.68028325e-01 -1.19530693e-01 -2.56529879e-02 4.15004164e-01 -7.60106325e-01 3.04849893e-01 8.87449682e-01 -4.46594842e-02 -3.28480124e-01 2.48623461e-01 -8.77542078e-01 3.99885952e-01 5.56309462e-01 -7.24771559e-01 -5.30981600e-01 -4.41933721e-01 2.45665297e-01 6.29226506e-01 1.84755638e-01 -2.59487748e-01 6.26337886e-01 -3.06618631e-01 1.37512013e-01 -8.52737248e-01 3.58770519e-01 -7.72741258e-01 -2.48637483e-01 -2.40667742e-02 -9.29040492e-01 4.82712358e-01 -2.00378627e-01 3.10818017e-01 -2.70172983e-01 -6.34596348e-01 1.85454488e-01 -4.47829276e-01 -4.10388768e-01 1.71208829e-01 -7.76937187e-01 4.89239246e-01 5.65769851e-01 9.70354080e-02 -4.45683807e-01 -1.14632356e+00 -5.36118269e-01 4.07733917e-01 1.60838827e-01 7.59632170e-01 8.47444475e-01 -1.19979465e+00 -8.70049775e-01 9.84059647e-03 2.72779375e-01 -2.83760637e-01 2.03964114e-01 5.29126704e-01 1.10168070e-01 9.03862536e-01 6.28427982e-01 -8.41700956e-02 -1.05392623e+00 3.98501337e-01 2.09476963e-01 -2.47518495e-01 -1.24638706e-01 1.14180803e+00 1.77000508e-01 -6.99098885e-01 4.10760015e-01 2.56683659e-02 -7.95163035e-01 4.75050658e-01 1.02809727e+00 -2.99923848e-02 2.24098757e-01 -7.04506814e-01 -3.06873024e-01 -1.96647152e-01 -7.22106576e-01 -5.88301599e-01 9.54155803e-01 -3.88043910e-01 -2.30138272e-01 2.27840215e-01 1.20139515e+00 1.81953445e-01 -6.84736431e-01 -7.67416716e-01 1.06761068e-01 -4.50236171e-01 -4.24286097e-01 -9.13692355e-01 -5.19521832e-01 3.40169996e-01 2.04957157e-01 4.99473572e-01 1.00531352e+00 2.16332614e-01 1.02951908e+00 5.55527270e-01 3.84200782e-01 -1.49874926e+00 4.41617250e-01 7.65431583e-01 1.16965258e+00 -1.19905984e+00 -2.77972370e-01 -2.15955645e-01 -9.00259435e-01 9.47940588e-01 7.33953893e-01 3.03797573e-01 5.97835898e-01 -1.37202322e-01 4.96886969e-01 -8.43932703e-02 -1.07095087e+00 6.97549107e-03 3.53551745e-01 1.01090036e-01 4.45939153e-01 -2.83643723e-01 -6.03089690e-01 7.62081444e-01 -3.11795384e-01 -3.31661820e-01 4.58996326e-01 1.07093406e+00 -5.82505047e-01 -1.26546013e+00 -1.29153803e-01 3.82928908e-01 -7.37374663e-01 -2.60825932e-01 -1.00162601e+00 3.37232023e-01 -3.92472178e-01 1.81036282e+00 -2.00992793e-01 -6.35933280e-01 6.83764875e-01 2.03943893e-01 -3.93749058e-01 -9.30923164e-01 -1.12188125e+00 4.77356315e-01 6.33164346e-01 -3.07095170e-01 -6.72924742e-02 -4.62281495e-01 -1.14429116e+00 3.10853925e-02 -7.07904756e-01 8.52209389e-01 6.72517419e-01 9.63504195e-01 4.55603868e-01 -1.94665343e-02 9.90476072e-01 -1.63366094e-01 -1.09496784e+00 -1.20059419e+00 -1.05996681e-02 4.19616729e-01 1.59367591e-01 -5.71771748e-02 -1.13986932e-01 -7.37638026e-02]	[12.376802444458008, 8.005331039428711]
e804cf45-0bd8-495f-b7f6-08d7ce34cf81	counterfactual-inference-of-the-mean-outcome	2102.08975	null	https://arxiv.org/abs/2102.08975v2	https://arxiv.org/pdf/2102.08975v2.pdf	Adaptive Doubly Robust Estimator from Non-stationary Logging Policy under a Convergence of Average Probability	Adaptive experiments, including efficient average treatment effect estimation and multi-armed bandit algorithms, have garnered attention in various applications, such as social experiments, clinical trials, and online advertisement optimization. This paper considers estimating the mean outcome of an action from samples obtained in adaptive experiments. In causal inference, the mean outcome of an action has a crucial role, and the estimation is an essential task, where the average treatment effect estimation and off-policy value estimation are its variants. In adaptive experiments, the probability of choosing an action (logging policy) is allowed to be sequentially updated based on past observations. Due to this logging policy depending on the past observations, the samples are often not independent and identically distributed (i.i.d.), making developing an asymptotically normal estimator difficult. A typical approach for this problem is to assume that the logging policy converges in a time-invariant function. However, this assumption is restrictive in various applications, such as when the logging policy fluctuates or becomes zero at some periods. To mitigate this limitation, we propose another assumption that the average logging policy converges to a time-invariant function and show the doubly robust (DR) estimator's asymptotic normality. Under the assumption, the logging policy itself can fluctuate or be zero for some actions. We also show the empirical properties by simulations.	['Masahiro Kato']	2021-02-17	null	null	null	null	['counterfactual-inference']	['miscellaneous']	[ 1.61336109e-01 -9.65002701e-02 -9.12440002e-01 -3.04950386e-01 -5.46438575e-01 -4.55380499e-01 4.15971220e-01 1.27535731e-01 -6.68829322e-01 1.18457103e+00 2.71588087e-01 -5.94602406e-01 -3.67225051e-01 -6.62172318e-01 -9.05165553e-01 -1.06384027e+00 -1.29435018e-01 5.35723567e-01 -9.44788009e-03 4.06496495e-01 1.56014889e-01 2.02558607e-01 -1.12835515e+00 -1.30130261e-01 8.03819656e-01 8.17760587e-01 3.55961546e-02 5.11961281e-01 -1.05265997e-01 3.14162850e-01 -7.04981804e-01 -1.74802318e-01 1.86530024e-01 -5.02559483e-01 -4.01023209e-01 -4.98250611e-02 -2.45426789e-01 -4.50594842e-01 3.28841545e-02 1.16449738e+00 3.82634640e-01 2.07460627e-01 7.43014097e-01 -1.37690306e+00 -2.87853003e-01 9.24503028e-01 -9.46821511e-01 1.02693193e-01 1.17790580e-01 1.80930402e-02 8.91808093e-01 -2.99326964e-02 2.04865098e-01 1.28077316e+00 3.67339045e-01 3.16954643e-01 -1.42974973e+00 -8.88387024e-01 4.51218307e-01 5.63261434e-02 -1.19622600e+00 -3.31330389e-01 5.17804801e-01 -3.28659624e-01 -9.18184519e-02 1.91895783e-01 5.69362342e-01 1.25884306e+00 4.67017502e-01 7.68630922e-01 1.20493305e+00 -3.14857602e-01 7.82251239e-01 1.64939519e-02 -8.53255689e-02 -5.98378107e-03 6.05209410e-01 2.18601432e-02 -1.13939658e-01 -6.93948746e-01 7.81332970e-01 3.73270959e-01 -2.48567417e-01 -9.90104526e-02 -9.32773888e-01 9.89490390e-01 7.94766285e-03 7.15310052e-02 -9.16748703e-01 3.04761142e-01 3.27359825e-01 2.74706900e-01 5.77761650e-01 -5.56481723e-03 -4.68955070e-01 -2.91327894e-01 -7.01434493e-01 3.93251061e-01 6.55267715e-01 5.34116864e-01 1.15285151e-01 -2.48363331e-01 -7.24473119e-01 6.74299061e-01 4.41135168e-02 7.03130722e-01 4.52811241e-01 -8.49087834e-01 3.03630322e-01 5.02290437e-03 9.33382869e-01 -6.83835924e-01 -2.69446254e-01 -4.48193282e-01 -1.04682374e+00 -2.24770084e-01 9.20674503e-01 -5.06054282e-01 -6.61324620e-01 2.16272974e+00 6.51279271e-01 2.96298534e-01 -3.73743683e-01 7.32136190e-01 -1.13320068e-01 4.66859281e-01 4.17025000e-01 -1.17242432e+00 1.32957256e+00 -2.53770668e-02 -1.00042319e+00 -5.43283410e-02 4.98526484e-01 -5.33309221e-01 9.95038092e-01 4.72562194e-01 -8.80768657e-01 1.13339610e-01 -5.16662419e-01 7.32715309e-01 2.20059767e-01 -1.60399079e-01 6.65652454e-01 5.96923709e-01 -4.35546517e-01 4.49639887e-01 -6.28642023e-01 -1.69843525e-01 4.44144636e-01 2.14397132e-01 -3.88137214e-02 -3.44531648e-02 -1.17155039e+00 2.22095683e-01 3.26480865e-01 -1.06122009e-01 -7.33582914e-01 -6.88262582e-01 -1.81917861e-01 2.34097287e-01 8.51136029e-01 -6.74673676e-01 1.51946867e+00 -9.84597206e-01 -1.64917898e+00 2.53160357e-01 -3.10615003e-01 -6.16815090e-01 7.15285420e-01 1.07456215e-01 -2.10088491e-01 -1.35132223e-01 3.14593256e-01 -3.47521722e-01 1.05691910e+00 -7.00999916e-01 -6.65861726e-01 -5.09079933e-01 7.45921955e-02 3.56217846e-02 -3.00347179e-01 1.00563886e-02 -5.67831919e-02 -7.14311123e-01 -9.08785686e-02 -1.10131240e+00 -3.88265640e-01 -2.77426749e-01 -4.26870346e-01 -2.84299642e-01 4.31645989e-01 -2.84697384e-01 1.38035595e+00 -2.18824291e+00 -2.56269008e-01 1.97241500e-01 -1.79117262e-01 -3.05789053e-01 1.39112189e-01 3.92580420e-01 -5.11994176e-02 2.05936894e-01 -1.25805959e-01 -3.81968021e-02 -1.14389628e-01 1.89584881e-01 -2.59292305e-01 8.44228089e-01 -4.85165328e-01 2.19221160e-01 -9.30081606e-01 -3.60857517e-01 -6.46097586e-02 -8.90433192e-02 -7.10777342e-01 2.00214282e-01 -3.71368557e-01 6.55925989e-01 -9.21695292e-01 2.90971130e-01 6.54269874e-01 -3.61086965e-01 4.12323505e-01 8.82065594e-02 -1.96813554e-01 -2.02904478e-01 -1.42808282e+00 8.50637496e-01 -4.56239372e-01 8.56782645e-02 9.10365582e-02 -1.52602613e+00 3.10697436e-01 5.40437043e-01 7.88149297e-01 -5.01779377e-01 2.68651605e-01 1.08963735e-02 1.71221390e-01 -4.05099601e-01 -3.30919288e-02 -4.77856696e-01 -9.96838883e-02 6.49274170e-01 -5.38315833e-01 3.68691593e-01 6.06165454e-02 1.40173547e-02 1.05452311e+00 -4.56670582e-01 6.55544221e-01 -2.48403490e-01 1.84289083e-01 -3.78367782e-01 8.89002323e-01 1.18264651e+00 -7.42787272e-02 1.30690694e-01 8.98659587e-01 -1.17631145e-01 -9.41652358e-01 -8.26433182e-01 -3.54048163e-01 9.48259354e-01 -5.25367931e-02 1.90364048e-01 -6.10838354e-01 -6.44009709e-01 2.60129809e-01 8.85221839e-01 -8.68331790e-01 -2.38149196e-01 -1.40088692e-01 -1.08793592e+00 -1.45923480e-01 2.48703286e-01 4.65017885e-01 -7.13369906e-01 -3.76530051e-01 5.47455609e-01 -1.58956543e-01 -7.11042523e-01 -7.47014344e-01 -1.72347590e-01 -8.27666879e-01 -1.04928625e+00 -8.11144769e-01 2.04083011e-01 6.06359839e-01 1.68228269e-01 7.63284624e-01 -3.11080247e-01 1.67042419e-01 3.65405351e-01 -1.64905101e-01 -6.43516302e-01 -2.29026854e-01 -2.12811962e-01 2.92623162e-01 5.24657428e-01 1.42614460e-02 -4.42557544e-01 -1.04752719e+00 4.25386846e-01 -1.02604735e+00 -4.12622958e-01 5.89037240e-01 9.19002175e-01 5.78414977e-01 2.29860619e-01 9.46110070e-01 -1.08569372e+00 7.45934427e-01 -7.77565181e-01 -8.21983933e-01 2.76150823e-01 -5.58142424e-01 1.97019577e-01 7.11078048e-01 -1.06217146e+00 -1.17902851e+00 -2.58221149e-01 2.05282539e-01 -3.14456582e-01 -9.32870619e-03 6.70381546e-01 -3.13558698e-01 5.03421187e-01 4.90681678e-01 -8.71606022e-02 1.43469006e-01 -3.94442797e-01 2.87493199e-01 9.24571216e-01 2.67611910e-03 -7.34278619e-01 3.41256976e-01 4.72187549e-01 1.48373321e-01 -6.92907035e-01 -1.06152368e+00 -2.79334038e-01 2.04307497e-01 -1.12130962e-01 4.57837850e-01 -6.35805488e-01 -1.27691841e+00 3.17355931e-01 -7.14015901e-01 -3.53301048e-01 -3.71303558e-01 1.04437053e+00 -5.99465191e-01 4.76690196e-02 -2.10854799e-01 -1.30251229e+00 -2.61028018e-02 -9.14873540e-01 6.06998980e-01 3.76442283e-01 -2.07529396e-01 -8.76219153e-01 -4.66725267e-02 5.00326864e-02 3.20359290e-01 2.63512254e-01 8.81449044e-01 -6.41524196e-01 -2.71861494e-01 -5.08756340e-01 9.19708535e-02 -1.01818912e-01 2.64490873e-01 -5.94908483e-02 -3.67911369e-01 -3.34786743e-01 7.36378282e-02 6.91908374e-02 3.92970920e-01 1.36478066e+00 1.55971837e+00 -7.70844638e-01 -5.41231394e-01 1.29949108e-01 9.83426988e-01 6.03777945e-01 3.44411552e-01 1.05686530e-01 -7.53594041e-02 2.35162228e-01 8.50714266e-01 1.08131361e+00 5.30385040e-02 6.58400774e-01 4.38503593e-01 3.18469912e-01 6.94189727e-01 -1.94004819e-01 2.56964535e-01 -3.36540863e-03 2.81792623e-03 -3.83675903e-01 -4.16888356e-01 4.67440099e-01 -1.88484108e+00 -1.16155159e+00 -2.49871034e-02 3.05193877e+00 1.19115210e+00 1.67015731e-01 4.49840605e-01 -2.21097991e-01 9.40941274e-01 -1.23002186e-01 -9.44998920e-01 -4.33900237e-01 2.01427713e-01 -1.29588872e-01 8.96374166e-01 2.01545402e-01 -7.70507634e-01 3.38775665e-01 6.15459776e+00 1.00169277e+00 -9.23366070e-01 2.49402255e-01 8.92277420e-01 -2.64431592e-02 -1.06143050e-01 2.05875874e-01 -7.29577482e-01 9.06123042e-01 1.06762993e+00 -6.75255477e-01 2.24770010e-01 7.43562877e-01 9.15312588e-01 -5.29550850e-01 -9.31082308e-01 6.85379505e-01 -6.81440234e-01 -8.84233654e-01 -3.37640375e-01 5.23509324e-01 7.12247074e-01 -5.42392552e-01 1.51831433e-01 3.01510543e-01 7.05345094e-01 -5.24929762e-01 2.96603024e-01 6.45671844e-01 7.39311576e-01 -9.38885391e-01 7.62019694e-01 6.11404181e-01 -6.67189181e-01 -4.78627354e-01 -3.34654719e-01 -1.82550088e-01 2.12973207e-01 1.30899000e+00 -6.54024303e-01 2.88874298e-01 4.51558292e-01 2.81201720e-01 2.58762270e-01 1.31966853e+00 -7.52584115e-02 1.17562425e+00 -6.28955960e-01 -2.25357100e-01 -1.36713153e-02 -4.30380106e-01 4.86309081e-01 5.55441856e-01 6.08039439e-01 3.19902569e-01 3.27347547e-01 3.80883038e-01 -1.16676219e-01 2.80187905e-01 -4.35831249e-01 -1.71171650e-01 7.24610209e-01 6.98145092e-01 -7.99490571e-01 -3.03690016e-01 -3.39111507e-01 5.53583264e-01 -1.54886097e-01 4.95894760e-01 -1.00394297e+00 -1.23975247e-01 7.44026423e-01 1.92819089e-01 1.94192410e-01 1.74027279e-01 -5.33241630e-02 -8.32586467e-01 -1.25943333e-01 -6.17034197e-01 7.89272308e-01 -2.53629416e-01 -1.21081114e+00 -2.74529785e-01 4.22718614e-01 -1.09679127e+00 -3.09178025e-01 3.80757861e-02 -5.84875762e-01 5.56613207e-01 -8.23121965e-01 -3.45338345e-01 2.72546023e-01 4.88698840e-01 2.76017070e-01 2.89986223e-01 3.54621351e-01 1.07284375e-01 -8.56695056e-01 6.13619030e-01 6.62186384e-01 -1.71726361e-01 6.75290883e-01 -1.05214179e+00 -5.60354531e-01 4.15080279e-01 -3.86460751e-01 6.01760507e-01 1.11742413e+00 -7.67753363e-01 -1.16424596e+00 -8.36642563e-01 2.28363916e-01 1.14081815e-01 7.89653182e-01 -1.90996062e-02 -8.69593799e-01 7.08351493e-01 -1.69982165e-01 1.37436777e-01 5.57926595e-01 3.16563904e-01 2.03708470e-01 -3.59512895e-01 -1.30502331e+00 8.55682790e-01 7.25077569e-01 1.30590349e-01 -6.89061061e-02 6.46120489e-01 5.43785453e-01 -7.03586489e-02 -8.38838518e-01 3.12326521e-01 6.72362089e-01 -7.72236586e-01 6.18493855e-01 -8.42872024e-01 -1.79928392e-02 2.93606371e-02 9.34727862e-02 -1.55578387e+00 -2.37947121e-01 -7.39199996e-01 -7.88691416e-02 1.32990849e+00 1.38115868e-01 -1.06227160e+00 7.37317264e-01 7.97168732e-01 5.06865680e-01 -4.61213738e-01 -1.29775763e+00 -8.56156707e-01 -4.49020043e-03 -3.46175224e-01 6.05648220e-01 7.84971237e-01 -2.11919501e-01 1.94348887e-01 -5.60986102e-01 1.56980246e-01 8.24077249e-01 1.80478320e-01 7.34952271e-01 -1.18427420e+00 -3.95358294e-01 -3.65826160e-01 -4.92478022e-03 -1.03337681e+00 1.51435047e-01 -1.29571766e-01 1.15481116e-01 -1.10056674e+00 4.77558792e-01 -5.48640013e-01 -3.68564039e-01 2.66387880e-01 -3.64039898e-01 -5.64987898e-01 -3.84022444e-01 8.13077837e-02 -2.77938992e-01 6.68613732e-01 1.11835647e+00 1.20866723e-01 -4.82121676e-01 9.01701152e-01 -6.35040283e-01 6.07649744e-01 7.86951065e-01 -8.55757713e-01 -5.99128425e-01 3.13105255e-01 1.22815333e-01 6.47505164e-01 6.87066242e-02 -3.29487950e-01 -2.76117101e-02 -8.16385090e-01 -4.72934581e-02 -3.86216938e-01 -3.22005078e-02 -9.02192712e-01 5.08350253e-01 6.05502129e-01 -4.43439662e-01 -2.03056827e-01 -1.62788242e-01 1.08278775e+00 1.55355811e-01 -2.66545504e-01 7.98901856e-01 -4.62507531e-02 1.44248649e-01 4.96913940e-01 -4.90251511e-01 1.94516227e-01 1.06250179e+00 9.60858539e-02 -8.52691755e-02 -8.70453656e-01 -6.54854596e-01 3.65165114e-01 1.39473766e-01 2.57300446e-03 2.28210717e-01 -1.26280999e+00 -6.64183199e-01 -2.13281423e-01 -1.14290215e-01 -2.69375473e-01 4.80926961e-01 1.18951297e+00 4.01433110e-01 1.97354272e-01 4.27970588e-01 -5.24740577e-01 -9.61827517e-01 7.03153670e-01 1.60976678e-01 -2.78622895e-01 -2.91299969e-01 2.53795475e-01 4.17990327e-01 3.61987621e-01 1.91739142e-01 -1.38143629e-01 -1.25832587e-01 1.70539483e-01 7.16222167e-01 3.12005162e-01 -3.35299999e-01 -5.62710762e-02 -5.21082431e-03 1.56223685e-01 -2.47141749e-01 -2.03794450e-01 1.28039551e+00 -2.88619846e-01 1.12761399e-02 7.96230197e-01 8.46192122e-01 -1.52614461e-02 -1.15737760e+00 -4.48632151e-01 1.38118509e-02 -6.66808963e-01 1.20883130e-01 -4.60871756e-01 -9.16826546e-01 2.19100207e-01 5.60315788e-01 6.05667770e-01 1.03703487e+00 -7.02292025e-02 3.59529942e-01 3.82790901e-02 4.25199986e-01 -1.07038844e+00 -2.79670089e-01 -1.21075427e-03 6.35087132e-01 -1.09148169e+00 8.76805484e-02 -8.56807753e-02 -4.06096816e-01 5.59939981e-01 1.58410341e-01 1.42860413e-01 8.63771141e-01 3.41203175e-02 -4.64815468e-01 2.90536553e-01 -7.16696739e-01 5.56056313e-02 -1.02473563e-02 3.07167381e-01 3.78783375e-01 4.85308826e-01 -9.60467756e-01 5.96735656e-01 1.27053022e-01 2.75213897e-01 6.09954119e-01 7.57392824e-01 -2.92818516e-01 -9.75621343e-01 -6.60547853e-01 8.40014100e-01 -9.29868221e-01 1.26849771e-01 1.62598148e-01 7.66761363e-01 -3.77558887e-01 9.29422677e-01 9.96209309e-02 3.82721126e-01 4.24123883e-01 2.84204967e-02 2.69314766e-01 -3.44144553e-01 5.26119620e-02 2.37247989e-01 -1.14149861e-01 -3.62617165e-01 -3.11283380e-01 -8.48859787e-01 -8.57869804e-01 -5.82341135e-01 -5.77303290e-01 5.16725481e-01 5.62164664e-01 1.06490004e+00 1.08682409e-01 3.11757535e-01 1.13558125e+00 -2.69158632e-01 -1.17519581e+00 -1.00100744e+00 -9.63280618e-01 3.53989512e-01 3.14233154e-01 -9.48236942e-01 -6.22320950e-01 -3.42569232e-01]	[7.903348922729492, 5.171093940734863]
51974065-c261-450e-a78f-f1abfe9d1bcc	predictive-coding-based-multiscale-network	2212.11642	null	https://arxiv.org/abs/2212.11642v2	https://arxiv.org/pdf/2212.11642v2.pdf	Predictive Coding Based Multiscale Network with Encoder-Decoder LSTM for Video Prediction	We are introducing a multi-scale predictive model for video prediction here, whose design is inspired by the "Predictive Coding" theories and "Coarse to Fine" approach. As a predictive coding model, it is updated by a combination of bottom-up and top-down information flows, which is different from traditional bottom-up training style. Its advantage is to reduce the dependence on input information and improve its ability to predict and generate images. Importantly, we achieve with a multi-scale approach -- higher level neurons generate coarser predictions (lower resolution), while the lower level generate finer predictions (higher resolution). This is different from the traditional predictive coding framework in which higher level predict the activity of neurons in lower level. To improve the predictive ability, we integrate an encoder-decoder network in the LSTM architecture and share the final encoded high-level semantic information between different levels. Additionally, since the output of each network level is an RGB image, a smaller LSTM hidden state can be used to retain and update the only necessary hidden information, avoiding being mapped to an overly discrete and complex space. In this way, we can reduce the difficulty of prediction and the computational overhead. Finally, we further explore the training strategies, to address the instability in adversarial training and mismatch between training and testing in long-term prediction. Code is available at https://github.com/Ling-CF/MSPN.	['Weihua Li', 'Junpei Zhong', 'Chaofan Ling']	2022-12-22	null	null	null	null	['video-prediction']	['computer-vision']	[ 2.41229877e-01 3.40584606e-01 -2.65353858e-01 -5.88281304e-02 -3.66528064e-01 -1.85603276e-01 4.94748354e-01 -3.79038960e-01 6.26321882e-02 7.96705246e-01 4.29691881e-01 -9.39050317e-02 2.84582913e-01 -1.21313024e+00 -1.03109252e+00 -6.40313327e-01 2.48670280e-01 -6.28827959e-02 5.30126870e-01 -1.83894038e-01 1.16252467e-01 2.25631818e-01 -1.59842694e+00 9.22013402e-01 7.88142025e-01 1.31527936e+00 4.93000329e-01 5.31228960e-01 1.53972360e-04 1.30155909e+00 -2.93178439e-01 -4.77194011e-01 8.17027539e-02 -5.42011738e-01 -8.03916276e-01 -3.09439689e-01 -5.39887473e-02 -3.97722960e-01 -6.61845803e-01 1.00237644e+00 2.82211155e-01 -1.69953406e-02 1.95077896e-01 -1.11503828e+00 -1.03079891e+00 5.02481163e-01 -1.41692042e-01 5.56993634e-02 3.95439416e-01 6.63218647e-02 5.95567882e-01 -7.62710333e-01 5.41976035e-01 1.10125315e+00 8.12122345e-01 8.44296098e-01 -1.07643497e+00 -8.11501861e-01 4.17708784e-01 4.04699028e-01 -1.22582173e+00 -3.36044669e-01 7.52376378e-01 -4.97956693e-01 8.46224427e-01 2.36178085e-01 1.04639912e+00 1.42027795e+00 5.35416365e-01 6.21870220e-01 9.29838598e-01 -1.77211896e-01 1.62364334e-01 1.31858781e-01 -4.30133432e-01 7.91007340e-01 -2.70062834e-01 4.63362902e-01 -7.10428476e-01 2.14558437e-01 1.13722682e+00 4.56185281e-01 -4.54692036e-01 -2.03365117e-01 -1.02221894e+00 7.36138046e-01 8.42808485e-01 4.35661554e-01 -3.48507881e-01 3.51021469e-01 2.83995807e-01 2.59888679e-01 4.19784606e-01 2.51510471e-01 -4.71132278e-01 -2.08361790e-01 -1.15508628e+00 -2.38595769e-01 5.69541097e-01 8.96926999e-01 8.75997663e-01 4.84166205e-01 -4.21250165e-01 6.03941441e-01 2.39878893e-01 7.14351013e-02 9.84866440e-01 -1.09531879e+00 4.62568730e-01 5.11434793e-01 -1.11003652e-01 -9.78505850e-01 -8.32654685e-02 -5.33512115e-01 -1.18266523e+00 4.03409332e-01 -1.75879478e-01 -3.78967486e-02 -1.06070173e+00 1.77547443e+00 -1.94016427e-01 6.53568804e-01 1.25693649e-01 7.53132761e-01 6.49813235e-01 1.11311901e+00 2.40399167e-01 -1.39820278e-01 9.89504576e-01 -1.28817356e+00 -5.42126238e-01 -3.64436686e-01 4.60125208e-01 -3.47088456e-01 1.03878915e+00 1.83911085e-01 -1.09644961e+00 -1.01215458e+00 -1.08540297e+00 -1.40331239e-01 -5.06811857e-01 7.63523653e-02 5.14542758e-01 1.43019676e-01 -1.42577279e+00 9.80984211e-01 -7.46304691e-01 -1.68379899e-02 4.67663795e-01 3.08045000e-01 -3.68319154e-01 1.29784867e-01 -1.57467782e+00 9.58559453e-01 6.14906430e-01 7.90552869e-02 -8.83664370e-01 -7.36924946e-01 -9.38514113e-01 2.67644882e-01 -1.41171426e-01 -8.40698481e-01 9.93328214e-01 -1.36976838e+00 -1.75627279e+00 2.71659285e-01 -4.08503711e-01 -5.28931320e-01 3.69087785e-01 -2.19666749e-01 -3.78587097e-01 -1.06786624e-01 -4.03158441e-02 9.59332466e-01 8.29376996e-01 -1.30517828e+00 -5.72090089e-01 -8.87066945e-02 6.31216913e-02 3.20384234e-01 -2.36105353e-01 -3.90502989e-01 -6.07307434e-01 -8.37662339e-01 2.35563561e-01 -8.15646708e-01 -2.33037353e-01 -2.96808500e-02 -1.53337359e-01 3.61867458e-01 9.33124840e-01 -7.77916312e-01 1.38152277e+00 -2.39343381e+00 2.80872226e-01 -9.04963613e-02 1.50656134e-01 2.41366446e-01 3.93089326e-03 2.77100563e-01 -1.84460402e-01 3.27970982e-01 -6.25574738e-02 -3.35093439e-01 -2.51229674e-01 3.29829723e-01 -6.68172479e-01 -2.28715673e-01 1.51573732e-01 1.09926069e+00 -7.63352573e-01 -3.79729897e-01 3.16022992e-01 6.92445219e-01 -7.45634854e-01 1.51006639e-01 -1.61067083e-01 6.16459072e-01 -4.07788903e-01 5.47299743e-01 4.93170232e-01 -4.09741491e-01 -2.36427840e-02 -2.75699854e-01 -1.34770513e-01 2.53972292e-01 -8.37683499e-01 1.68397033e+00 -6.08068228e-01 5.91006994e-01 -3.12310278e-01 -9.58593011e-01 8.06390941e-01 5.11422396e-01 1.55288368e-01 -9.48741198e-01 -1.50761276e-01 -5.07241152e-02 -3.50683182e-01 -1.86842605e-01 4.91266072e-01 -3.05776924e-01 -3.77925336e-02 -7.10950345e-02 8.72698352e-02 1.28602728e-01 -3.35779309e-01 -1.24303112e-02 7.83886850e-01 6.81137741e-01 2.16990843e-01 2.49283940e-01 4.79200155e-01 -1.46946684e-01 8.62478852e-01 5.58633864e-01 -2.90916152e-02 6.24058425e-01 5.94235778e-01 -6.31895900e-01 -1.00231707e+00 -8.83873582e-01 3.55284661e-03 1.24893355e+00 2.46128365e-01 -4.56400961e-01 -7.30133772e-01 -3.80388588e-01 -3.20585251e-01 6.82616889e-01 -8.47191632e-01 -4.47545797e-01 -5.77977657e-01 -3.39339435e-01 4.33864474e-01 6.96101665e-01 7.54046023e-01 -1.44001365e+00 -4.51422274e-01 3.30175251e-01 -2.50225395e-01 -9.39622998e-01 -1.83374077e-01 2.40993261e-01 -1.15779781e+00 -6.20157182e-01 -4.68602359e-01 -8.87567163e-01 5.48876286e-01 -1.86461329e-01 9.57415640e-01 7.82945305e-02 3.53479832e-01 -1.36671260e-01 -4.15824741e-01 -9.11714062e-02 -4.88570631e-01 3.76035795e-02 -1.65146500e-01 -5.52717485e-02 -7.79985264e-02 -7.44658768e-01 -6.31112158e-01 7.45010376e-02 -7.55524993e-01 8.97913218e-01 7.02369511e-01 9.91820991e-01 8.54001164e-01 3.15710381e-02 4.68442231e-01 -8.03124666e-01 3.91565681e-01 -4.43871081e-01 -3.45111758e-01 1.73855722e-01 -4.69606847e-01 8.90874118e-02 1.18573570e+00 -3.58584672e-01 -1.04166591e+00 1.11920141e-01 -3.81034285e-01 -7.46950328e-01 9.95745137e-02 3.62049222e-01 -1.09198503e-02 -1.24705255e-01 2.80348867e-01 6.76398039e-01 -9.25856754e-02 -3.20254505e-01 3.31927687e-01 2.24871352e-01 4.19396192e-01 -1.57195285e-01 5.37809014e-01 2.23675117e-01 -1.37268871e-01 -8.92985016e-02 -8.70129585e-01 3.68579596e-01 -7.18769908e-01 -3.19528520e-01 8.60021472e-01 -1.09871042e+00 -5.81544340e-01 4.41679746e-01 -1.13549912e+00 -6.52847409e-01 -5.74298382e-01 1.78660393e-01 -6.68900192e-01 -2.12056898e-02 -1.07472682e+00 -3.16431850e-01 -3.99607301e-01 -1.28017330e+00 7.92788804e-01 3.48309815e-01 -8.21045265e-02 -1.10393000e+00 -1.69427708e-01 5.07804528e-02 6.78406477e-01 2.93585002e-01 7.04817891e-01 -2.30561361e-01 -7.20993042e-01 -1.01344176e-01 -6.61277249e-02 4.27694768e-01 -1.77699864e-01 -1.23248696e-01 -1.00024366e+00 -1.63100675e-01 1.51492953e-01 -1.71398088e-01 1.01618016e+00 2.36015394e-01 1.59286046e+00 -6.49328709e-01 -4.93756533e-01 9.58686769e-01 1.50101507e+00 2.98347592e-01 9.92357135e-01 4.54052538e-01 8.61628294e-01 2.79293239e-01 4.27002698e-01 4.00638878e-01 5.17761886e-01 4.90276426e-01 4.39948261e-01 -1.73079312e-01 -2.90386677e-01 -8.79105270e-01 5.44879377e-01 9.84150112e-01 -1.64014563e-01 4.06979807e-02 -6.61966980e-01 1.61807388e-01 -2.00915384e+00 -1.38118374e+00 2.88102090e-01 1.99449551e+00 9.19391930e-01 1.88473195e-01 -4.07766104e-01 -1.63544714e-02 7.45798707e-01 2.47683406e-01 -5.50539613e-01 -5.44482708e-01 7.12789148e-02 3.24928492e-01 3.70303601e-01 6.28821373e-01 -9.79681611e-01 1.23987937e+00 6.73383284e+00 8.89696658e-01 -1.48593628e+00 3.12969536e-01 9.47762549e-01 -1.05389334e-01 -4.00034815e-01 -5.57594374e-02 -6.60807014e-01 9.82272863e-01 1.07785690e+00 1.17589869e-01 5.17702937e-01 9.72342968e-01 1.31733149e-01 5.22780092e-03 -1.07651162e+00 8.42817664e-01 -1.01233423e-01 -1.76342833e+00 4.29676503e-01 -1.58571705e-01 7.47209132e-01 7.51399994e-02 1.42508283e-01 6.51219964e-01 1.43547133e-01 -1.20472789e+00 9.57234144e-01 9.02050376e-01 9.79726970e-01 -5.82916915e-01 6.66698992e-01 5.29720604e-01 -1.48898959e+00 -4.43561435e-01 -5.62290490e-01 -2.03015774e-01 1.73941880e-01 2.77779102e-01 -1.47009403e-01 3.22504789e-01 9.16885793e-01 8.79570186e-01 -5.00695527e-01 6.83007836e-01 -4.24156666e-01 3.78842831e-01 1.45454884e-01 2.74231702e-01 1.22087292e-01 -1.12006351e-01 8.97307172e-02 1.15961647e+00 6.53157413e-01 2.13722050e-01 1.49136316e-02 8.44445884e-01 -1.66744292e-01 -3.07476968e-01 -6.38043761e-01 4.81624156e-01 6.10495865e-01 9.39831316e-01 -1.76051915e-01 -6.28598213e-01 -3.77701581e-01 1.33393538e+00 5.40388525e-01 4.91549373e-01 -1.19117332e+00 -4.45299298e-02 4.29377168e-01 2.57807672e-01 3.94826561e-01 9.76728648e-02 -4.67801958e-01 -1.18552840e+00 -1.20161558e-02 -6.18657827e-01 1.81391805e-01 -1.13298583e+00 -7.68896580e-01 9.07681584e-01 -3.95950496e-01 -1.53176212e+00 -3.20946962e-01 -4.57144797e-01 -6.41289413e-01 1.03533757e+00 -1.60146904e+00 -1.24322999e+00 -3.94326627e-01 8.38621795e-01 5.33788323e-01 -6.30920976e-02 1.06563127e+00 3.16667616e-01 -5.46842933e-01 5.78915179e-01 4.50798050e-02 7.24995732e-02 2.87845790e-01 -8.53778481e-01 2.41341427e-01 9.31920350e-01 -1.78208098e-01 2.73163736e-01 2.36780524e-01 -6.07650638e-01 -9.90862489e-01 -1.41354835e+00 8.22736621e-01 -2.66627550e-01 5.71345150e-01 -2.40745544e-01 -1.00050282e+00 9.31321025e-01 4.30669188e-02 1.51167408e-01 6.10150218e-01 -2.09070370e-01 -2.49190658e-01 -3.19389045e-01 -1.03939879e+00 5.96253037e-01 9.69373822e-01 -6.56697690e-01 -3.95361990e-01 -5.73847480e-02 9.90061581e-01 -5.25128365e-01 -1.14689052e+00 5.06342053e-01 6.08606517e-01 -1.21911931e+00 9.25303578e-01 -1.42428905e-01 8.92034471e-01 -3.42649311e-01 -1.25769123e-01 -1.27514219e+00 -9.16039824e-01 -3.26353520e-01 -4.97416109e-01 9.84604836e-01 5.14057517e-01 -7.89075732e-01 8.46724808e-01 5.86535931e-01 -3.81180644e-01 -1.26367545e+00 -1.01487553e+00 -3.90056968e-01 3.59089933e-02 -4.07417566e-01 6.00077868e-01 7.14927018e-01 1.00586087e-01 9.89387482e-02 -7.44752109e-01 2.13025257e-01 4.94471379e-02 2.04291373e-01 2.86787599e-01 -8.77412319e-01 -4.32887375e-01 -3.88345450e-01 -4.60342824e-01 -1.25062382e+00 -2.94073857e-02 -8.44972491e-01 -4.09846343e-02 -1.73595881e+00 2.52053618e-01 -4.45135772e-01 -5.24725735e-01 8.51554334e-01 -8.48589316e-02 4.56618309e-01 5.12995124e-01 6.40513718e-01 -4.54229951e-01 7.26457775e-01 1.50356364e+00 8.63738731e-02 -1.26642630e-01 -1.72805175e-01 -7.92684615e-01 7.52680302e-01 9.90797400e-01 -3.80355895e-01 -4.09155339e-01 -5.94356358e-01 4.41347435e-02 3.78914207e-01 4.62324589e-01 -1.42053330e+00 3.35517526e-01 -9.59474370e-02 9.23771083e-01 -3.83290797e-01 6.18376851e-01 -7.52270520e-01 5.25915384e-01 7.39106715e-01 -2.86438823e-01 1.11283949e-02 2.36593097e-01 3.94926608e-01 -5.90139687e-01 -2.07782425e-02 9.03735995e-01 -3.04256260e-01 -1.04593551e+00 5.98151505e-01 -2.96404094e-01 -4.12256956e-01 1.18961179e+00 -6.41982079e-01 -3.36086005e-01 -3.21879625e-01 -1.01313615e+00 -3.49837169e-02 6.49776697e-01 4.93325382e-01 7.77728319e-01 -1.61585689e+00 -2.68540829e-01 4.47880715e-01 -2.38521293e-01 -1.46620059e-02 4.51897144e-01 6.39210880e-01 -6.26449823e-01 3.79453212e-01 -4.45963532e-01 -2.57263541e-01 -7.00346947e-01 6.98215902e-01 5.52207589e-01 -4.21493769e-01 -6.76830411e-01 8.95961165e-01 4.68203485e-01 -2.38516390e-01 7.79178040e-03 -1.80712298e-01 -3.22891116e-01 -1.59910709e-01 4.69440490e-01 1.02425620e-01 -3.83692682e-01 -6.16518199e-01 -9.60102156e-02 5.27047634e-01 2.26876572e-01 7.89398476e-02 1.32508898e+00 -1.64888889e-01 -1.94484577e-01 5.24832666e-01 1.00937355e+00 -2.88994193e-01 -1.67517400e+00 -3.08661954e-03 -4.50837195e-01 -2.90348560e-01 -5.48825413e-02 -7.52668738e-01 -1.22119439e+00 1.02796280e+00 5.01415193e-01 2.76120007e-01 1.39681315e+00 -1.20210230e-01 8.48794997e-01 -2.88051702e-02 3.73362988e-01 -1.06883836e+00 7.55167305e-02 6.34000838e-01 1.01145482e+00 -9.30236697e-01 -2.60467410e-01 -2.30030268e-01 -8.11402857e-01 1.13541996e+00 9.34884012e-01 -1.34011447e-01 5.94875157e-01 3.55359167e-01 -3.21849704e-01 1.60813883e-01 -9.79267120e-01 1.86533675e-01 2.15640962e-01 5.50124466e-01 4.66217518e-01 1.58906028e-01 2.60782480e-01 7.84349442e-01 -4.74016279e-01 2.98060685e-01 2.61896104e-01 6.02278113e-01 -4.47191954e-01 -1.00359261e+00 -1.14924803e-01 4.83814269e-01 -3.90720308e-01 -4.95702505e-01 1.42249987e-01 5.75537026e-01 6.00534678e-01 5.71628690e-01 1.63612649e-01 -8.41762066e-01 1.45025611e-01 1.59393132e-01 1.67138234e-01 -5.12730598e-01 -3.72102827e-01 -2.33173758e-01 -2.06385210e-01 -9.16084647e-01 -2.61515647e-01 -2.28668153e-01 -1.19460928e+00 -5.57693422e-01 1.90732758e-02 -3.79787199e-02 2.43677750e-01 7.60963619e-01 7.28720605e-01 8.48671556e-01 5.91712296e-01 -1.12290132e+00 -8.72536525e-02 -8.15984666e-01 -3.36578280e-01 2.77203113e-01 2.22223446e-01 -4.39772189e-01 -1.03354238e-01 2.73082942e-01]	[11.080900192260742, -1.1839765310287476]
c39055b9-b216-4326-b43c-156c779a72f5	a-fast-evidential-approach-for-stock	2104.05204	null	https://arxiv.org/abs/2104.05204v2	https://arxiv.org/pdf/2104.05204v2.pdf	A Fast Evidential Approach for Stock Forecasting	Within the framework of evidence theory, the confidence functions of different information can be combined into a combined confidence function to solve uncertain problems. The Dempster combination rule is a classic method of fusing different information. This paper proposes a similar confidence function for the time point in the time series. The Dempster combination rule can be used to fuse the growth rate of the last time point, and finally a relatively accurate forecast data can be obtained. Stock price forecasting is a concern of economics. The stock price data is large in volume, and more accurate forecasts are required at the same time. The classic methods of time series, such as ARIMA, cannot balance forecasting efficiency and forecasting accuracy at the same time. In this paper, the fusion method of evidence theory is applied to stock price prediction. Evidence theory deals with the uncertainty of stock price prediction and improves the accuracy of prediction. At the same time, the fusion method of evidence theory has low time complexity and fast prediction processing speed.	['Fuyuan Xiao', 'Tianxiang Zhan']	2021-04-12	null	null	null	null	['stock-price-prediction']	['time-series']	[-7.28053272e-01 -6.75284088e-01 -2.20165119e-01 -3.30740005e-01 -1.66945428e-01 -4.71074313e-01 4.08176720e-01 1.18294068e-01 -1.32717595e-01 9.13554907e-01 -1.39091372e-01 -4.35878575e-01 -4.35187936e-01 -1.22365916e+00 -1.20163605e-01 -7.96444535e-01 5.72320670e-02 2.15769395e-01 3.14816177e-01 -2.78380930e-01 6.16411746e-01 4.40935820e-01 -1.70055294e+00 -4.17853706e-02 1.05401158e+00 1.86247051e+00 2.55274147e-01 5.06904870e-02 -6.36628330e-01 5.99676013e-01 -7.15493381e-01 -1.06502205e-01 4.77130830e-01 -1.29479602e-01 2.38322958e-01 -3.61832619e-01 -5.81461251e-01 -4.64923024e-01 1.05641983e-01 1.23902428e+00 7.21001178e-02 4.92582098e-02 5.65327406e-01 -1.66545463e+00 -5.10572016e-01 8.45315576e-01 -5.88196933e-01 3.03465277e-01 -3.16461623e-02 -2.98613578e-01 5.28858721e-01 -9.68798280e-01 -1.32341236e-01 1.09425759e+00 5.36448717e-01 -2.77110785e-01 -5.19103289e-01 -9.31890428e-01 2.10980713e-01 2.98867047e-01 -1.28978360e+00 1.27269387e-01 6.44796908e-01 -3.47373545e-01 5.15832126e-01 2.48859957e-01 1.03197730e+00 2.78381202e-02 9.48935270e-01 5.41079521e-01 1.39358783e+00 -2.03458712e-01 3.27259928e-01 6.41003102e-02 5.35407150e-03 3.85567881e-02 8.94484460e-01 4.90737945e-01 -2.06708163e-01 -4.08900566e-02 5.50517857e-01 8.03538561e-01 -2.18900889e-01 4.70254421e-01 -9.72114265e-01 8.54631722e-01 1.60111822e-02 6.77953839e-01 -5.27010500e-01 -1.67758614e-01 2.52239197e-01 4.92078096e-01 7.89525032e-01 -5.44509105e-03 -6.17070079e-01 1.33476146e-02 -1.19274497e+00 4.77194548e-01 8.81506681e-01 7.50748575e-01 2.54720986e-01 5.32433212e-01 -3.07246204e-02 -3.45593356e-02 6.34635508e-01 1.07834888e+00 6.26023591e-01 -7.52753615e-01 2.24726960e-01 4.28279161e-01 4.93009567e-01 -1.18545997e+00 -3.59753281e-01 -5.14078140e-01 -8.17924321e-01 6.80741370e-01 2.07293600e-01 -2.08877563e-01 -7.07182229e-01 1.17693114e+00 -7.63417259e-02 5.09369373e-01 4.10154909e-01 5.91338813e-01 4.16691065e-01 1.35519183e+00 -2.63363272e-01 -1.01377559e+00 1.24123192e+00 -3.38193893e-01 -1.26839948e+00 2.17883170e-01 7.18300119e-02 -9.20317352e-01 -9.45743546e-02 7.85504818e-01 -9.17786717e-01 -4.93585825e-01 -1.10610092e+00 6.65429652e-01 -6.27130806e-01 -2.69292176e-01 4.22566563e-01 3.20326805e-01 -6.08839273e-01 7.85317719e-01 -5.13316631e-01 7.35155404e-01 -4.73906785e-01 -3.02760974e-02 1.22191548e-01 5.62214591e-02 -1.64277470e+00 1.42422628e+00 9.33849335e-01 3.66498172e-01 1.82946473e-01 -6.60847723e-01 -6.85380459e-01 2.40877315e-01 2.20587194e-01 -2.48427659e-01 1.15226030e+00 -4.81381595e-01 -1.26362014e+00 -3.40627789e-01 1.71087272e-02 -4.13338661e-01 3.44778925e-01 9.14261192e-02 -1.27464259e+00 -2.58637786e-01 2.96092052e-02 -2.50077516e-01 7.77749062e-01 -7.06880212e-01 -1.24157834e+00 -2.36890167e-01 -5.39386213e-01 1.61551964e-02 3.25359792e-01 -1.03960082e-01 4.51303303e-01 -6.52351856e-01 4.92823303e-01 -5.01037538e-01 -2.16138333e-01 -5.67460656e-01 4.89379257e-01 -4.62827742e-01 8.59164774e-01 -7.78104782e-01 1.47837365e+00 -2.08501363e+00 -3.35314482e-01 6.96464062e-01 -1.32526621e-01 1.48872538e-02 4.45445240e-01 4.07530665e-01 -5.12832664e-02 1.98409095e-01 -1.73545122e-01 4.28227901e-01 1.12440288e-01 3.86031270e-01 -9.02383327e-01 2.65404284e-01 -7.39455149e-02 6.15447164e-01 -8.37674081e-01 -3.68580908e-01 3.40809107e-01 -1.03488041e-03 2.48187229e-01 -9.82048549e-03 -3.02095748e-02 -1.61214337e-01 -4.20542717e-01 7.29674399e-01 8.92063141e-01 3.69225293e-02 -1.64722890e-01 -1.64412454e-01 -8.38938475e-01 -2.28512019e-01 -1.64093828e+00 8.01554024e-01 -2.13797376e-01 2.08468601e-01 -2.55200297e-01 -8.35202754e-01 1.52462995e+00 6.55845344e-01 5.14119506e-01 -6.23364925e-01 2.08209172e-01 8.17798615e-01 1.11781463e-01 -2.54160315e-01 6.40852511e-01 -5.02929568e-01 -1.53807133e-01 4.37790364e-01 -3.71478677e-01 -4.81553704e-01 2.83184618e-01 -3.59347880e-01 3.08127999e-01 -1.72217175e-01 6.77913666e-01 -3.02636176e-01 1.49558067e-01 -1.95930064e-01 1.08059072e+00 1.18511431e-01 7.30233714e-02 3.09207588e-02 1.92652836e-01 -6.66869223e-01 -9.37967598e-01 -8.41956496e-01 -3.12940657e-01 2.95470625e-01 2.52548575e-01 4.99539599e-02 2.67194748e-01 -1.88872680e-01 5.20825922e-01 1.06171167e+00 -3.29308271e-01 5.08082993e-02 2.66541112e-02 -6.88086867e-01 -3.76564115e-02 5.11960149e-01 5.90805531e-01 -6.92125797e-01 -4.67640936e-01 7.26149976e-01 1.45132810e-01 -4.41567034e-01 -5.65879345e-02 -7.29106367e-02 -8.26035678e-01 -8.27136934e-01 -8.45354915e-01 -1.24251276e-01 3.05096507e-01 2.78999180e-01 8.60029042e-01 2.23896921e-01 6.85662508e-01 -9.09523591e-02 -4.77092803e-01 -1.23007619e+00 -7.43393749e-02 -7.82938719e-01 3.62175643e-01 -1.49154142e-01 1.87653944e-01 -4.52867091e-01 -4.16282624e-01 3.06176096e-01 -8.49311888e-01 -3.77140135e-01 4.00249988e-01 7.43000567e-01 6.01673305e-01 1.05395174e+00 1.01739490e+00 1.40432846e-02 9.06318069e-01 -6.39124572e-01 -1.31785333e+00 5.75531304e-01 -1.26562107e+00 -4.27789353e-02 5.34921944e-01 -2.80773938e-01 -1.09077835e+00 -4.28767830e-01 2.16054156e-01 -4.28311914e-01 3.73551190e-01 1.33893740e+00 2.08868414e-01 9.73946825e-02 -1.07113846e-01 3.99191231e-01 2.47151360e-01 -3.46995205e-01 -1.14575006e-01 4.74919915e-01 4.05927718e-01 -2.23117813e-01 5.09841919e-01 5.89881502e-02 5.15324354e-01 -1.12402692e-01 -5.92064202e-01 -2.49650970e-01 -2.93951094e-01 -5.26883483e-01 3.31893086e-01 -7.61986196e-01 -8.13775539e-01 5.79015493e-01 -1.12505138e+00 5.34553587e-01 -1.52517840e-01 1.22850633e+00 -2.78398126e-01 1.16924264e-01 -4.10237223e-01 -1.37235034e+00 -2.84317046e-01 -8.30400348e-01 3.81760806e-01 5.37170768e-01 2.14933112e-01 -1.03686559e+00 4.51166891e-02 -5.13181925e-01 3.18869323e-01 3.27489108e-01 4.87482756e-01 -9.25392985e-01 -4.43528593e-01 -6.65934741e-01 1.47917759e-04 4.17247295e-01 3.76043841e-02 5.50643742e-01 -2.56304175e-01 4.99921739e-02 6.24472201e-01 4.26702142e-01 7.54534006e-01 6.00587010e-01 7.67639697e-01 -3.54158193e-01 -1.02525286e-01 8.59807655e-02 1.38010216e+00 1.00599802e+00 7.31828094e-01 4.36510026e-01 -1.08646266e-01 6.16679847e-01 1.18462360e+00 7.37289429e-01 3.31069648e-01 7.55073056e-02 9.55161676e-02 5.89099944e-01 8.95947278e-01 -2.79530752e-02 1.21720321e-01 1.37999582e+00 -5.32280326e-01 -1.94734484e-01 -7.65599549e-01 1.47179767e-01 -2.15604591e+00 -1.62682033e+00 -1.33492559e-01 2.18344665e+00 5.80411375e-01 3.05655330e-01 -1.37399986e-01 5.27292311e-01 7.58869708e-01 -1.09004267e-02 -3.76857728e-01 -2.65230298e-01 -1.57297358e-01 -3.68888885e-01 7.42244005e-01 3.95762444e-01 -6.12988114e-01 -1.54492222e-02 6.64978504e+00 1.04199851e+00 -1.22902226e+00 -2.64403075e-01 3.52588296e-01 3.68568689e-01 -6.32009745e-01 1.39640927e-01 -1.03991365e+00 1.26575875e+00 9.05436993e-01 -9.97518122e-01 8.10606107e-02 9.28939581e-01 1.82040304e-01 -3.85485053e-01 -4.50791121e-01 9.85915899e-01 -2.83464909e-01 -1.38703668e+00 -2.39969283e-01 1.42859295e-01 7.40428090e-01 -3.62262666e-01 5.13314083e-02 2.44003713e-01 3.54874074e-01 -7.27720082e-01 8.68820548e-01 1.40139723e+00 2.51170754e-01 -1.22649825e+00 1.43874013e+00 6.96026742e-01 -1.58154845e+00 -2.39610881e-01 -5.59419751e-01 -5.41738689e-01 8.47337127e-01 1.20872641e+00 -2.26095110e-01 1.04061472e+00 5.22343159e-01 7.08060861e-01 1.85919449e-01 1.17546034e+00 -1.73841923e-01 1.36755601e-01 -6.07057571e-01 -2.00141564e-01 1.35501459e-01 -7.94178307e-01 2.57136256e-01 4.50102806e-01 1.32674170e+00 7.04871833e-01 2.78725445e-01 5.28539538e-01 5.84171534e-01 -1.14920940e-02 -5.46168864e-01 -5.20922616e-02 9.62733507e-01 6.96728051e-01 -7.28361666e-01 -7.35964298e-01 -5.39139390e-01 -6.50077239e-02 -4.88916993e-01 5.40796779e-02 -4.98377442e-01 -4.12353665e-01 1.24774463e-01 -2.80159712e-01 2.47457147e-01 -3.04499090e-01 -5.35559833e-01 -1.04422164e+00 3.79413692e-03 -3.15347284e-01 4.43817794e-01 -8.77510667e-01 -1.61668277e+00 3.22229981e-01 4.76416349e-01 -1.76399112e+00 -6.29516840e-01 -5.81829607e-01 -9.44315910e-01 1.33637667e+00 -1.41239333e+00 -4.27478045e-01 2.02958554e-01 4.10869658e-01 2.18576312e-01 -4.88194495e-01 6.45582676e-01 -7.53867924e-02 -3.60336572e-01 -2.39467025e-01 6.67956710e-01 -2.28724107e-01 2.77502447e-01 -1.06533229e+00 1.57008674e-02 9.49510813e-01 -3.63751441e-01 3.88167441e-01 8.78518164e-01 -1.27113223e+00 -8.79660130e-01 -5.64950585e-01 9.14317369e-01 1.76591828e-01 8.95239353e-01 6.57932758e-01 -1.22003663e+00 2.45804414e-01 9.01475847e-02 4.26066406e-02 5.10290742e-01 -9.50421095e-02 -2.42113531e-01 -4.45160747e-01 -1.31661892e+00 2.58998036e-01 -1.02818511e-01 -8.37373212e-02 -1.17902172e+00 -9.08113420e-02 7.39344180e-01 -2.41561934e-01 -1.34888411e+00 7.18408167e-01 8.96561801e-01 -9.25509334e-01 5.53990185e-01 -6.67126551e-02 3.15334722e-02 -6.65434897e-01 -2.48191774e-01 -1.65000713e+00 -5.23135066e-01 -1.05862476e-01 -1.51191577e-01 1.04533887e+00 4.23603535e-01 -1.32800078e+00 -1.70752138e-01 9.10730243e-01 -1.07479319e-01 -5.78469872e-01 -1.10016870e+00 -1.25489092e+00 -1.95640013e-01 -3.65964919e-01 1.40170336e+00 9.13536251e-01 2.53741622e-01 -3.13476950e-01 -4.67540413e-01 1.29904225e-01 7.56068230e-01 6.04827285e-01 1.51498675e-01 -1.87781155e+00 2.06283927e-01 -6.91379428e-01 -2.43518576e-01 -4.22668695e-01 8.41554441e-03 -3.14495653e-01 -3.30691375e-02 -1.63880312e+00 -4.04441208e-01 -3.30399394e-01 -7.17280686e-01 1.43731683e-01 -4.38631922e-02 -3.80567133e-01 4.61193442e-01 6.41637266e-01 1.40335068e-01 5.60810924e-01 1.20343649e+00 1.39362225e-02 -1.44918874e-01 3.74904960e-01 -3.31646532e-01 8.82287502e-01 1.06273568e+00 -2.05837429e-01 -3.39244813e-01 1.49492756e-01 6.44031763e-01 5.90586305e-01 -8.19963589e-02 -7.39236355e-01 4.51196522e-01 -7.30653703e-01 6.00498497e-01 -1.34460592e+00 1.57581955e-01 -1.27257621e+00 8.51154745e-01 7.64593005e-01 2.73705900e-01 6.46523178e-01 1.16458617e-01 5.63256204e-01 -6.60251796e-01 -5.86869955e-01 3.39807242e-01 -1.53375849e-01 -9.35872138e-01 3.36741567e-01 -3.72931629e-01 -6.68005228e-01 1.21248114e+00 -2.51959264e-01 -3.90179098e-01 -4.22914118e-01 -3.83807123e-01 5.46332717e-01 -3.78431492e-02 2.93069780e-01 7.20256388e-01 -1.72157359e+00 -8.17372382e-01 9.93364863e-03 -4.26422566e-01 -2.23593518e-01 2.65490800e-01 8.24867308e-01 -4.40440416e-01 5.47016561e-01 -4.92255062e-01 -2.30098441e-01 -6.05007887e-01 7.83788323e-01 5.28980419e-02 -2.14847699e-01 -1.80352479e-01 2.16182455e-01 -3.00699711e-01 3.90244216e-01 -3.25531304e-01 -5.35920501e-01 -5.06707847e-01 6.42210603e-01 1.14981580e+00 6.78201795e-01 -2.65743434e-02 -4.04980212e-01 -2.83264190e-01 6.30400479e-01 2.58276373e-01 -4.09633785e-01 1.28162920e+00 -2.47881562e-01 -4.22892660e-01 1.00441718e+00 6.08420670e-01 1.45801187e-01 -8.71830225e-01 -6.01369105e-02 1.26256734e-01 -5.97248197e-01 1.44902840e-01 -7.14284837e-01 -8.99970055e-01 3.67663354e-01 2.56111979e-01 9.78726864e-01 1.10559714e+00 -5.57200611e-01 7.03350961e-01 7.20095411e-02 7.02896953e-01 -1.20701396e+00 -8.25827420e-01 5.35444379e-01 1.09326136e+00 -1.24068582e+00 3.18509281e-01 -1.39279336e-01 -5.33881009e-01 1.38523364e+00 5.76290116e-02 -2.65476316e-01 1.22037005e+00 5.59349537e-01 -1.59493014e-01 2.29790449e-01 -9.08855557e-01 -9.43190604e-02 4.90992188e-01 1.32744074e-01 2.45123282e-01 4.48411673e-01 -1.03895342e+00 1.18227649e+00 -3.27132881e-01 2.80445337e-01 4.18666750e-01 8.85989308e-01 -8.61021399e-01 -8.43642354e-01 -8.04533660e-01 6.65270865e-01 -4.35051084e-01 6.44690916e-02 4.37560886e-01 5.33614337e-01 1.18411139e-01 1.11119843e+00 4.54583943e-01 -5.07842004e-01 2.94164538e-01 1.58638716e-01 1.31047992e-02 -6.08291775e-02 -3.49557698e-02 2.47894913e-01 -2.93064415e-01 -1.68776512e-01 -5.42856574e-01 -7.28286743e-01 -1.29063439e+00 -8.27172220e-01 -5.88847280e-01 7.13575304e-01 7.62729943e-01 1.16696441e+00 7.23395422e-02 2.86791533e-01 9.37398791e-01 -6.62714005e-01 -8.63677979e-01 -7.97933459e-01 -1.31700218e+00 -2.70433128e-01 1.38176978e-01 -9.35385287e-01 -6.49363101e-01 -3.51260722e-01]	[4.741006374359131, 4.103579521179199]
a2c29424-08a1-4779-b414-6ba36769662d	seeing-by-haptic-glance-reinforcement	2102.07599	null	https://arxiv.org/abs/2102.07599v1	https://arxiv.org/pdf/2102.07599v1.pdf	Seeing by haptic glance: reinforcement learning-based 3D object Recognition	Human is able to conduct 3D recognition by a limited number of haptic contacts between the target object and his/her fingers without seeing the object. This capability is defined as `haptic glance' in cognitive neuroscience. Most of the existing 3D recognition models were developed based on dense 3D data. Nonetheless, in many real-life use cases, where robots are used to collect 3D data by haptic exploration, only a limited number of 3D points could be collected. In this study, we thus focus on solving the intractable problem of how to obtain cognitively representative 3D key-points of a target object with limited interactions between the robot and the object. A novel reinforcement learning based framework is proposed, where the haptic exploration procedure (the agent iteratively predicts the next position for the robot to explore) is optimized simultaneously with the objective 3D recognition with actively collected 3D points. As the model is rewarded only when the 3D object is accurately recognized, it is driven to find the sparse yet efficient haptic-perceptual 3D representation of the object. Experimental results show that our proposed model outperforms the state of the art models.	['Patrick Le Callet', 'Guillaume Gallot', 'Suiyi Ling', 'Kevin Riou']	2021-02-15	null	null	null	null	['3d-object-recognition']	['computer-vision']	[ 1.20023496e-01 2.00394347e-01 -9.84294116e-02 -4.04308038e-03 -3.41216445e-01 -1.51805490e-01 1.27488360e-01 3.23901236e-01 -5.42448521e-01 3.16964239e-01 -2.39541337e-01 1.00031488e-01 -4.01037037e-01 -4.55010504e-01 -7.51918852e-01 -5.94514787e-01 -3.78300309e-01 9.18040276e-01 -4.27680835e-02 -6.32872581e-02 6.73567951e-01 7.47867167e-01 -1.84899247e+00 -5.46995290e-02 9.23225522e-01 1.44518292e+00 1.17615843e+00 2.53765285e-01 1.15966842e-01 1.32271126e-01 -1.34857282e-01 4.33525771e-01 5.78783512e-01 -2.61709802e-02 -6.09901726e-01 3.38787228e-01 -2.00045452e-01 -3.79833460e-01 4.14071567e-02 1.06170070e+00 6.39845014e-01 4.01423752e-01 7.87889898e-01 -1.17424226e+00 -6.49400830e-01 5.57651035e-02 -6.07936144e-01 -2.30700791e-01 8.18358600e-01 -5.79027110e-04 7.44878113e-01 -1.18753493e+00 9.06600893e-01 1.35099268e+00 8.31948519e-02 6.87216163e-01 -1.08796954e+00 -3.02950233e-01 2.06651315e-01 3.31148177e-01 -1.25312793e+00 -5.89458793e-02 1.00773239e+00 -5.15402436e-01 8.21158886e-01 2.20165774e-01 1.25354135e+00 1.06505942e+00 2.86020726e-01 1.02294981e+00 1.19369686e+00 -5.27024925e-01 7.39187121e-01 2.29846805e-01 -3.09055835e-01 5.39116323e-01 1.24121327e-02 4.52807665e-01 -9.77759361e-01 -1.90334797e-01 1.15738094e+00 1.13847889e-01 -9.83271375e-02 -1.29520690e+00 -1.33791173e+00 5.89848161e-01 7.13798940e-01 2.49400690e-01 -1.00793505e+00 -1.07122593e-01 -1.32133886e-01 2.06407085e-01 1.34460032e-01 6.60012782e-01 -2.68396258e-01 -3.59626740e-01 -2.46003568e-01 5.37175238e-01 6.81859553e-01 1.17152917e+00 6.70890331e-01 -3.53800565e-01 4.01369631e-02 5.78184724e-01 6.01154685e-01 5.32944620e-01 3.22268248e-01 -1.07101715e+00 3.60041082e-01 8.86673152e-01 6.54168904e-01 -9.70795870e-01 -5.14880300e-01 -3.01649541e-01 -6.13889098e-01 8.15568209e-01 1.58301339e-01 3.23516205e-02 -8.26763570e-01 1.36220157e+00 7.69193292e-01 -2.76277512e-01 -6.35598376e-02 1.59334433e+00 4.52054054e-01 1.85712650e-01 -1.50809422e-01 -8.19292590e-02 1.02147090e+00 -5.53451478e-01 -4.89878356e-01 -4.34659719e-01 4.13681567e-01 -4.22139496e-01 1.10395980e+00 3.80222559e-01 -1.07171583e+00 -7.00743139e-01 -8.62310827e-01 1.42461941e-01 -4.20237899e-01 1.75461844e-01 7.57925212e-01 1.75957024e-01 -7.87768900e-01 6.20900154e-01 -8.07588875e-01 -4.50223684e-01 5.18396139e-01 4.30502832e-01 -5.51962376e-01 -1.39949083e-01 -7.50061393e-01 1.24344015e+00 5.13707459e-01 5.13184309e-01 -8.96540761e-01 -2.89588839e-01 -6.57885432e-01 -2.22274780e-01 4.94854569e-01 -6.92907453e-01 1.05409980e+00 -3.89155537e-01 -1.33775961e+00 1.12227631e+00 8.33584964e-02 -1.21846363e-01 6.46129429e-01 -5.51662743e-01 2.54573613e-01 2.33566329e-01 1.00306645e-01 1.10766721e+00 8.98555458e-01 -1.77352309e+00 -5.11954367e-01 -8.32937658e-01 1.26614019e-01 8.32224846e-01 6.25716522e-04 -7.19937921e-01 -2.68964112e-01 -3.33493769e-01 8.30281794e-01 -1.07492995e+00 -3.30743760e-01 6.52100682e-01 -3.86689037e-01 -4.09325808e-01 6.51736736e-01 -1.57595739e-01 1.05894171e-01 -2.25676775e+00 5.44526339e-01 4.40467268e-01 2.19551325e-01 -1.03271388e-01 -1.27744332e-01 5.55723488e-01 3.12936634e-01 -2.08382681e-01 1.13188982e-01 -2.93642730e-01 1.75378889e-01 5.79276010e-02 -9.69305113e-02 5.50332606e-01 -3.36233526e-02 8.96138728e-01 -1.05196166e+00 -3.03245217e-01 3.63075554e-01 4.84203994e-01 -6.06258750e-01 5.17716527e-01 -1.18883289e-01 8.15770328e-01 -1.11285651e+00 8.70075881e-01 6.39740705e-01 -1.98055968e-01 -1.58127457e-01 -9.43857655e-02 1.69628654e-02 -9.29267481e-02 -1.29675210e+00 2.28920484e+00 -2.06210479e-01 -9.60764382e-03 2.71813035e-01 -8.91738534e-01 1.17516041e+00 1.35048062e-01 6.36249840e-01 -7.57548511e-01 2.57006615e-01 5.33456326e-01 -1.35831982e-01 -7.03209758e-01 2.04507560e-01 8.74527637e-03 -1.02151588e-01 3.86760503e-01 -3.29190254e-01 -4.52561945e-01 -4.85828370e-01 -2.84554332e-01 7.69074798e-01 4.93957818e-01 2.60816008e-01 -6.35782257e-02 -9.40390453e-02 1.17124721e-01 1.10418543e-01 9.94225502e-01 -2.40126535e-01 2.56671607e-01 -1.52387261e-01 -1.35748968e-01 -8.48268747e-01 -1.38944662e+00 7.56060034e-02 6.96657956e-01 8.53434086e-01 2.95403212e-01 -3.65257829e-01 -1.94778204e-01 3.41138095e-01 5.29792547e-01 -9.42611635e-01 -2.09223583e-01 -2.18784049e-01 1.41324967e-01 -3.60633254e-01 2.49844685e-01 4.41167533e-01 -1.61965072e+00 -1.71505964e+00 1.22857071e-01 2.87337955e-02 -6.11487746e-01 -1.23522662e-01 3.99507016e-01 -1.12897217e+00 -9.56897557e-01 -8.26023221e-01 -1.10521591e+00 1.01731908e+00 3.81898373e-01 4.53050882e-01 -6.41904026e-02 -4.06179696e-01 5.96913576e-01 -6.62487805e-01 -4.09121722e-01 1.08837180e-01 -2.28381246e-01 3.47578079e-01 -2.16981456e-01 3.42946887e-01 -7.24579394e-01 -7.27522910e-01 2.66000986e-01 -4.26091760e-01 2.71950334e-01 1.08601296e+00 8.01238239e-01 8.71543646e-01 -8.75508264e-02 6.81599140e-01 -2.38160044e-01 8.12253594e-01 -1.91053793e-01 -1.95433855e-01 -8.06719065e-02 -1.89193696e-01 -9.23628658e-02 2.70366017e-02 -9.01082695e-01 -6.72818065e-01 5.09850025e-01 1.54346079e-01 -7.65829682e-01 -3.82052273e-01 6.15089595e-01 -8.61617737e-03 -2.50231832e-01 5.99989712e-01 3.12847048e-01 3.64171237e-01 -7.15445995e-01 1.09129846e-01 6.55770957e-01 1.77944466e-01 -4.76133108e-01 7.24781513e-01 3.47205341e-01 1.55049726e-01 -5.60590506e-01 -4.16794300e-01 -4.50054854e-01 -9.89995301e-01 -6.04096234e-01 5.88336110e-01 -6.09054983e-01 -1.52335072e+00 1.79746330e-01 -9.92922723e-01 -2.23530889e-01 -5.47857463e-01 9.38712656e-01 -1.18404055e+00 7.78965354e-02 -6.10578544e-02 -1.40970933e+00 -3.45862135e-02 -1.21086073e+00 1.37082267e+00 1.37638643e-01 -3.94223899e-01 -2.57839829e-01 -3.17988634e-01 1.56366467e-01 1.52355850e-01 2.80449420e-01 1.01169705e+00 -4.35403377e-01 -6.93262398e-01 -3.83148372e-01 -4.62046117e-02 -4.39657718e-01 2.95701325e-01 -1.03325248e+00 -7.00003386e-01 -3.67059737e-01 2.12168679e-01 -8.10409606e-01 2.40097225e-01 2.76237130e-01 1.07840955e+00 -7.54605234e-02 -6.31059647e-01 -1.10925019e-01 1.05129337e+00 4.91182894e-01 2.96351135e-01 1.77159339e-01 4.21965867e-01 1.01542532e+00 1.25193310e+00 6.42178953e-01 1.18901126e-01 6.74663544e-01 9.37605917e-01 2.13629737e-01 4.72738564e-01 -3.64824921e-01 -7.97243416e-02 5.95361829e-01 -2.29639918e-01 1.86494321e-01 -6.59167051e-01 2.89803237e-01 -1.89965236e+00 -5.12017369e-01 6.03542030e-01 2.22763538e+00 6.58054292e-01 3.63151789e-01 -1.51388511e-01 2.06437632e-01 5.27373910e-01 -3.32486540e-01 -1.25390840e+00 6.97675953e-03 3.08066666e-01 -1.46011978e-01 -9.46287289e-02 3.37088704e-01 -6.25442445e-01 8.02836597e-01 5.16109848e+00 5.25202096e-01 -8.92309248e-01 -4.80290323e-01 1.28030241e-01 -3.46622646e-01 -4.65531424e-02 -2.44145542e-01 -4.47596997e-01 -8.81736204e-02 1.12346813e-01 6.58404082e-02 5.62842727e-01 9.31419551e-01 4.32378858e-01 -6.59726560e-01 -1.57266235e+00 1.33973181e+00 -2.07103819e-01 -8.75476956e-01 1.52586326e-01 1.88321561e-01 1.85716167e-01 -4.53403443e-01 2.54773766e-01 6.61434308e-02 -2.12198451e-01 -9.54220176e-01 9.86039937e-01 9.72103715e-01 6.13864422e-01 -5.67721725e-01 2.11984053e-01 1.03109694e+00 -9.29627180e-01 -2.87730724e-01 -3.56767148e-01 -1.52732670e-01 1.95032388e-01 3.54564309e-01 -1.02903020e+00 1.57297090e-01 8.66770625e-01 5.23867249e-01 -2.13181213e-01 1.38473606e+00 1.88854456e-01 -4.39385831e-01 -3.82445395e-01 -7.89930403e-01 2.25031361e-01 -1.20017447e-01 8.33578050e-01 2.56024331e-01 5.75821936e-01 3.48441005e-01 4.44844335e-01 1.08111036e+00 3.61124426e-01 1.25273153e-01 -7.86145985e-01 1.48709603e-02 5.57985604e-01 8.59618187e-01 -8.22784841e-01 1.63671508e-01 2.23730758e-01 1.16049874e+00 5.15327930e-01 3.85341942e-01 -1.18294179e-01 -3.14507931e-01 3.87615740e-01 7.96043798e-02 3.23995858e-01 -6.00887060e-01 -2.48513550e-01 -5.20365894e-01 3.72171760e-01 -5.00009775e-01 -1.65664271e-01 -1.29287088e+00 -1.21624422e+00 3.71404350e-01 -2.40885958e-01 -1.54423368e+00 -2.80775070e-01 -6.96784019e-01 1.17774174e-01 1.06017888e+00 -1.18668306e+00 -7.66606450e-01 -2.51671106e-01 5.17311335e-01 4.56314296e-01 1.58348437e-02 1.12212586e+00 -3.58706146e-01 4.37776029e-01 -5.93799017e-02 -1.57137975e-01 -4.05725658e-01 3.16256404e-01 -1.02924061e+00 -2.15639472e-02 -2.94357210e-01 -1.27494469e-01 5.27375162e-01 7.26955056e-01 -1.08707678e+00 -2.08827329e+00 -3.80220711e-01 5.44030845e-01 -2.36226514e-01 1.74577668e-01 -7.02536583e-01 -7.86465824e-01 1.05810888e-01 -4.59172308e-01 -1.25788212e-01 3.66655380e-01 1.13349147e-02 3.51112813e-01 2.24866912e-01 -1.36847591e+00 7.93765068e-01 1.43879485e+00 -3.92275035e-01 -7.47409582e-01 3.94672513e-01 4.69292998e-01 -6.91396773e-01 -9.31641936e-01 4.04920697e-01 8.44560981e-01 -5.80619216e-01 9.60999310e-01 -4.43363160e-01 6.72499388e-02 -1.87976420e-01 -2.55613655e-01 -1.43370903e+00 -2.47318015e-01 -3.62388790e-01 -4.01877195e-01 2.91527301e-01 1.49785072e-01 -3.34175438e-01 1.12054694e+00 5.36457717e-01 5.01873083e-02 -9.76870179e-01 -1.41686964e+00 -5.29324770e-01 -4.14526254e-01 -3.36435109e-01 1.85432658e-01 4.60121602e-01 4.46446270e-01 6.87581114e-03 -1.10282496e-01 3.44031215e-01 7.52019227e-01 6.50594532e-01 4.25962478e-01 -1.70880818e+00 -4.42282967e-02 -2.45881453e-01 -4.28870320e-01 -1.58431733e+00 1.95659064e-02 -8.44938695e-01 4.77681726e-01 -1.60878277e+00 2.25222800e-02 -8.12001765e-01 -4.48252149e-02 2.65939832e-01 2.93262333e-01 -1.77670375e-01 1.78719148e-01 4.38252985e-01 -4.99420971e-01 1.06772268e+00 2.15898657e+00 -6.96172342e-02 -6.40789330e-01 2.87745684e-01 -4.65058506e-01 4.57339227e-01 6.48476005e-01 -2.03729942e-02 -4.91592079e-01 -2.79835165e-01 1.47063911e-01 5.28013647e-01 7.99818754e-01 -9.49007273e-01 4.33314413e-01 -3.01195234e-01 8.23265672e-01 -1.03728044e+00 1.05369687e+00 -1.28501928e+00 2.92813499e-02 6.07364416e-01 -4.49116230e-01 -1.99726656e-01 1.79758742e-02 9.70064640e-01 3.12845230e-01 -1.96005046e-01 3.86104733e-01 -3.85458291e-01 -8.58121336e-01 4.01295155e-01 -5.62140524e-01 -3.94140333e-01 1.14253867e+00 -6.68207407e-01 3.18000406e-01 -2.69597471e-01 -1.39393914e+00 2.51769006e-01 3.93735290e-01 5.91059148e-01 1.38091683e+00 -1.52932024e+00 -2.58377910e-01 3.63571554e-01 1.19429328e-01 2.29387581e-01 3.47360522e-01 5.11736095e-01 1.32432342e-01 4.69045252e-01 -5.38945913e-01 -7.82738805e-01 -9.23799336e-01 6.98592186e-01 1.20198697e-01 4.09223706e-01 -8.85866761e-01 5.84719002e-01 3.16230841e-02 -5.89248180e-01 6.96583986e-01 -3.31818789e-01 -3.61606121e-01 -1.41951472e-01 1.21692710e-01 2.04308122e-01 -1.86815560e-01 -4.67285603e-01 -3.14030737e-01 6.46541655e-01 3.67535166e-02 -1.92581072e-01 1.51017666e+00 -3.07010710e-01 2.67017424e-01 8.81969154e-01 1.00707281e+00 -5.71201921e-01 -1.62501264e+00 -3.25866044e-01 -2.46218100e-01 -7.47541428e-01 -6.27088323e-02 -8.84100437e-01 -5.90659320e-01 7.29388118e-01 1.05737507e+00 1.00559399e-01 8.98299575e-01 3.54921579e-01 3.49461824e-01 9.88520980e-01 1.00908446e+00 -1.24113202e+00 5.34142256e-01 2.90062785e-01 1.49055099e+00 -1.31943691e+00 -1.71888739e-01 -4.79440957e-01 -5.47158480e-01 6.82917297e-01 7.74778187e-01 -1.79940775e-01 8.82581353e-01 -2.33767584e-01 -1.84541896e-01 -5.32559097e-01 -4.14750278e-01 -9.23459083e-02 3.95210177e-01 1.03352094e+00 -3.07278454e-01 1.07532755e-01 2.15758115e-01 4.01391298e-01 -3.69872123e-01 -7.13723376e-02 5.38389534e-02 1.43068910e+00 -9.54140067e-01 -6.85171843e-01 -2.92627722e-01 5.87923408e-01 3.24173868e-01 2.84402609e-01 -3.06183189e-01 5.91992497e-01 -1.04329407e-01 6.85020208e-01 5.95583096e-02 -2.64545083e-01 5.72009027e-01 -1.60008803e-01 8.76555324e-01 -7.14682639e-01 -4.58865538e-02 1.14370629e-01 -3.55336100e-01 -9.12330568e-01 -5.55074096e-01 -8.02291274e-01 -1.45461285e+00 1.86983615e-01 -1.93209291e-01 1.05999395e-01 1.00752831e+00 7.80824780e-01 4.72123206e-01 1.81002378e-01 5.59933364e-01 -1.80137455e+00 -5.96020162e-01 -8.46694708e-01 -1.16647995e+00 2.41725162e-01 4.28458840e-01 -1.42205858e+00 -1.74907371e-01 -2.71079719e-01]	[5.8506951332092285, -0.8655223250389099]
9259acf0-9fcb-42b9-9262-5fc9ac7f8503	detflowtrack-3d-multi-object-tracking-based	2203.02157	null	https://arxiv.org/abs/2203.02157v1	https://arxiv.org/pdf/2203.02157v1.pdf	DetFlowTrack: 3D Multi-object Tracking based on Simultaneous Optimization of Object Detection and Scene Flow Estimation	3D Multi-Object Tracking (MOT) is an important part of the unmanned vehicle perception module. Most methods optimize object detection and data association independently. These methods make the network structure complicated and limit the improvement of MOT accuracy. we proposed a 3D MOT framework based on simultaneous optimization of object detection and scene flow estimation. In the framework, a detection-guidance scene flow module is proposed to relieve the problem of incorrect inter-frame assocation. For more accurate scene flow label especially in the case of motion with rotation, a box-transformation-based scene flow ground truth calculation method is proposed. Experimental results on the KITTI MOT dataset show competitive results over the state-of-the-arts and the robustness under extreme motion with rotation.	['Hesheng Wang', 'Guangming Wang', 'Yueling Shen']	2022-03-04	null	null	null	null	['scene-flow-estimation', '3d-multi-object-tracking']	['computer-vision', 'computer-vision']	[-6.75330535e-02 -4.16058153e-01 2.13115606e-02 -5.86870611e-02 6.65412843e-02 -3.59168410e-01 5.24395525e-01 -2.04342008e-01 -6.38703763e-01 4.55722243e-01 -3.41848701e-01 -2.72128165e-01 -3.90640646e-02 -8.11765254e-01 -5.34113526e-01 -6.90648139e-01 4.64280620e-02 5.10935545e-01 9.33770597e-01 -1.45943388e-01 2.81058967e-01 5.98466754e-01 -1.55741394e+00 -7.23095089e-02 6.82056010e-01 9.28263724e-01 4.97675687e-01 7.91439354e-01 -1.82744682e-01 8.76993835e-01 -3.91511351e-01 9.62549374e-02 6.98018491e-01 -1.40315235e-01 -2.05865279e-01 3.84099334e-01 7.36460149e-01 -4.71416146e-01 -6.93962038e-01 1.02722383e+00 3.70901763e-01 3.60356957e-01 3.85024667e-01 -1.52105534e+00 1.83025658e-01 -5.01687899e-02 -7.55829155e-01 5.42769134e-01 2.72221297e-01 3.88551384e-01 5.20486295e-01 -7.80132234e-01 6.29063249e-01 1.38377392e+00 3.86356741e-01 3.81569207e-01 -9.03055251e-01 -6.56392634e-01 2.26055190e-01 5.88950932e-01 -1.46417141e+00 -4.55333889e-01 8.60177815e-01 -4.53866959e-01 6.65277302e-01 2.36190945e-01 9.22861516e-01 4.08106923e-01 3.16477150e-01 5.94343126e-01 7.95666397e-01 -7.42332116e-02 1.00528158e-01 7.53031000e-02 -3.53756063e-02 9.47490394e-01 7.76396334e-01 3.99566442e-01 -5.17627239e-01 2.80474454e-01 9.59489584e-01 1.18696027e-01 -4.06208336e-02 -8.16524029e-01 -1.23438501e+00 5.72703123e-01 5.88810563e-01 1.26492247e-01 -1.22115016e-01 2.70734072e-01 1.31532907e-01 2.18831435e-01 3.09990674e-01 -6.81469142e-02 1.16936741e-02 1.25891611e-01 -7.49847591e-01 3.07743430e-01 6.19300663e-01 1.08841276e+00 9.79234695e-01 2.71206677e-01 -4.30774949e-02 1.89160734e-01 5.82176685e-01 7.76658237e-01 4.69251648e-02 -1.16803718e+00 4.50396717e-01 9.57892895e-01 1.32917970e-01 -1.38444841e+00 -5.72389483e-01 -5.01509368e-01 -7.60260761e-01 7.15852797e-01 5.93482196e-01 -7.39144683e-02 -7.64995933e-01 1.15785003e+00 8.91429126e-01 4.92553651e-01 4.68552522e-02 1.15850103e+00 8.00627291e-01 5.78318954e-01 -2.90756762e-01 -3.07785839e-01 9.71052766e-01 -8.52987826e-01 -8.68888378e-01 -4.50564206e-01 6.44898117e-01 -6.46053076e-01 3.35094988e-01 2.85062402e-01 -7.42593586e-01 -8.22918653e-01 -1.05696416e+00 -5.97551316e-02 -3.60488892e-01 -6.89148605e-02 4.81655002e-01 6.60082340e-01 -7.43036628e-01 -8.90267175e-03 -9.92160857e-01 -4.93016422e-01 4.27474439e-01 4.21551317e-01 -2.23481998e-01 -2.23785356e-01 -5.78783929e-01 1.12196124e+00 7.49000192e-01 1.73972309e-01 -1.00452518e+00 -6.33368075e-01 -8.38232696e-01 -1.43213958e-01 5.41744769e-01 -9.36408758e-01 7.65307665e-01 -4.68672305e-01 -1.49831271e+00 5.70754111e-01 -1.95051774e-01 -6.63688838e-01 7.28665948e-01 -2.30112165e-01 -1.65593907e-01 1.55009046e-01 -1.74818896e-02 7.67266452e-01 7.14949965e-01 -1.25034821e+00 -1.03874850e+00 -2.49076352e-01 1.11993328e-01 5.19990027e-01 -4.50790254e-03 -2.66444743e-01 -5.78661740e-01 7.35822925e-03 1.78784490e-01 -1.01320088e+00 -4.53831434e-01 3.28802943e-01 -1.34322003e-01 2.29231175e-02 1.66666591e+00 -2.75111914e-01 9.29181159e-01 -2.10929298e+00 4.48378846e-02 -8.53596348e-03 2.77530164e-01 2.05074236e-01 1.40319422e-01 -2.09267363e-01 4.12087828e-01 -6.26190543e-01 2.61136480e-02 -3.74103278e-01 -3.57911915e-01 2.42079511e-01 8.22666883e-02 9.66621459e-01 -9.16416124e-02 6.08884096e-01 -8.85724425e-01 -7.65563130e-01 1.06960404e+00 3.64816368e-01 -8.21310282e-01 1.48359165e-01 -2.09274560e-01 7.32571185e-01 -5.28651416e-01 7.06053793e-01 8.66630197e-01 -1.25316575e-01 -1.93528458e-01 -3.88592899e-01 -6.58296466e-01 -7.04709738e-02 -1.73599541e+00 1.77724683e+00 -1.58178106e-01 8.35577548e-01 3.26949090e-01 -7.07304299e-01 8.56760144e-01 -1.71056874e-02 9.26088035e-01 -3.56796175e-01 4.92101341e-01 -6.90340856e-03 1.58498928e-01 -4.36896622e-01 8.84320438e-01 2.55465001e-01 1.76638678e-01 -1.05348423e-01 -1.98834434e-01 -3.40038627e-01 3.99008572e-01 2.39976376e-01 9.04813051e-01 1.23420164e-01 3.40757817e-01 -2.75980979e-01 6.78780854e-01 3.72184306e-01 9.09573436e-01 5.25903523e-01 -6.12767994e-01 1.40684068e-01 -1.96881965e-01 -5.53971827e-01 -8.04467678e-01 -7.10166395e-01 -1.10953711e-02 4.77083981e-01 1.10318768e+00 -3.47537875e-01 -1.57887071e-01 -5.47355473e-01 2.55563222e-02 4.19346720e-01 -1.66013077e-01 1.13573186e-01 -8.62520099e-01 -7.71569788e-01 2.46557202e-02 9.36313942e-02 8.93273830e-01 -5.03525198e-01 -1.15972662e+00 3.72415036e-01 -4.07953560e-01 -1.65472555e+00 -2.97886312e-01 -1.85405344e-01 -8.81953418e-01 -1.15242028e+00 -2.19266206e-01 -4.43358541e-01 6.20755553e-01 9.86295342e-01 4.68277216e-01 1.05360657e-01 -2.12769732e-01 2.69257933e-01 -1.52049944e-01 -4.37959969e-01 -3.04610193e-01 -2.97922879e-01 2.77658015e-01 1.44749358e-01 1.33273274e-01 -2.81660557e-01 -6.29982293e-01 6.55550480e-01 -5.81479251e-01 2.66147196e-01 4.50296700e-01 3.99183571e-01 4.90068227e-01 1.83998048e-01 -1.45635009e-01 -1.58809066e-01 -3.09967160e-01 -1.52849808e-01 -1.21582150e+00 -2.33232364e-01 -4.01317686e-01 -2.45142266e-01 1.50999650e-01 -3.54554802e-01 -1.04915488e+00 6.16747260e-01 3.05233866e-01 -7.73169935e-01 -2.41702765e-01 -1.24165781e-01 -1.73973143e-01 -6.52634859e-01 3.41282308e-01 3.44947912e-02 -1.84888262e-02 -1.53366864e-01 2.61634082e-01 4.07124966e-01 5.31015694e-01 8.10755193e-02 1.12750614e+00 9.99990046e-01 5.37112951e-01 -1.16695738e+00 -5.35737634e-01 -9.07507002e-01 -6.63882732e-01 -8.72231364e-01 1.10249603e+00 -1.12730742e+00 -8.03364515e-01 2.84951597e-01 -1.41006052e+00 -1.42217100e-01 -1.03375182e-01 8.94165218e-01 -5.10936975e-01 4.47872788e-01 -1.95419982e-01 -9.52317178e-01 -6.12205192e-02 -1.27188230e+00 8.22281897e-01 4.36743647e-01 2.75048852e-01 -8.49650741e-01 -5.03991246e-02 3.77988040e-01 2.79063314e-01 2.87307888e-01 -3.68875861e-02 -7.47837052e-02 -1.54506028e+00 -3.42113376e-02 -3.10107172e-01 -1.84870631e-01 3.72081110e-03 1.57924034e-02 -8.45728934e-01 -3.24100167e-01 -9.58335325e-02 3.90688807e-01 8.12247694e-01 5.96368551e-01 6.09461367e-01 3.39621492e-03 -6.71929836e-01 8.33756924e-01 1.49669290e+00 2.44797230e-01 4.13462400e-01 3.65718633e-01 9.85838652e-01 3.33266079e-01 1.00960350e+00 3.16413939e-01 5.53891599e-01 9.55554366e-01 9.44532394e-01 1.95913184e-02 -6.10816181e-01 3.11863404e-02 5.34491718e-01 5.18596649e-01 -1.19957544e-01 -4.50964391e-01 -6.61224186e-01 5.42928636e-01 -2.03435922e+00 -1.05853391e+00 -6.29589856e-01 1.96927178e+00 6.20791800e-02 4.34483051e-01 1.18573755e-01 1.11989237e-01 6.73550844e-01 2.45383665e-01 -3.98409128e-01 3.14161539e-01 -2.14964598e-01 -7.44139612e-01 1.04292643e+00 9.46413338e-01 -1.15530145e+00 1.17007184e+00 5.39459896e+00 5.86058199e-01 -8.68432164e-01 1.63346872e-01 -1.53724000e-01 -9.07365158e-02 2.85772443e-01 5.16748056e-02 -1.43191421e+00 1.85177982e-01 4.67851639e-01 4.67527285e-02 1.41931444e-01 5.97509623e-01 3.55980009e-01 -4.76405472e-01 -7.24173844e-01 1.18714631e+00 1.05648115e-01 -1.39043832e+00 -8.54277462e-02 3.16365987e-01 6.05656743e-01 2.72041410e-01 -3.79833639e-01 -2.63532661e-02 3.42711300e-01 -1.17911570e-01 7.27688134e-01 3.75139654e-01 4.33354646e-01 -4.03474033e-01 4.94026423e-01 4.55107838e-01 -1.63341308e+00 -1.36361897e-01 -3.01707715e-01 -1.68699101e-01 6.07391477e-01 6.03140295e-01 -9.17759299e-01 7.44793653e-01 6.90313578e-01 1.06335592e+00 -4.71027642e-01 1.53390038e+00 1.30859122e-01 4.08335030e-02 -6.81505084e-01 -5.95063157e-02 5.92525378e-02 -2.56847471e-01 1.34969223e+00 1.03963757e+00 2.67857730e-01 7.73912221e-02 5.96072376e-01 6.26995742e-01 2.88010031e-01 -3.12962264e-01 -9.34571087e-01 4.76666331e-01 1.86308101e-01 1.37447727e+00 -9.21060085e-01 -4.06235039e-01 -4.51035231e-01 5.84310710e-01 -1.91079363e-01 3.13371390e-01 -7.84586549e-01 2.05261856e-02 7.20007479e-01 1.29260272e-01 4.51639652e-01 -8.20238471e-01 -3.73343885e-01 -1.16606069e+00 -3.22548211e-01 -9.13335234e-02 3.34586143e-01 -5.91514528e-01 -5.32231629e-01 3.19837570e-01 1.01994112e-01 -1.69671214e+00 1.05744656e-02 -5.39814472e-01 -3.10601711e-01 2.70157695e-01 -1.86044466e+00 -1.00316727e+00 -6.25753164e-01 7.32943952e-01 7.31487572e-01 -5.33022657e-02 4.91350666e-02 6.41025960e-01 -5.80693305e-01 5.08491620e-02 -3.36954743e-01 -4.73450646e-02 4.43778634e-01 -7.46921599e-01 -1.09607369e-01 1.44509125e+00 1.11321926e-01 -8.90760645e-02 8.74180019e-01 -8.42352152e-01 -1.56243682e+00 -1.31057346e+00 6.55667901e-01 -4.41058338e-01 4.95625108e-01 -3.52863848e-01 -5.84275007e-01 6.06768966e-01 1.46873400e-01 2.75896817e-01 8.42302293e-02 -5.70609272e-01 4.13349181e-01 -4.76051927e-01 -1.00682199e+00 4.07133013e-01 1.12336838e+00 4.58711907e-02 -3.36974740e-01 2.79483467e-01 6.17916405e-01 -7.26290762e-01 -4.57565218e-01 5.23942709e-01 5.32419682e-01 -8.07583153e-01 1.19175005e+00 1.44204527e-01 -4.53945726e-01 -1.11860251e+00 -1.92834988e-01 -9.23260570e-01 -2.62073427e-01 -7.23697960e-01 -4.78567630e-01 7.68189371e-01 -1.74268991e-01 -3.89402539e-01 8.98877323e-01 1.73389480e-01 -4.09300089e-01 1.56813622e-01 -1.22284591e+00 -8.86748075e-01 -8.90236437e-01 -3.50390434e-01 1.77968174e-01 6.77459419e-01 -3.82465631e-01 4.76671010e-01 -4.00445491e-01 5.66873789e-01 1.16804779e+00 1.09896764e-01 1.37573326e+00 -1.36626184e+00 6.08518720e-03 -3.45244557e-01 -8.49732041e-01 -1.38639045e+00 -1.73648611e-01 -6.39308810e-01 2.33143330e-01 -1.41683221e+00 -1.74903721e-01 -4.27760005e-01 -4.91934121e-02 8.30203369e-02 9.07130481e-04 2.44214475e-01 5.28560162e-01 2.33012483e-01 -9.89483893e-01 6.85738564e-01 1.54012525e+00 -1.18569069e-01 -4.70886439e-01 3.72845754e-02 8.40022042e-02 6.42992318e-01 6.11185968e-01 -6.31270766e-01 -2.09001824e-01 -5.47491312e-01 -1.45990238e-01 1.34335265e-01 6.73737526e-01 -1.51451015e+00 7.88914919e-01 -3.00957859e-01 1.66440308e-01 -1.27424347e+00 7.69699216e-01 -1.31203246e+00 2.50816256e-01 9.17310834e-01 2.80116796e-01 3.58946286e-02 3.60598356e-01 7.64822781e-01 -8.90949974e-04 2.60015339e-01 9.11690593e-01 -4.36251499e-02 -1.13372123e+00 5.50782204e-01 -3.42361450e-01 -3.48202616e-01 1.34590971e+00 -6.84311628e-01 -3.75274211e-01 -6.84624314e-02 -2.62738556e-01 4.21777755e-01 2.72304565e-01 5.27200460e-01 7.51518726e-01 -1.24546504e+00 -6.77315056e-01 4.19395894e-01 4.50416394e-02 3.40081841e-01 9.42840576e-02 1.20483851e+00 -5.38339138e-01 5.34319282e-01 -2.21182480e-01 -1.05488658e+00 -1.34414494e+00 3.78199816e-01 4.67052341e-01 -1.17290474e-01 -6.69644296e-01 4.43342716e-01 3.39146882e-01 -4.29641046e-02 1.51776806e-01 -4.87125278e-01 -2.36394390e-01 -2.49086291e-01 5.92955530e-01 7.80704975e-01 -1.31810233e-01 -9.10685420e-01 -4.77896899e-01 7.91617095e-01 1.89097673e-01 3.13122687e-03 9.63745236e-01 -7.07783639e-01 2.30077758e-01 3.03565800e-01 6.87876165e-01 -2.47536749e-01 -1.57570684e+00 -1.97216675e-01 -3.55021834e-01 -7.45108902e-01 5.78275383e-01 -2.40666613e-01 -1.09441257e+00 7.16093957e-01 8.79715681e-01 4.73797806e-02 7.85261154e-01 -2.22874537e-01 5.67668319e-01 4.72640842e-01 5.29904783e-01 -8.50225925e-01 1.24643175e-02 7.22874522e-01 4.15633470e-01 -1.40870810e+00 1.75418079e-01 -5.77932596e-01 -1.64487034e-01 1.04840624e+00 9.90483105e-01 -1.03558496e-01 6.31809175e-01 2.49080703e-01 -2.36678366e-02 -2.05785215e-01 -4.42738354e-01 -5.70032954e-01 2.21611798e-01 6.10070050e-01 -3.45697910e-01 -3.03432196e-01 -9.76415426e-02 -4.04595762e-01 3.15423369e-01 8.23113397e-02 4.54014689e-01 1.03126752e+00 -9.08182800e-01 -6.42315745e-01 -5.77338398e-01 4.15136442e-02 2.39286199e-02 3.16714674e-01 3.37599330e-02 9.46760595e-01 2.47474775e-01 1.24620926e+00 1.80367902e-01 -5.04553378e-01 3.97640258e-01 -5.75921476e-01 5.82817554e-01 -3.00429046e-01 -3.15398365e-01 2.86838681e-01 4.66509163e-02 -7.68590212e-01 -9.05055404e-01 -7.60117590e-01 -1.33603132e+00 -3.08932573e-01 -6.26483977e-01 -1.79674268e-01 8.09417248e-01 9.21452343e-01 3.20612907e-01 6.22772455e-01 4.99919206e-01 -1.02185333e+00 2.02029511e-01 -7.35647142e-01 -3.38139504e-01 3.19651254e-02 7.40631998e-01 -8.97471189e-01 -3.40641141e-01 1.47827268e-01]	[6.748386383056641, -2.1469478607177734]
5bbaede4-191c-4c93-a882-a370ebdf9801	exploring-depth-information-for-face	2212.1423	null	https://arxiv.org/abs/2212.14230v1	https://arxiv.org/pdf/2212.14230v1.pdf	Exploring Depth Information for Face Manipulation Detection	Face manipulation detection has been receiving a lot of attention for the reliability and security of the face images. Recent studies focus on using auxiliary information or prior knowledge to capture robust manipulation traces, which are shown to be promising. As one of the important face features, the face depth map, which has shown to be effective in other areas such as the face recognition or face detection, is unfortunately paid little attention to in literature for detecting the manipulated face images. In this paper, we explore the possibility of incorporating the face depth map as auxiliary information to tackle the problem of face manipulation detection in real world applications. To this end, we first propose a Face Depth Map Transformer (FDMT) to estimate the face depth map patch by patch from a RGB face image, which is able to capture the local depth anomaly created due to manipulation. The estimated face depth map is then considered as auxiliary information to be integrated with the backbone features using a Multi-head Depth Attention (MDA) mechanism that is newly designed. Various experiments demonstrate the advantage of our proposed method for face manipulation detection.	['Xinpeng Zhang', 'Zhenxing Qian', 'Sheng Li', 'Meiling Li', 'Haoyue Wang']	2022-12-29	null	null	null	null	['face-detection']	['computer-vision']	[ 4.44729507e-01 9.31317434e-02 2.67944094e-02 -3.82484049e-01 -3.53359729e-01 -1.76519692e-01 5.65594614e-01 -4.48295802e-01 -7.21292291e-03 2.56651849e-01 -1.29518127e-02 3.83035928e-01 -7.86655992e-02 -7.22215712e-01 -5.91210246e-01 -1.00415862e+00 1.66648582e-01 5.53347804e-02 1.84537411e-01 -1.52388588e-01 7.48309612e-01 8.59205604e-01 -2.13629532e+00 1.61960572e-01 4.71846104e-01 1.36790764e+00 3.30955833e-01 1.94899619e-01 -2.33859699e-02 5.69618344e-01 -4.71808523e-01 -3.44305009e-01 3.22527796e-01 -3.47825170e-01 -3.68323058e-01 2.41567135e-01 4.96106297e-01 -8.80964756e-01 -9.59241465e-02 1.05971336e+00 7.93576837e-01 -1.54643685e-01 5.54581821e-01 -1.37983704e+00 -1.35168090e-01 2.00001463e-01 -9.77029383e-01 2.68032312e-01 6.62693262e-01 1.03142366e-01 1.80775240e-01 -1.04068589e+00 5.67956150e-01 1.53967273e+00 2.97916144e-01 7.82431602e-01 -4.45842147e-01 -1.02917945e+00 6.97953627e-02 5.01500726e-01 -1.34693515e+00 -9.65359688e-01 1.22736561e+00 -1.88322410e-01 4.11593139e-01 2.29155216e-02 3.69192600e-01 9.44896460e-01 7.80860633e-02 6.73346877e-01 1.11604810e+00 -4.79572266e-01 -5.91882840e-02 4.65226740e-01 -1.16309494e-01 9.82178926e-01 1.71489909e-01 1.60209760e-01 -6.25980556e-01 1.74592599e-01 8.79855454e-01 8.85409713e-02 -5.16792357e-01 3.84934060e-02 -5.89838445e-01 4.41121191e-01 5.36452830e-01 1.70566455e-01 -5.10034442e-01 -1.25657678e-01 1.90036744e-01 4.32606265e-02 5.02209961e-01 -1.47617787e-01 -1.43038258e-01 6.35797009e-02 -5.86161911e-01 3.08032129e-02 3.16095382e-01 8.61059189e-01 7.51926601e-01 3.21148825e-03 -2.30657130e-01 5.14154434e-01 5.29308856e-01 6.37129903e-01 1.09529644e-01 -8.52460861e-01 4.01780158e-01 9.67074394e-01 -9.95857045e-02 -1.26724637e+00 -3.00000638e-01 4.18714136e-02 -5.53723872e-01 3.82668644e-01 2.86184907e-01 2.10291252e-01 -5.27280569e-01 1.71307814e+00 9.35422361e-01 3.51830602e-01 -2.92254120e-01 9.48399365e-01 8.87230158e-01 3.24972034e-01 -2.48338506e-01 -3.93621683e-01 1.46499336e+00 -6.69980347e-01 -7.90092468e-01 -1.32153437e-01 1.13792345e-01 -6.93688393e-01 8.08208287e-01 5.01089871e-01 -9.37008858e-01 -5.02102137e-01 -9.15697336e-01 -6.48982525e-02 -2.83348501e-01 1.34828597e-01 5.52874207e-01 9.78444755e-01 -9.83361006e-01 2.74604112e-01 -8.60703826e-01 -3.45212609e-01 6.45419657e-01 5.46362877e-01 -6.69597566e-01 -3.59945625e-01 -7.85448134e-01 8.59958053e-01 1.58715934e-01 5.90975344e-01 -1.18529296e+00 -3.68959129e-01 -8.69144738e-01 9.15625170e-02 5.04872918e-01 -2.11049661e-01 6.89838886e-01 -7.97279775e-01 -1.72843778e+00 8.77082705e-01 -3.79047424e-01 2.80988932e-01 2.44898304e-01 -1.10277489e-01 -1.09181553e-01 5.92763662e-01 -9.61335599e-02 4.85819340e-01 1.48996043e+00 -1.37321687e+00 -3.42342883e-01 -1.17515731e+00 1.19666688e-01 1.33449793e-01 -6.71388865e-01 5.03925443e-01 -4.60709393e-01 -4.43862766e-01 1.62519336e-01 -6.06648684e-01 4.69346315e-01 3.80749911e-01 -2.14980081e-01 -3.41257185e-01 1.20036674e+00 -9.44187045e-01 1.10487175e+00 -1.95518982e+00 2.45076314e-01 8.79836380e-02 2.87285149e-02 2.58844942e-01 -1.62694916e-01 2.16525748e-01 7.20306188e-02 -2.23936513e-01 -1.81123346e-01 -4.86347944e-01 -3.79166007e-01 -5.10845110e-02 -1.02327071e-01 9.28031147e-01 5.29302478e-01 6.89697742e-01 -4.84016925e-01 -4.93949383e-01 3.43920797e-01 7.79036403e-01 -4.34278548e-01 4.43586290e-01 2.91645434e-02 8.33733559e-01 -6.42558217e-01 1.17888069e+00 1.20518506e+00 3.60433549e-01 -1.82656780e-01 -3.95699114e-01 -1.10043466e-01 -1.97359428e-01 -1.03096175e+00 1.40305877e+00 -2.25838691e-01 8.72757137e-02 5.32851219e-01 -7.77796090e-01 8.28735292e-01 2.94552058e-01 2.77618080e-01 -7.75789082e-01 5.60734093e-01 -1.85159184e-02 -1.48424536e-01 -8.22884798e-01 -1.68111976e-02 -2.96605914e-03 4.75033104e-01 5.72533369e-01 -8.68190303e-02 -4.72602807e-02 -2.29719996e-01 -1.23405918e-01 8.13710272e-01 2.86394536e-01 1.28037021e-01 2.84151230e-02 1.09058344e+00 -5.40952265e-01 3.80171239e-01 7.10000545e-02 -2.77865380e-01 4.28783536e-01 3.88744950e-01 -2.77580228e-03 -5.85061967e-01 -4.90477443e-01 -2.81506360e-01 9.35578108e-01 3.08756381e-01 -6.36372492e-02 -1.14590013e+00 -5.52807152e-01 -7.59671852e-02 -9.50285420e-03 -6.80395663e-01 -4.09270853e-01 -6.53363228e-01 -4.12472367e-01 3.89231741e-01 3.97436559e-01 6.94544852e-01 -1.37194765e+00 -7.47363567e-01 -3.12417567e-01 -6.22775890e-02 -1.12073243e+00 -1.59857050e-01 -2.01153830e-01 -7.55196035e-01 -1.31224251e+00 -6.57522321e-01 -6.01393461e-01 8.58606219e-01 5.07957220e-01 3.72668386e-01 3.48655283e-01 -5.36851406e-01 4.03064966e-01 -3.80120605e-01 -4.31271166e-01 -2.22101174e-02 -2.18494043e-01 2.37035289e-01 5.13629854e-01 3.09757203e-01 -4.43548262e-01 -7.88186073e-01 3.86854112e-01 -9.41673219e-01 -4.00566757e-01 5.69758534e-01 5.71793556e-01 1.81504786e-01 2.26802185e-01 5.85733712e-01 -7.00336754e-01 2.12384641e-01 -4.01418835e-01 -5.90374589e-01 1.26277328e-01 -2.00109720e-01 -1.58227861e-01 2.66889274e-01 -2.39938647e-01 -1.28578019e+00 -3.45640033e-02 -1.80382207e-01 -6.51144862e-01 -2.77629972e-01 7.61895403e-02 -8.52989137e-01 -5.78799188e-01 1.84471473e-01 2.03315362e-01 3.94822985e-01 -5.15177786e-01 2.60681771e-02 8.87967646e-01 3.19279879e-01 -4.79524285e-01 8.59271586e-01 7.24344790e-01 3.24754596e-01 -9.46283221e-01 -6.64656579e-01 -4.38873112e-01 -6.81237102e-01 -4.70634758e-01 7.86212742e-01 -7.06667483e-01 -1.29935563e+00 8.01899493e-01 -1.22659445e+00 8.77542198e-02 5.21392763e-01 2.23923162e-01 -3.27685833e-01 6.64365828e-01 -3.77219796e-01 -1.30441809e+00 -4.33887511e-01 -1.24356651e+00 1.73598230e+00 2.64992744e-01 5.50445259e-01 -5.47965348e-01 -4.34603333e-01 4.82990861e-01 3.65578979e-01 3.82886976e-01 6.56224489e-01 -3.00053284e-02 -8.69623542e-01 -3.91965479e-01 -2.29592726e-01 2.92747200e-01 2.86280513e-01 -2.04874054e-01 -1.50177634e+00 -4.05046135e-01 6.41549647e-01 -1.96614847e-01 6.84886634e-01 1.68273568e-01 1.25859499e+00 -1.54608220e-01 -4.11189139e-01 6.62129045e-01 1.28138959e+00 1.60204023e-01 8.71869147e-01 -1.04080597e-02 7.92115271e-01 1.04114127e+00 9.26779628e-01 5.91856360e-01 1.66241527e-01 8.29664290e-01 8.85435879e-01 3.06553751e-01 -7.97609240e-02 3.79987247e-02 6.71230078e-01 5.48608959e-01 -2.68337876e-01 -5.96497245e-02 -5.59190094e-01 1.21138722e-01 -1.43707418e+00 -1.00670600e+00 8.49485025e-02 2.16847396e+00 2.62426555e-01 -9.91149470e-02 -4.70177047e-02 5.71209669e-01 8.87081325e-01 -1.07846230e-01 -5.28983474e-01 3.20641622e-02 1.44540086e-01 3.97978306e-01 8.49693716e-02 1.60410136e-01 -8.83303463e-01 7.79009461e-01 5.11502790e+00 7.70040512e-01 -1.14533079e+00 1.78284615e-01 3.38460416e-01 2.43370399e-01 3.54036912e-02 -2.27026924e-01 -1.10182464e+00 6.03455305e-01 4.35501754e-01 2.59963185e-01 4.02073950e-01 8.56268048e-01 1.78407863e-01 -3.88459831e-01 -1.10169685e+00 1.21759892e+00 6.74154103e-01 -4.23232049e-01 7.13836625e-02 1.40497282e-01 2.24713027e-01 -7.20319986e-01 2.81632155e-01 1.07134238e-01 -8.62462997e-01 -9.77575719e-01 5.53292334e-01 5.88723898e-01 8.15107882e-01 -8.93934011e-01 7.56664515e-01 5.27201295e-01 -1.28193998e+00 -4.48700696e-01 -4.90699440e-01 -1.19730368e-01 1.08135127e-01 3.92632306e-01 -7.99322069e-01 4.27245587e-01 5.65154135e-01 5.80314934e-01 -5.89235842e-01 8.09962749e-01 -2.96291947e-01 1.42179906e-01 -3.90404880e-01 3.23985815e-01 -3.10246676e-01 -1.27577931e-01 4.37911570e-01 4.20525014e-01 3.08483511e-01 2.30366677e-01 -4.76661138e-03 7.84704924e-01 -4.16142978e-02 4.62040491e-02 -8.27013969e-01 3.11088469e-02 3.56382430e-01 1.40448892e+00 -7.41463661e-01 -8.94542201e-04 -3.82436603e-01 1.03056049e+00 2.16790617e-01 -5.22057433e-03 -7.35499859e-01 -1.57237977e-01 5.84454715e-01 4.08890903e-01 2.18934640e-01 9.05391276e-02 1.49514690e-01 -9.93206680e-01 4.60005373e-01 -6.58753574e-01 1.35026813e-01 -6.75719082e-01 -9.96681213e-01 6.82226777e-01 6.30576164e-02 -1.04332638e+00 -7.47060105e-02 -8.09036136e-01 -5.85503042e-01 8.10237765e-01 -1.83419096e+00 -1.36996114e+00 -9.90998983e-01 8.37786794e-01 6.16699338e-01 -1.11065172e-01 5.75375140e-01 4.99662817e-01 -8.89245987e-01 8.21490586e-01 -5.57990372e-01 -6.37581274e-02 6.07859015e-01 -5.78759789e-01 -1.38465110e-02 7.86888838e-01 -4.13995832e-01 6.39101267e-01 3.91915530e-01 -6.22347474e-01 -2.00477672e+00 -9.54196036e-01 1.88289836e-01 -7.67245054e-01 -4.55126278e-02 -4.39545274e-01 -8.68679702e-01 5.64406037e-01 -2.28695586e-01 1.63473696e-01 6.86204508e-02 -4.94144559e-01 -2.48518407e-01 -3.07280600e-01 -1.57995009e+00 1.15548164e-01 1.17077720e+00 -6.24863386e-01 -3.45085740e-01 2.04388555e-02 1.97929502e-01 -2.74615258e-01 -6.62063241e-01 8.08930159e-01 7.28273630e-01 -1.11736131e+00 1.01331031e+00 1.97015749e-03 3.54138523e-01 -2.97679931e-01 -9.62946713e-02 -6.69421971e-01 1.34900659e-01 -2.59966642e-01 -4.44967896e-01 1.59456062e+00 -3.67929786e-01 -5.48914015e-01 8.93653810e-01 4.27379847e-01 4.95078266e-02 -7.44311512e-01 -9.94309783e-01 -3.47676069e-01 -3.78922582e-01 -2.30752498e-01 6.69233322e-01 6.85555279e-01 -1.57494873e-01 3.61460447e-02 -3.74046981e-01 4.04646039e-01 7.26540387e-01 2.65811980e-02 8.79312396e-01 -1.33091938e+00 9.46987569e-02 -3.42676669e-01 -7.80412078e-01 -8.46727610e-01 3.96217138e-01 -7.33725548e-01 -2.05776542e-02 -1.20872116e+00 2.98424453e-01 -1.98369712e-01 4.47533876e-02 3.31436723e-01 -2.46683940e-01 5.27835250e-01 -2.28342284e-02 -1.09602980e-01 -1.12804309e-01 7.87826538e-01 1.21181476e+00 -1.80863384e-02 -1.06462231e-02 -1.44671947e-02 -6.00158691e-01 5.58384597e-01 4.22038794e-01 -3.05464447e-01 -3.07036519e-01 -3.16132665e-01 -1.18738219e-01 2.43171975e-01 3.10528904e-01 -1.01523781e+00 2.02515721e-01 6.25650361e-02 5.06755590e-01 -6.47975624e-01 6.99562311e-01 -1.02589929e+00 -1.63111255e-01 3.51123273e-01 2.97593772e-01 -5.04734702e-02 1.26729712e-01 6.95288062e-01 -1.72915921e-01 -2.53585577e-01 9.45098758e-01 -2.33544737e-01 -7.03855276e-01 5.56503296e-01 1.36436358e-01 -6.03486419e-01 1.34491765e+00 -4.48222637e-01 -2.27005973e-01 -8.91060308e-02 -3.16059679e-01 1.25232056e-01 3.19813728e-01 5.70490479e-01 9.18258965e-01 -1.27563417e+00 -5.90844214e-01 6.98700249e-01 2.28704602e-01 -4.41261083e-02 4.70796853e-01 1.05350780e+00 -4.19183403e-01 2.33344242e-01 -3.90090942e-01 -7.27187335e-01 -1.45881605e+00 9.08313692e-01 1.79781288e-01 3.75095367e-01 -5.20135105e-01 8.38884890e-01 3.26396614e-01 -3.43027301e-02 4.55284953e-01 -5.50551862e-02 -4.76420015e-01 1.99135214e-01 9.21835303e-01 4.74156678e-01 1.40452549e-01 -8.89578998e-01 -5.29935837e-01 1.14082420e+00 6.22364506e-02 2.62980253e-01 1.22497821e+00 -4.45693821e-01 -5.31343758e-01 1.67948585e-02 1.18599975e+00 -9.60555598e-02 -1.12538540e+00 -3.53628509e-02 -1.49010450e-01 -9.53089058e-01 6.46899715e-02 -3.19174320e-01 -1.36941969e+00 1.28970563e+00 8.83920968e-01 -3.14224392e-01 1.43573153e+00 7.77016431e-02 6.36879086e-01 1.36269048e-01 8.56722832e-01 -6.99739754e-01 3.26484472e-01 8.86780247e-02 1.02356577e+00 -1.41569614e+00 -1.46360442e-01 -7.87080586e-01 -1.68612540e-01 1.23511803e+00 9.57157016e-01 -1.24293985e-02 7.21434534e-01 2.57076651e-01 -2.25276619e-01 -4.62926626e-01 -2.61236668e-01 -3.68941844e-01 6.26564994e-02 6.16362512e-01 8.73533543e-03 -4.64977384e-01 8.12022761e-02 4.18945342e-01 1.29301086e-01 -3.76773104e-02 1.76141575e-01 9.51100588e-01 -5.77012479e-01 -9.03539896e-01 -6.20027363e-01 2.62643576e-01 -3.53076726e-01 2.11792439e-01 -3.01711529e-01 5.33900082e-01 3.50032955e-01 7.95957625e-01 -1.07973054e-01 -1.54687122e-01 2.20804572e-01 4.87205684e-02 1.02855611e+00 -7.28131831e-01 -3.50646406e-01 -1.70501739e-01 -4.96585637e-01 -6.71888530e-01 -7.13236868e-01 -3.73445183e-01 -8.17026377e-01 -1.69684395e-01 -7.25448906e-01 -3.68687630e-01 7.18342602e-01 8.82654369e-01 6.58019409e-02 2.12157175e-01 1.04891050e+00 -1.43941128e+00 -2.51538128e-01 -1.21619749e+00 -6.63838923e-01 3.94923866e-01 4.18730050e-01 -1.26719475e+00 -5.04967034e-01 -2.97314793e-01]	[13.330334663391113, 0.46657058596611023]
6413a346-8428-4f91-9a44-cc842d15ca16	event-coreference-resolution-using-neural	1810.04216	null	http://arxiv.org/abs/1810.04216v1	http://arxiv.org/pdf/1810.04216v1.pdf	Event Coreference Resolution Using Neural Network Classifiers	This paper presents a neural network classifier approach to detecting both within- and cross- document event coreference effectively using only event mention based features. Our approach does not (yet) rely on any event argument features such as semantic roles or spatiotemporal arguments. Experimental results on the ECB+ dataset show that our approach produces F1 scores that significantly outperform the state-of-the-art methods for both within-document and cross-document event coreference resolution when we use B3 and CEAFe evaluation measures, but gets worse F1 score with the MUC measure. However, when we use the CoNLL measure, which is the average of these three scores, our approach has slightly better F1 for within- document event coreference resolution but is significantly better for cross-document event coreference resolution.	['Kemal Oflazer', 'Lamana Mulaffer', 'Amna AlZeyara', 'Arun Pandian']	2018-10-09	null	null	null	null	['cross-document-coreference-resolution']	['natural-language-processing']	[ 1.04413107e-01 1.98531389e-01 -5.20627737e-01 -3.71398687e-01 -1.33541572e+00 -9.33177710e-01 1.25070930e+00 6.77174330e-01 -1.01921988e+00 1.00723267e+00 7.56277919e-01 -1.84247538e-01 -6.67365670e-01 -5.91780841e-01 -4.63985801e-01 -4.58159208e-01 -1.69954598e-01 6.82570159e-01 5.66486418e-01 -2.87151396e-01 2.33525053e-01 6.10542774e-01 -1.42580521e+00 7.85046995e-01 3.46414298e-01 8.45021129e-01 -3.28651041e-01 5.34910381e-01 1.39674112e-01 9.37000334e-01 -8.88291001e-01 -5.33648729e-01 -4.76563394e-01 -3.60684752e-01 -1.35532796e+00 -1.12178206e+00 3.26188266e-01 2.08815113e-01 -3.03210288e-01 7.97565639e-01 7.81159699e-01 3.91119689e-01 5.21639407e-01 -1.10222781e+00 4.45231423e-03 1.16942060e+00 -2.48584494e-01 8.23403120e-01 7.73926139e-01 -7.50670254e-01 1.16341078e+00 -5.78312814e-01 9.49625552e-01 1.55872488e+00 8.82953525e-01 2.83313334e-01 -1.11306882e+00 -8.06194067e-01 -9.17167682e-03 4.88750964e-01 -9.21514273e-01 -4.31297392e-01 5.66302359e-01 7.91050196e-02 1.51250875e+00 4.38519925e-01 2.35490501e-01 1.41905141e+00 1.29627630e-01 7.08407283e-01 8.65557492e-01 -6.18737340e-01 -2.50338148e-02 -2.41370425e-01 5.43926179e-01 4.53258120e-02 1.27023965e-01 5.42129159e-01 -6.23095512e-01 -3.09914827e-01 3.58019143e-01 -5.48269331e-01 -4.32811707e-01 3.04345697e-01 -1.30133545e+00 9.47139561e-01 3.25010031e-01 1.03939664e+00 -4.71065313e-01 -9.45651606e-02 8.86483252e-01 9.68794897e-02 4.71131764e-02 5.04571974e-01 -6.96509123e-01 -4.36758399e-01 -1.13756216e+00 5.65521181e-01 1.03269196e+00 4.08451825e-01 -4.04348336e-02 -2.65929431e-01 -4.47425932e-01 8.59853625e-01 -2.65576512e-01 1.01252079e-01 4.26170915e-01 -1.39292288e+00 4.80096281e-01 2.96106130e-01 2.92655498e-01 -1.00720012e+00 -9.65243161e-01 1.02469036e-02 -3.15694213e-01 -1.71432540e-01 5.81860304e-01 -1.79341361e-01 -3.21853757e-01 2.20382833e+00 1.54904425e-01 -1.40346125e-01 4.87030894e-01 7.35755026e-01 1.43667614e+00 4.53361899e-01 4.00962114e-01 -7.15868950e-01 1.63450289e+00 -5.45457244e-01 -1.11078179e+00 6.86286390e-03 6.72481239e-01 -6.74857438e-01 3.91846955e-01 3.47531259e-01 -1.35846627e+00 -3.80462736e-01 -1.10666597e+00 -4.09042323e-03 -4.17109132e-01 -2.50548303e-01 6.44471884e-01 3.13934237e-01 -6.80033088e-01 5.58340907e-01 -5.31708360e-01 -5.62479317e-01 -1.35644764e-01 2.90745735e-01 -6.80886328e-01 3.56651723e-01 -1.78285742e+00 1.39606774e+00 1.09657836e+00 -6.07423902e-01 -5.12884796e-01 -6.19256556e-01 -8.41083288e-01 2.47751206e-01 4.52790648e-01 -8.44297484e-02 1.41911161e+00 -6.12910688e-01 -9.65483367e-01 9.45246994e-01 -8.05238485e-02 -6.24996185e-01 2.56579280e-01 -3.02440822e-01 -9.35506284e-01 4.46213901e-01 1.76088378e-01 8.40015650e-01 -1.03904061e-01 -9.56749201e-01 -1.05416822e+00 -8.13229289e-03 4.42303866e-01 2.58417487e-01 7.15290159e-02 8.69148791e-01 -4.73610237e-02 -5.75889349e-01 -8.87222365e-02 -7.39499688e-01 4.38558877e-01 -4.81406063e-01 -2.35108554e-01 -9.79999602e-01 8.64130974e-01 -4.22620773e-01 1.29946792e+00 -2.05311346e+00 -6.49826080e-02 -1.18495092e-01 -3.87192398e-01 2.51105756e-01 -3.75249796e-02 4.50877070e-01 -8.86191785e-01 3.09694894e-02 4.70113009e-02 1.11440979e-01 -1.90367680e-02 1.84455439e-01 -1.80142224e-01 3.09195668e-01 3.67837027e-02 5.66198051e-01 -8.41617763e-01 -8.42031181e-01 7.54524693e-02 4.95299876e-01 -4.33422059e-01 -1.56185463e-01 9.46822762e-02 1.14812627e-01 -1.86759025e-01 6.79204091e-02 3.71571720e-01 6.95627108e-02 6.56588137e-01 -5.42950153e-01 -2.51536578e-01 8.31225455e-01 -1.17141104e+00 1.63911128e+00 -2.19923690e-01 7.04400957e-01 -4.07399312e-02 -1.41247070e+00 6.35576546e-01 9.41638827e-01 3.43489647e-01 -8.30062509e-01 3.44412088e-01 2.12864608e-01 2.99950898e-01 -1.90745175e-01 4.75789696e-01 -2.39821181e-01 -6.08636975e-01 4.11821008e-01 1.79942831e-01 3.98154706e-01 4.79858220e-01 4.01318431e-01 1.05998242e+00 1.68961138e-02 7.17629790e-01 -4.62026000e-01 7.05074430e-01 2.94233523e-02 7.41207957e-01 8.59699130e-01 -2.28939220e-01 4.92305964e-01 7.00162590e-01 -4.58836138e-01 -4.42566067e-01 -9.66203570e-01 -5.50598979e-01 1.09334564e+00 3.93467322e-02 -5.40958941e-01 -6.92611039e-01 -1.08070576e+00 -3.17444563e-01 1.26937521e+00 -6.54489756e-01 2.95462664e-02 -1.03179801e+00 -8.67616236e-01 1.21716189e+00 9.54016089e-01 4.24643427e-01 -1.48011220e+00 -7.96579421e-01 5.19905210e-01 -1.03519785e+00 -1.22073090e+00 -2.64072925e-01 6.25487149e-01 -5.45263827e-01 -1.35581481e+00 -3.25665355e-01 -8.18531871e-01 -2.91116744e-01 -5.42474508e-01 1.33394992e+00 -2.87105069e-02 -4.11048606e-02 1.74334183e-01 -5.01505613e-01 -4.57374245e-01 -4.47572231e-01 -1.57344371e-01 -5.90843800e-03 -5.66414535e-01 6.71614468e-01 -4.49381292e-01 -3.28436345e-01 1.87872246e-01 -6.13314152e-01 -6.20383739e-01 2.71973815e-02 1.02790082e+00 3.07066441e-01 1.26033634e-01 6.95087612e-01 -5.82703114e-01 7.69458055e-01 -2.34931216e-01 -1.76546752e-01 2.66525835e-01 -3.81199181e-01 -5.85973561e-02 1.35128155e-01 -6.69024885e-01 -1.43078578e+00 -5.46586454e-01 -1.08962916e-01 -4.56225164e-02 -4.62771624e-01 4.04630303e-01 -1.29924983e-01 5.97767711e-01 7.79809713e-01 -3.38119328e-01 -6.65544510e-01 -3.43041301e-01 1.24091625e-01 5.39924026e-01 1.00492513e+00 -7.50461757e-01 -1.40913680e-01 3.94846708e-01 -1.36316791e-01 -3.61796468e-01 -1.05038381e+00 -4.31747913e-01 -5.44905484e-01 4.32183370e-02 1.13991868e+00 -6.91794813e-01 -1.02612603e+00 4.27388661e-02 -1.65877712e+00 2.47322232e-01 -1.65933356e-01 9.22514379e-01 -7.35283494e-01 2.63672680e-01 -8.75465751e-01 -5.61116219e-01 -3.44284922e-01 -9.14747715e-01 9.12051737e-01 2.81003475e-01 -1.00706792e+00 -1.00152791e+00 2.65744358e-01 9.84915420e-02 -3.90458410e-03 5.33834696e-01 1.00767827e+00 -1.37857723e+00 3.25154901e-01 -1.42960951e-01 -2.17556208e-01 -2.11963281e-01 -8.56426656e-02 -5.45868218e-01 -8.14022779e-01 -1.64636120e-01 -1.48508564e-01 -3.64063382e-01 7.72265851e-01 5.37950873e-01 6.40852153e-01 -5.18610030e-02 -6.71718419e-01 2.00618714e-01 1.05200660e+00 7.57273853e-01 7.49134421e-01 7.48774648e-01 -3.86747979e-02 7.07779646e-01 9.34653819e-01 1.67964488e-01 3.09994489e-01 9.79707897e-01 -9.74678434e-03 1.53234825e-01 -2.41068557e-01 9.22083557e-02 2.20907077e-01 3.87160853e-02 -2.77267784e-01 -5.73927999e-01 -7.72942483e-01 7.79928625e-01 -2.01772714e+00 -1.56526256e+00 -1.90549597e-01 1.78918338e+00 9.25254703e-01 3.49385709e-01 8.16977695e-02 6.49648011e-01 9.98352826e-01 1.68243557e-01 4.87076305e-02 -8.87974918e-01 -4.77095425e-01 4.97867554e-01 1.75568983e-02 3.93281311e-01 -1.41006637e+00 8.61297607e-01 7.07764292e+00 6.98383570e-01 -7.75928974e-01 2.36985579e-01 -1.12631237e-02 -2.54506826e-01 1.44001380e-01 -5.98356463e-02 -9.11195099e-01 3.08483899e-01 1.31368208e+00 5.11501320e-02 3.91224166e-04 3.51262808e-01 -2.12639093e-01 -3.01625550e-01 -1.35664582e+00 8.45156252e-01 2.12799743e-01 -1.45541573e+00 -2.19960108e-01 -2.62387186e-01 1.46266297e-01 -4.16403972e-02 -5.69252253e-01 3.87006462e-01 4.45076317e-01 -7.70977616e-01 8.82880926e-01 1.42594963e-01 6.43596411e-01 -1.03777146e+00 9.89132643e-01 2.53240854e-01 -1.10117757e+00 -3.89310606e-02 1.93586230e-01 3.56023043e-01 4.37975973e-01 4.97731864e-02 -3.95341337e-01 6.82170808e-01 1.16336417e+00 3.09493750e-01 3.55199389e-02 8.08930933e-01 -3.56658787e-01 4.37400162e-01 -3.97899181e-01 1.06947511e-01 2.88144320e-01 7.00300395e-01 9.03258920e-01 1.67302978e+00 1.85245827e-01 4.90766883e-01 7.71189183e-02 3.67031962e-01 8.85867029e-02 -1.22576244e-01 -3.37710917e-01 2.68908709e-01 8.97913396e-01 9.95018065e-01 -7.67004669e-01 -4.24100786e-01 -1.87296227e-01 7.18161643e-01 2.46942133e-01 4.48069200e-02 -1.00050330e+00 -7.49936044e-01 2.83419818e-01 -2.67900705e-01 4.16112304e-01 5.03391922e-01 2.81428665e-01 -7.16831088e-01 -3.04631621e-01 -9.15633857e-01 1.30205977e+00 -8.56895030e-01 -9.94178832e-01 6.45951927e-01 7.22986281e-01 -7.14148223e-01 -7.76727974e-01 -5.45584798e-01 -7.62504935e-01 5.68360090e-01 -1.27657568e+00 -1.09029853e+00 2.58709699e-01 7.76455641e-01 1.89133570e-01 -5.31568415e-02 1.20255280e+00 3.27273160e-01 -3.00334673e-02 6.73098087e-01 -3.78425360e-01 4.87521857e-01 1.12784362e+00 -1.09007025e+00 -1.30542308e-01 5.51017225e-01 1.96318969e-01 5.53969860e-01 8.28527987e-01 -5.53840399e-01 -5.52840889e-01 -4.64174837e-01 1.54074967e+00 -5.27979851e-01 4.27956969e-01 3.31169069e-01 -7.03833520e-01 1.02247500e+00 5.82160115e-01 -2.17388719e-01 6.62352920e-01 6.07492089e-01 -5.13664067e-01 2.32657269e-01 -1.40440166e+00 1.79127023e-01 1.16382468e+00 -4.81109142e-01 -1.61026812e+00 1.53138518e-01 7.15437293e-01 -4.72647399e-01 -1.20766699e+00 1.02107120e+00 4.67862427e-01 -9.61227536e-01 1.18906593e+00 -9.24783051e-01 6.45008236e-02 -3.14623378e-02 -4.32060003e-01 -1.08006275e+00 -4.64259744e-01 -2.52871364e-01 8.66348296e-02 1.44175124e+00 5.33915818e-01 -4.70950484e-01 1.80663273e-01 1.99853510e-01 -1.13973938e-01 -1.19458809e-01 -1.25914538e+00 -5.83469510e-01 3.04972112e-01 -4.73853439e-01 5.16660631e-01 1.27213132e+00 5.27508497e-01 4.11065370e-01 1.42383354e-03 7.51912943e-04 4.53589648e-01 3.64327341e-01 -9.40454006e-02 -1.69184124e+00 -6.68589771e-02 -5.29548049e-01 -3.37054916e-02 -1.46458507e-01 7.22451091e-01 -9.27605689e-01 -6.40970320e-02 -1.27413130e+00 4.20637488e-01 -7.71388933e-02 -6.06785953e-01 5.97876668e-01 6.75687790e-02 1.59301832e-01 2.62191035e-02 -9.49415788e-02 -6.37223125e-01 -5.16213588e-02 7.15773702e-01 1.14430256e-01 -1.18242107e-01 -5.03007889e-01 -6.42611325e-01 1.01812315e+00 5.11009455e-01 -8.16036522e-01 2.62584500e-02 -9.63867828e-02 -7.92425051e-02 6.35607123e-01 2.64078945e-01 -8.50939095e-01 2.62589157e-01 3.65772732e-02 6.52941942e-01 -9.11305130e-01 4.41780329e-01 -3.94632697e-01 1.02966309e-01 4.35077727e-01 -5.88606596e-01 3.93349409e-01 6.27869010e-01 2.77167022e-01 -4.55428600e-01 -3.44102412e-01 8.33113968e-01 -1.35305747e-01 -6.66694105e-01 -5.09146452e-01 -5.54586112e-01 4.32196945e-01 7.61379182e-01 5.05942106e-02 -5.59719980e-01 -3.30499828e-01 -1.08640003e+00 6.40935032e-03 -5.64574376e-02 7.09039986e-01 2.40681455e-01 -1.34007287e+00 -8.61909449e-01 -3.51878256e-01 3.34277079e-02 -6.34391844e-01 3.41939852e-02 8.09916735e-01 2.60189958e-02 8.72736573e-01 -1.21390350e-01 -4.79000062e-01 -1.72630966e+00 3.72869045e-01 4.16696101e-01 -7.27107286e-01 -6.00447595e-01 6.47597909e-01 6.10255264e-02 -4.02031809e-01 3.98671120e-01 1.04411803e-01 -7.82026708e-01 6.12005413e-01 7.74322689e-01 2.95925140e-01 2.23449230e-01 -9.57986772e-01 -9.41652477e-01 3.28243136e-01 -1.20775096e-01 -4.88763839e-01 1.28925931e+00 3.15137357e-01 -2.12063827e-02 1.15348056e-01 9.42228913e-01 -2.58110650e-02 -3.15245152e-01 -2.18778360e-03 5.04847527e-01 1.84230089e-01 2.09432095e-01 -1.42797339e+00 -6.59510553e-01 5.73185861e-01 5.34253120e-01 2.07117975e-01 9.96024966e-01 3.75035316e-01 6.34842396e-01 4.82559294e-01 2.85714626e-01 -1.15129817e+00 -1.40591756e-01 7.01418877e-01 9.89348054e-01 -7.88325965e-01 -1.14404120e-01 -1.81733891e-01 -4.96518433e-01 1.02565813e+00 3.83656412e-01 -1.07210115e-01 5.74938715e-01 6.58611715e-01 -1.47699848e-01 -2.95986205e-01 -7.82196105e-01 -1.74632236e-01 3.14296484e-01 3.66822511e-01 7.43803740e-01 -1.16420083e-03 -9.08920765e-01 9.25607920e-01 -3.24029565e-01 -1.23266466e-01 1.46078125e-01 7.45669127e-01 -1.72237456e-01 -1.25105906e+00 -5.13845980e-01 6.81187958e-03 -1.21562505e+00 -6.01795875e-02 -5.59523880e-01 1.52574539e+00 2.39561468e-01 1.14944720e+00 4.71077919e-01 -9.93526801e-02 6.34082913e-01 3.91468346e-01 7.53696799e-01 -1.52023241e-01 -1.02266920e+00 1.45780951e-01 1.13593018e+00 -8.27053547e-01 -1.07640302e+00 -1.00817966e+00 -1.58564448e+00 -2.13281766e-01 -4.92003918e-01 4.81545597e-01 3.07568431e-01 1.03453922e+00 4.35178131e-02 3.93330276e-01 4.79370775e-03 -7.23364472e-01 -5.35757951e-02 -1.14842701e+00 -2.32298508e-01 7.08842278e-01 2.18548149e-01 -9.91889536e-01 -4.54282999e-01 -3.33285183e-01]	[9.245667457580566, 9.52568244934082]
56d34372-e61b-4702-ba8c-68dfab100062	very-long-natural-scenery-image-prediction-by-1	1912.12688	null	https://arxiv.org/abs/1912.12688v1	https://arxiv.org/pdf/1912.12688v1.pdf	Very Long Natural Scenery Image Prediction by Outpainting	Comparing to image inpainting, image outpainting receives less attention due to two challenges in it. The first challenge is how to keep the spatial and content consistency between generated images and original input. The second challenge is how to maintain high quality in generated results, especially for multi-step generations in which generated regions are spatially far away from the initial input. To solve the two problems, we devise some innovative modules, named Skip Horizontal Connection and Recurrent Content Transfer, and integrate them into our designed encoder-decoder structure. By this design, our network can generate highly realistic outpainting prediction effectively and efficiently. Other than that, our method can generate new images with very long sizes while keeping the same style and semantic content as the given input. To test the effectiveness of the proposed architecture, we collect a new scenery dataset with diverse, complicated natural scenes. The experimental results on this dataset have demonstrated the efficacy of our proposed network. The code and dataset are available from https://github.com/z-x-yang/NS-Outpainting.	['Jian Dong', 'Zongxin Yang', 'Yi Yang', 'Ping Liu', 'Shuicheng Yan']	2019-12-29	very-long-natural-scenery-image-prediction-by	http://openaccess.thecvf.com/content_ICCV_2019/html/Yang_Very_Long_Natural_Scenery_Image_Prediction_by_Outpainting_ICCV_2019_paper.html	http://openaccess.thecvf.com/content_ICCV_2019/papers/Yang_Very_Long_Natural_Scenery_Image_Prediction_by_Outpainting_ICCV_2019_paper.pdf	iccv-2019-10	['image-outpainting']	['computer-vision']	[ 3.34370375e-01 -1.09486863e-01 -3.98025848e-02 -2.51006842e-01 -4.65795010e-01 -2.26554245e-01 1.57237679e-01 -4.20999736e-01 -1.27245709e-01 9.08468008e-01 2.66293347e-01 1.26471922e-01 3.55829477e-01 -8.27174962e-01 -8.60637903e-01 -5.27393103e-01 3.85605127e-01 -3.51715200e-02 3.69104534e-01 -2.56096482e-01 2.49038577e-01 2.32797697e-01 -1.38071573e+00 4.31960583e-01 1.04959297e+00 9.37267959e-01 7.34454513e-01 4.79612529e-01 -9.94328037e-02 9.82942343e-01 -6.30849600e-01 -2.97144949e-01 3.50201398e-01 -8.11465621e-01 -5.30198276e-01 2.47034192e-01 2.39065856e-01 -7.86837101e-01 -5.63719451e-01 1.03996801e+00 6.34573996e-01 4.87320647e-02 2.71882564e-01 -1.06546390e+00 -1.05562460e+00 6.18966162e-01 -8.90783846e-01 3.88194211e-02 2.02806801e-01 4.13855910e-01 6.05434358e-01 -8.10200155e-01 6.56022251e-01 1.32276762e+00 3.48783612e-01 7.07625270e-01 -8.93720925e-01 -8.04586828e-01 1.30305350e-01 1.82211965e-01 -1.42445195e+00 -4.69336063e-01 9.24529195e-01 -1.00293912e-01 4.48676884e-01 1.78074673e-01 5.53391159e-01 1.01671135e+00 2.36091450e-01 9.01106596e-01 8.92354250e-01 -2.76790679e-01 2.54047345e-02 1.45121932e-01 -5.53222120e-01 4.82737839e-01 -4.41401117e-02 2.41830051e-02 -3.29354763e-01 2.99278796e-01 1.08805037e+00 2.60214090e-01 -5.19508481e-01 2.16747001e-02 -1.27097499e+00 6.30950034e-01 6.71003640e-01 2.57865787e-01 -2.56003261e-01 4.19685334e-01 3.30574393e-01 1.71332374e-01 5.84287643e-01 1.45815492e-01 -1.68617696e-01 -8.44698399e-03 -1.01431942e+00 2.41503015e-01 1.95266485e-01 1.25865710e+00 6.56326056e-01 2.25619212e-01 -3.35069984e-01 1.03299534e+00 3.09984386e-02 4.40821201e-01 5.71951926e-01 -9.31613445e-01 7.39369571e-01 2.65730113e-01 8.03125277e-02 -1.12875688e+00 1.53126180e-01 -4.38823760e-01 -1.20696509e+00 1.77933127e-02 -1.30991593e-01 -3.26878875e-01 -8.36869836e-01 1.77626324e+00 1.60047963e-01 3.05576295e-01 -1.10161416e-01 1.01535082e+00 9.32639182e-01 1.24434853e+00 -6.47351071e-02 -2.20172480e-01 1.10734129e+00 -1.48332071e+00 -8.77209663e-01 -3.37535501e-01 1.95541248e-01 -1.01859236e+00 1.15671158e+00 1.05853282e-01 -1.39426208e+00 -8.96040380e-01 -1.06374323e+00 -2.86003947e-01 1.10342704e-01 3.35471272e-01 3.34532589e-01 8.18225667e-02 -9.94811952e-01 5.24881244e-01 -4.89336759e-01 -1.26409099e-01 6.06814027e-01 1.08311307e-02 -1.86804369e-01 -2.85887688e-01 -1.18547118e+00 6.03313446e-01 6.06702983e-01 2.23189920e-01 -9.03683305e-01 -6.24843776e-01 -7.72384703e-01 1.42610967e-01 1.43291876e-01 -6.48831069e-01 1.26849365e+00 -1.33464968e+00 -1.54305637e+00 4.27268714e-01 -1.64558649e-01 -1.81410626e-01 7.46269524e-01 -2.22115189e-01 -3.06096733e-01 4.20907699e-02 2.88051009e-01 1.09122944e+00 8.27363193e-01 -1.40226042e+00 -5.56456387e-01 -2.60081887e-02 -2.22185835e-01 3.49332184e-01 -3.45665365e-01 -9.72970054e-02 -7.60840416e-01 -1.11753547e+00 -1.46409720e-01 -7.92952001e-01 -2.84762651e-01 2.22666219e-01 -4.65448171e-01 2.06071392e-01 1.04311121e+00 -9.05618131e-01 1.17460787e+00 -2.31646037e+00 9.52448100e-02 -2.40129322e-01 1.18812084e-01 4.84308153e-01 -3.70906264e-01 5.71939826e-01 -1.65323138e-01 8.74339938e-02 -4.73500401e-01 -3.71568054e-01 -4.62591082e-01 1.17368080e-01 -5.80075085e-01 1.13802433e-01 3.76814753e-01 1.04089057e+00 -7.10979581e-01 -5.49814582e-01 1.65699854e-01 4.79952186e-01 -5.49601436e-01 4.83120352e-01 -4.48527157e-01 6.41063094e-01 -4.94758993e-01 4.21191275e-01 1.03402710e+00 -2.58054584e-01 -2.11886153e-01 -1.63483813e-01 -5.07106707e-02 -5.48873767e-02 -1.02587652e+00 2.00269651e+00 -4.82891470e-01 6.09992385e-01 -4.04119194e-02 -6.30328298e-01 1.02681530e+00 1.24457598e-01 1.61440983e-01 -9.81799603e-01 1.07358284e-01 1.83862418e-01 -1.77491486e-01 -5.56945264e-01 5.07534087e-01 -6.37489036e-02 1.52309150e-01 4.15771127e-01 -5.82726225e-02 -1.01394914e-01 1.80199429e-01 2.68817455e-01 7.54596233e-01 3.37299645e-01 3.45949307e-02 5.22065349e-02 5.28204679e-01 -1.00812957e-01 7.63127625e-01 3.95441890e-01 3.67632471e-02 1.09237790e+00 4.09849048e-01 -4.07793760e-01 -1.37321854e+00 -8.52406740e-01 2.06306666e-01 6.57475710e-01 5.35532832e-01 -3.20570290e-01 -8.21010768e-01 -4.08280849e-01 -3.78593683e-01 6.13249600e-01 -4.40870792e-01 -1.65787503e-01 -7.13228106e-01 -3.84972632e-01 4.31257963e-01 3.96990955e-01 1.05395126e+00 -1.36165655e+00 -4.10133570e-01 2.95877218e-01 -5.05524457e-01 -1.01873195e+00 -8.22274804e-01 -4.50861335e-01 -8.17223787e-01 -6.80398166e-01 -1.21898377e+00 -1.15223622e+00 7.95999825e-01 4.85193968e-01 1.00159788e+00 3.34367782e-01 -3.10865909e-01 -3.59565914e-01 -4.69614327e-01 -2.01439336e-01 -4.42451358e-01 8.72956440e-02 -4.43801284e-01 -2.34087240e-02 -2.92038888e-01 -8.07169974e-01 -9.24032211e-01 3.74190867e-01 -1.32742095e+00 7.17107654e-01 8.22107852e-01 8.60184669e-01 6.30046487e-01 2.58183390e-01 6.06721103e-01 -7.65337825e-01 7.06496239e-01 -5.15650272e-01 -4.94131625e-01 2.23028868e-01 -2.77645230e-01 -5.12202308e-02 1.10289848e+00 -4.18559730e-01 -1.25391209e+00 -1.30584359e-03 -3.09604406e-01 -5.33966780e-01 -7.58864954e-02 2.10441768e-01 -3.60453784e-01 2.15217486e-01 3.43822390e-01 6.86252832e-01 1.85401123e-02 -5.71197748e-01 3.60546678e-01 6.72354758e-01 5.99952638e-01 -4.83888030e-01 8.09118807e-01 3.32465589e-01 -2.98846483e-01 -4.73861307e-01 -5.50678432e-01 2.13588446e-01 -2.86811978e-01 -1.82984367e-01 7.64306605e-01 -1.17206931e+00 -3.85424882e-01 6.88711345e-01 -1.38330495e+00 -3.70700777e-01 -2.48324037e-01 2.33731419e-01 -4.86510396e-01 5.15655637e-01 -8.28973234e-01 -4.75613654e-01 -5.51961780e-01 -1.21611321e+00 9.62124348e-01 4.70636457e-01 1.34882569e-01 -5.73472440e-01 -3.51851992e-02 2.23349482e-01 5.74261069e-01 2.93620288e-01 8.06086242e-01 2.50479192e-01 -7.61372447e-01 1.35049611e-01 -5.08576095e-01 4.58072573e-01 3.50264281e-01 4.59566265e-02 -6.78223729e-01 -3.76307219e-01 9.93217081e-02 -4.36940610e-01 9.00936782e-01 1.20107897e-01 1.47053707e+00 -4.85682577e-01 -1.39452145e-01 6.90620184e-01 1.60232115e+00 3.53680968e-01 9.97124076e-01 2.24341542e-01 7.12456882e-01 4.59772736e-01 6.79844797e-01 5.35780787e-01 1.63972616e-01 6.62504375e-01 4.54504400e-01 -3.86236399e-01 -4.30490255e-01 -8.04998338e-01 3.70021731e-01 9.72662389e-01 1.77404851e-01 -5.25124252e-01 -5.28895736e-01 5.76770127e-01 -1.99819338e+00 -1.14655352e+00 -6.72189146e-02 1.81103957e+00 1.01184475e+00 2.60583987e-03 -1.72115013e-01 -1.82194024e-01 9.00170684e-01 3.47440034e-01 -7.42020369e-01 -2.59821892e-01 -2.42795512e-01 2.21152045e-02 2.69564807e-01 3.46383631e-01 -7.72459686e-01 1.07178140e+00 5.54896545e+00 1.32661724e+00 -1.28256416e+00 9.48258489e-02 1.16537428e+00 -2.21824467e-01 -4.27667975e-01 -3.14679113e-03 -5.61380148e-01 1.01841211e+00 5.07614970e-01 4.96176444e-03 4.93515074e-01 7.50728965e-01 4.55144584e-01 -1.51731893e-01 -6.96031451e-01 1.07445848e+00 8.75552893e-02 -1.58786762e+00 3.15187395e-01 -3.21513325e-01 9.76117671e-01 -2.64046520e-01 1.05307728e-01 7.56727755e-02 5.97385690e-02 -1.10577691e+00 9.50552285e-01 3.83262753e-01 1.03697300e+00 -9.01922107e-01 5.45244455e-01 4.86053079e-01 -1.16277349e+00 4.76054214e-02 -5.88142872e-01 -3.13508548e-02 3.25709134e-01 6.78840697e-01 -3.47646922e-01 5.18269718e-01 6.35573268e-01 9.37570393e-01 -6.20884418e-01 1.04935789e+00 -4.16422248e-01 3.87399673e-01 -6.46915808e-02 1.90424800e-01 1.85978323e-01 -2.70871818e-01 2.64426857e-01 1.05737245e+00 6.20145500e-01 1.15112364e-01 -1.33218914e-01 1.13902545e+00 -2.96797246e-01 5.89835159e-02 -6.37298524e-01 2.14815289e-01 4.98728514e-01 1.21335518e+00 -5.88683665e-01 -3.27285647e-01 -2.28015840e-01 1.32211065e+00 3.40854585e-01 3.28244150e-01 -1.14588773e+00 -5.75553656e-01 4.69113767e-01 1.56297550e-01 3.39970917e-01 -1.13529138e-01 -1.44065842e-01 -1.24725509e+00 4.14276183e-01 -9.55490589e-01 -3.46306786e-02 -1.10926533e+00 -1.06935167e+00 8.38455677e-01 -1.91661179e-01 -1.54554594e+00 1.57489143e-02 -1.16385058e-01 -8.41760337e-01 1.00678265e+00 -1.43713140e+00 -1.22807014e+00 -6.39477193e-01 6.39468610e-01 9.03711796e-01 -9.89342034e-02 4.19195771e-01 5.28946877e-01 -7.22809613e-01 5.36895871e-01 1.65698171e-01 5.93045615e-02 7.68644035e-01 -6.82312727e-01 5.19866467e-01 1.03744149e+00 -1.82604745e-01 2.57569939e-01 5.11426330e-01 -6.98156416e-01 -1.12234902e+00 -1.44977701e+00 5.03419995e-01 1.63044497e-01 3.35098505e-02 -4.21173662e-01 -8.36772203e-01 4.86969769e-01 6.64165914e-01 -4.29926161e-03 1.59525111e-01 -7.71381795e-01 -1.44873574e-01 -2.01978385e-01 -1.11818397e+00 7.86296964e-01 1.10902333e+00 -1.00887038e-01 -1.20852128e-01 3.59055132e-01 1.03606236e+00 -5.06338477e-01 -5.18568754e-01 4.37498122e-01 2.27752090e-01 -1.18347776e+00 7.71016538e-01 -1.31844878e-01 1.23364925e+00 -6.64925992e-01 -6.98699476e-03 -1.36280560e+00 -4.38666910e-01 -6.41332746e-01 1.44385248e-01 1.50027061e+00 3.10351729e-01 -3.63537312e-01 8.41650009e-01 2.30706915e-01 -8.48782063e-02 -1.02579486e+00 -4.56566066e-01 -6.41574502e-01 -4.69107777e-02 2.32730974e-02 8.53053868e-01 6.70568228e-01 -5.15492499e-01 4.12173748e-01 -1.00051129e+00 -7.96288773e-02 4.14787829e-01 3.94922704e-01 7.93100297e-01 -3.79503787e-01 -4.97237742e-01 -1.91286311e-01 -1.61049515e-01 -1.45865250e+00 -6.02944605e-02 -5.89193523e-01 1.38870537e-01 -1.55908775e+00 3.90521407e-01 -4.65921313e-01 9.02571157e-02 3.70607972e-01 -2.80260324e-01 4.12359089e-01 4.04999882e-01 4.19637680e-01 -4.25855845e-01 1.09736431e+00 1.86115837e+00 -1.35578439e-01 -4.13821302e-02 -3.01536351e-01 -8.37145925e-01 4.57632452e-01 1.00276768e+00 -4.43696260e-01 -7.49034226e-01 -9.82762575e-01 -7.74413394e-03 4.47606593e-01 2.25442216e-01 -1.12640560e+00 6.45351708e-02 -3.34489316e-01 7.28008032e-01 -6.23850644e-01 3.26385438e-01 -7.12231219e-01 5.25321841e-01 4.57270175e-01 -3.81841630e-01 2.91833043e-01 2.33101830e-01 4.43066239e-01 -5.75772941e-01 -8.86084363e-02 9.90839720e-01 -2.27330372e-01 -7.63564289e-01 5.02379656e-01 6.25263974e-02 9.17730927e-02 1.24095643e+00 -4.65820245e-02 -3.44860643e-01 -6.24585032e-01 -2.77338028e-01 2.86813796e-01 6.30226731e-01 6.33295178e-01 9.68100846e-01 -1.54387569e+00 -9.32594240e-01 2.74580628e-01 -5.79504408e-02 2.88333327e-01 6.27459109e-01 4.04345095e-01 -1.03466129e+00 1.93333894e-01 -5.69219291e-01 -2.96337605e-01 -9.81707215e-01 5.51653802e-01 1.44948617e-01 -1.31642044e-01 -6.26261115e-01 8.23519349e-01 5.39715648e-01 -2.02533811e-01 4.84714992e-02 -6.98440149e-02 1.06827512e-01 -3.80760431e-01 7.06287384e-01 7.41739497e-02 -2.63661414e-01 -4.67596322e-01 3.93627435e-02 4.66519773e-01 -3.11110258e-01 -1.94913726e-02 1.36951506e+00 -2.83306003e-01 -2.09287524e-01 6.33226857e-02 1.18031740e+00 -3.92587855e-02 -1.60327816e+00 -9.34057534e-02 -6.51458442e-01 -8.30580354e-01 -2.28838250e-01 -6.17210090e-01 -1.53361702e+00 8.46553802e-01 5.84133685e-01 -1.75320581e-01 1.39748228e+00 -3.57183695e-01 1.33292556e+00 -1.38462156e-01 2.76519090e-01 -8.94237518e-01 2.07273543e-01 2.77649909e-01 1.16441739e+00 -1.02256584e+00 -6.46928623e-02 -5.29611826e-01 -7.63790071e-01 9.12782729e-01 1.04964125e+00 -3.77979785e-01 2.56196886e-01 1.61331251e-01 6.66783154e-02 2.94089258e-01 -7.52475560e-01 1.42274916e-01 -1.41412467e-01 4.51791972e-01 4.24298793e-01 -1.75951451e-01 -3.87905687e-01 3.49168092e-01 -1.86144203e-01 2.32255653e-01 6.08651638e-01 7.85497665e-01 -2.83167422e-01 -1.23561108e+00 -2.84966886e-01 3.03012192e-01 -4.07426596e-01 -1.79452345e-01 -1.61344856e-01 4.93928313e-01 3.15490156e-01 8.97211909e-01 -2.09766757e-02 -3.91551524e-01 1.88989758e-01 -4.89901930e-01 2.45782062e-01 -4.94698375e-01 -3.40542644e-01 7.11935281e-04 -2.13932574e-01 -6.10448837e-01 -2.06176132e-01 -2.30415270e-01 -1.06163478e+00 -4.62259293e-01 -1.77746639e-01 8.05716962e-02 3.89823437e-01 4.55859840e-01 6.13198221e-01 6.68008327e-01 8.66330624e-01 -7.50984311e-01 -3.28424394e-01 -9.29975092e-01 -4.71320122e-01 5.75808287e-01 2.45634690e-01 -1.37644216e-01 -2.04737689e-02 2.08811998e-01]	[11.396196365356445, -1.0075087547302246]
79946c35-eba2-4ab4-bd7c-948524ec5ae3	global-deep-learning-methods-for	1812.04103	null	https://arxiv.org/abs/1812.04103v2	https://arxiv.org/pdf/1812.04103v2.pdf	Non-local U-Net for Biomedical Image Segmentation	Deep learning has shown its great promise in various biomedical image segmentation tasks. Existing models are typically based on U-Net and rely on an encoder-decoder architecture with stacked local operators to aggregate long-range information gradually. However, only using the local operators limits the efficiency and effectiveness. In this work, we propose the non-local U-Nets, which are equipped with flexible global aggregation blocks, for biomedical image segmentation. These blocks can be inserted into U-Net as size-preserving processes, as well as down-sampling and up-sampling layers. We perform thorough experiments on the 3D multimodality isointense infant brain MR image segmentation task to evaluate the non-local U-Nets. Results show that our proposed models achieve top performances with fewer parameters and faster computation.	['Shuiwang Ji', 'Zhengyang Wang', 'Dinggang Shen', 'Na Zou']	2018-12-10	null	null	null	null	['brain-image-segmentation']	['medical']	[ 2.46946588e-01 9.47231054e-03 -1.91673115e-01 -5.76459587e-01 -7.10538208e-01 4.66356091e-02 1.28206670e-01 7.39009753e-02 -5.97637892e-01 6.17463768e-01 1.39310345e-01 -3.06776315e-01 7.37948529e-03 -6.60484910e-01 -9.28545296e-01 -7.81319439e-01 -3.33163083e-01 4.04057354e-01 5.46848059e-01 1.37060806e-01 7.04384223e-02 4.27173495e-01 -9.11355078e-01 7.63355792e-01 1.10644400e+00 1.17545033e+00 3.04789573e-01 5.16148031e-01 -2.84612656e-01 8.71568382e-01 -3.15262556e-01 -1.51129827e-01 1.84971377e-01 -4.18986976e-01 -9.02635872e-01 -2.43426815e-01 1.46979272e-01 -6.80697381e-01 -3.02057177e-01 1.17532372e+00 9.15132701e-01 -7.58225024e-02 4.91738647e-01 -6.11335695e-01 -7.50134647e-01 9.78316605e-01 -7.69334257e-01 5.28294325e-01 1.05076842e-03 -1.46812201e-01 7.75045991e-01 -6.61602020e-01 4.96244222e-01 1.16193235e+00 7.79115021e-01 6.69059098e-01 -1.10913527e+00 -6.27399683e-01 1.41357139e-01 1.71010509e-01 -1.14991426e+00 -2.24953398e-01 5.59466660e-01 -2.04544455e-01 1.17404556e+00 1.75793126e-01 6.00486755e-01 5.99758625e-01 6.35919988e-01 1.28769433e+00 8.96619141e-01 -6.92898706e-02 5.34268729e-02 -4.90828782e-01 4.02584434e-01 7.52298295e-01 3.63264307e-02 -1.35279968e-01 -4.07885671e-01 9.26122162e-03 1.23297095e+00 2.38018736e-01 -2.24370390e-01 -2.27013230e-01 -1.17122173e+00 6.11623824e-01 9.20450747e-01 4.83841658e-01 -4.32875246e-01 1.51773125e-01 6.18066549e-01 1.88664943e-01 7.28074729e-01 9.91079286e-02 -6.03155315e-01 1.32208973e-01 -1.15560007e+00 -1.17291100e-01 3.00260544e-01 1.06037354e+00 5.40420651e-01 -1.46176845e-01 -4.75144148e-01 1.02693152e+00 7.93446824e-02 7.48399869e-02 7.88707733e-01 -5.13486207e-01 4.98236120e-01 5.93333662e-01 -4.36213285e-01 -6.17145061e-01 -8.58204782e-01 -5.77910066e-01 -1.18174088e+00 -1.35748535e-01 -1.12457396e-02 -4.85360980e-01 -1.42792344e+00 1.56271780e+00 2.73764223e-01 2.48175368e-01 -1.07165113e-01 8.02768052e-01 1.03765547e+00 5.82511365e-01 6.49109483e-02 -1.14285260e-01 1.26541018e+00 -1.28112960e+00 -8.29517007e-01 -1.33344838e-02 7.89363801e-01 -6.03020549e-01 8.22591245e-01 9.59494188e-02 -1.39306390e+00 -4.29815322e-01 -9.47076201e-01 -4.30953175e-01 -2.02626407e-01 6.26467913e-02 7.33432889e-01 5.78208029e-01 -1.43904257e+00 7.10828483e-01 -1.16211712e+00 9.53470767e-02 9.43415880e-01 7.28922725e-01 -1.85812727e-01 1.16131790e-01 -1.23189056e+00 5.30730367e-01 6.36886716e-01 2.62028813e-01 -6.71440005e-01 -6.45853579e-01 -8.41939688e-01 2.04865843e-01 1.81795061e-01 -6.87260449e-01 1.10886288e+00 -6.92816854e-01 -1.46666002e+00 7.04422593e-01 -1.03587888e-01 -7.24838614e-01 5.68128288e-01 -8.71686414e-02 -6.21744245e-02 4.62727755e-01 -6.07143864e-02 1.16522908e+00 5.40096223e-01 -7.69897044e-01 -5.33476353e-01 -5.11986673e-01 2.99642645e-02 2.72976846e-01 -2.49969393e-01 1.59525245e-01 -4.15496051e-01 -8.62112343e-01 5.78573465e-01 -5.76850057e-01 -4.19308364e-01 -3.15791726e-01 -4.42056149e-01 -1.01560749e-01 7.04319715e-01 -7.65694141e-01 1.35013592e+00 -1.81508291e+00 -1.30250603e-01 1.06927179e-01 4.33272064e-01 2.20442116e-01 -1.73371598e-01 -1.06310837e-01 -1.79872110e-01 1.29799634e-01 -4.24247414e-01 -1.34712696e-01 -2.46072009e-01 3.22191678e-02 2.48773485e-01 3.27851593e-01 1.47729978e-01 1.27907038e+00 -6.53204024e-01 -5.89716852e-01 1.04270957e-01 4.55831379e-01 -7.74519801e-01 -2.16569752e-01 -4.73468527e-02 4.01019186e-01 -6.15502894e-01 6.94405675e-01 9.06629860e-01 -3.23727727e-01 -4.83130179e-02 -2.68296212e-01 -4.78629544e-02 2.13741228e-01 -6.73247159e-01 1.93580294e+00 -2.83453226e-01 3.89855474e-01 2.97857553e-01 -1.13935769e+00 6.45030737e-01 2.90005654e-01 8.61080527e-01 -9.10549402e-01 3.94413918e-01 3.26110542e-01 1.19487666e-01 -3.38184774e-01 2.57623047e-01 -5.46717420e-02 2.11397856e-01 3.40140730e-01 1.47655949e-01 3.26593786e-01 3.16449851e-01 1.06920383e-03 9.61057723e-01 9.69089195e-03 7.99502283e-02 -7.15306818e-01 6.08639777e-01 -5.01727879e-01 5.34679890e-01 5.91167331e-01 -1.71891764e-01 8.00468683e-01 7.13087201e-01 -6.56486630e-01 -8.83496761e-01 -9.19421315e-01 -5.18246531e-01 1.06216908e+00 8.85737911e-02 -1.89400822e-01 -1.22868860e+00 -6.21017814e-01 -4.67833906e-01 2.01890960e-01 -5.66971123e-01 4.30865288e-02 -8.17804873e-01 -1.26584530e+00 4.70934689e-01 8.32216382e-01 7.95273483e-01 -1.11914968e+00 -7.39908338e-01 4.97158110e-01 -7.50297261e-03 -9.90997314e-01 -8.55922461e-01 3.83554429e-01 -1.39480078e+00 -6.55644357e-01 -1.26239860e+00 -1.20757151e+00 9.88589883e-01 -9.50275138e-02 7.74705648e-01 -8.76364633e-02 -2.42892012e-01 -1.92048252e-01 -1.67929277e-01 -1.60910234e-01 1.36754259e-01 4.32045400e-01 -3.32342148e-01 -2.30867207e-01 1.90369859e-01 -4.95480806e-01 -9.63213265e-01 2.30024368e-01 -1.09158707e+00 3.98995697e-01 7.63487637e-01 1.09481359e+00 8.31313789e-01 -2.77846813e-01 7.68798232e-01 -1.01720655e+00 7.01926351e-01 -1.83776245e-01 -3.24217349e-01 2.19743446e-01 -2.78744072e-01 1.43814266e-01 5.47594309e-01 -3.26268792e-01 -9.96130049e-01 7.16373771e-02 -5.00056744e-01 -2.49141812e-01 1.50949106e-01 4.94505793e-01 1.82791576e-02 -2.89431006e-01 2.69240558e-01 1.06889606e-01 -1.47948086e-01 -5.03951073e-01 1.69381604e-01 6.25666678e-01 2.83590645e-01 -6.38924003e-01 -1.04266547e-01 4.12711680e-01 -1.55553237e-01 -7.59986281e-01 -5.30495524e-01 -2.83982605e-01 -7.07250834e-01 4.86064814e-02 1.21221101e+00 -8.17810535e-01 -5.93670547e-01 7.60540962e-01 -1.16860890e+00 -4.53973681e-01 -1.19435512e-01 4.63483214e-01 -4.94806439e-01 2.57020682e-01 -1.26688170e+00 -2.26896062e-01 -8.19897354e-01 -1.75629961e+00 1.03184426e+00 4.36794937e-01 1.64305940e-01 -9.31731880e-01 -3.51647198e-01 2.09519774e-01 5.45030773e-01 7.42403790e-02 1.02513707e+00 -6.92679405e-01 -6.37687445e-01 -9.44422260e-02 -5.86505175e-01 3.57736737e-01 5.93335479e-02 -5.69690824e-01 -8.07211936e-01 -3.07309717e-01 1.01970285e-01 -2.38822743e-01 1.12535524e+00 1.05564821e+00 1.74789143e+00 -8.39108303e-02 -3.77327740e-01 9.55946028e-01 1.15753615e+00 5.37971854e-01 7.14665055e-01 4.60674912e-02 8.82931709e-01 2.53473014e-01 -1.04097761e-01 2.70925850e-01 4.63992238e-01 9.32875201e-02 1.16580822e-01 -4.76688027e-01 -3.91754471e-02 1.56050310e-01 6.04881868e-02 1.28046906e+00 -8.32937360e-02 -9.84957516e-02 -1.05377328e+00 5.23609161e-01 -1.80699718e+00 -6.19660020e-01 9.20145065e-02 1.89706171e+00 1.00580907e+00 1.97051764e-01 -1.56854153e-01 -3.43926728e-01 6.96256161e-01 2.68450886e-01 -6.43638015e-01 -4.15396631e-01 2.97491662e-02 4.57341790e-01 6.28961265e-01 4.49804932e-01 -1.22850943e+00 8.91296506e-01 6.81823111e+00 1.17721677e+00 -1.21888351e+00 3.14766258e-01 1.40202916e+00 -2.22945422e-01 -2.88724393e-01 -5.85418701e-01 -6.34238660e-01 4.36938733e-01 6.57314956e-01 3.84390295e-01 1.12267524e-01 5.33436000e-01 -1.09751627e-01 -9.85805020e-02 -1.02216148e+00 9.79028881e-01 -1.55840456e-01 -1.53299296e+00 2.88187921e-01 -1.73595279e-01 1.02042544e+00 3.67072880e-01 5.38970232e-02 1.08400576e-01 3.16078290e-02 -1.12601769e+00 5.08569717e-01 3.62387985e-01 7.78762043e-01 -8.96103859e-01 8.66234183e-01 2.39585951e-01 -1.20343208e+00 8.63008425e-02 -4.63839173e-01 2.72271305e-01 2.26601124e-01 5.17632008e-01 -4.03001219e-01 4.97143447e-01 7.92294621e-01 5.86138189e-01 -2.19810128e-01 1.02633011e+00 1.69676319e-01 3.20344657e-01 -4.42935497e-01 -1.21654823e-01 6.15868747e-01 -3.79397988e-01 2.31663883e-01 1.25601375e+00 2.51584411e-01 3.41885775e-01 2.42479235e-01 7.49801040e-01 -3.46386880e-01 2.64661521e-01 -2.04806879e-01 1.70554712e-01 -3.55276428e-02 9.10959601e-01 -1.16181099e+00 -4.39851880e-01 -5.60331166e-01 8.37576985e-01 2.51526445e-01 3.48903090e-01 -8.16232920e-01 -4.54672337e-01 3.67109567e-01 7.23462477e-02 2.69919991e-01 -1.03151001e-01 -7.32902050e-01 -9.88359094e-01 -5.73924966e-02 -6.94402754e-01 3.79715115e-01 -4.63402420e-01 -9.58173096e-01 8.98614109e-01 -5.82417361e-02 -8.19830954e-01 2.30135217e-01 -6.36765480e-01 -4.47780043e-01 6.82908237e-01 -1.50330782e+00 -1.03400600e+00 1.25992373e-01 5.25852144e-01 4.62068945e-01 3.93327326e-02 3.63295823e-01 6.73673987e-01 -6.93416059e-01 6.61269665e-01 1.51984021e-01 3.03588450e-01 3.02003056e-01 -1.10135543e+00 3.35085779e-01 7.43482947e-01 -1.45421579e-01 8.99410784e-01 1.48827970e-01 -7.77101517e-01 -7.71481454e-01 -9.66348886e-01 5.49513221e-01 2.45648265e-01 4.46052074e-01 -2.90762812e-01 -8.81310046e-01 6.86959684e-01 4.76937115e-01 2.84335762e-01 4.28447425e-01 -1.88952520e-01 3.35890383e-01 -1.00567654e-01 -1.20976555e+00 5.87459087e-01 1.15589166e+00 -4.00627196e-01 -3.71756464e-01 4.41225886e-01 8.28701735e-01 -8.70738089e-01 -1.02375269e+00 5.84404588e-01 4.01673585e-01 -8.88714075e-01 1.12646031e+00 -3.30032647e-01 5.67840219e-01 -4.08101603e-02 2.42455676e-01 -1.09255910e+00 -3.16456407e-01 -6.12446308e-01 1.96974948e-01 6.85404360e-01 6.22350276e-01 -7.43845820e-01 8.15797627e-01 5.72648346e-01 -5.52862942e-01 -1.42663920e+00 -1.15713131e+00 -3.47831100e-01 1.76130816e-01 -2.60082334e-01 8.04362476e-01 6.94471776e-01 -9.47553739e-02 2.23686367e-01 -2.22115144e-01 -7.15474561e-02 4.54401881e-01 -1.17669255e-01 -4.40315679e-02 -8.33611429e-01 6.46532252e-02 -7.24935949e-01 -2.81627983e-01 -1.56728709e+00 -1.08811758e-01 -1.00260556e+00 7.86070824e-02 -1.72189701e+00 3.99853468e-01 -4.40339714e-01 -6.69516504e-01 5.15209913e-01 -2.38604248e-01 2.45914489e-01 -1.39409333e-01 9.39626247e-02 -5.78133762e-01 5.24180710e-01 1.86079872e+00 -1.63638368e-01 -3.06058764e-01 -1.36434957e-01 -3.06459606e-01 9.13141608e-01 1.06204438e+00 -3.43638688e-01 -5.50627112e-01 -9.04927015e-01 -7.14685097e-02 1.58819973e-01 -6.75289929e-02 -1.10467994e+00 4.31357920e-01 3.03379983e-01 6.16614163e-01 -9.83760059e-01 1.87995601e-02 -5.61993599e-01 -3.99059564e-01 5.49942076e-01 -4.72906440e-01 2.88871467e-01 2.13522211e-01 1.10603750e-01 -4.34631169e-01 -1.99605256e-01 9.53296781e-01 -2.31558308e-01 -4.91744041e-01 9.23932731e-01 -2.47418523e-01 -1.02467120e-01 1.09048569e+00 -2.49783188e-01 -9.72690284e-02 1.66412499e-02 -8.99619460e-01 3.07265371e-01 2.98866574e-02 6.65904954e-02 6.57167375e-01 -1.23378122e+00 -4.61110383e-01 4.79177326e-01 -4.33092743e-01 4.28772122e-01 6.49567485e-01 1.22089040e+00 -1.12540305e+00 6.15048766e-01 -4.15318221e-01 -6.86880410e-01 -1.04960859e+00 3.34715247e-01 4.99096036e-01 -5.62526524e-01 -8.44828486e-01 1.26899326e+00 6.45160139e-01 -4.67186600e-01 1.40408620e-01 -1.05140662e+00 -3.48951995e-01 1.03502072e-01 5.69003344e-01 2.98967361e-01 1.25457421e-01 -4.91627395e-01 -3.42794210e-01 4.74310428e-01 -4.16276067e-01 7.87510574e-02 1.38248610e+00 -1.27993584e-01 -5.37920713e-01 9.60469544e-02 1.43140817e+00 -5.06478965e-01 -1.25961995e+00 -2.92304754e-01 -3.14613581e-02 1.38319936e-02 3.63456666e-01 -5.74451685e-01 -1.58764899e+00 1.13002610e+00 6.67798996e-01 1.62674878e-02 1.31343412e+00 -1.47483155e-01 1.36901736e+00 1.83242843e-01 3.70620042e-01 -1.17666566e+00 -1.43134087e-01 6.10441804e-01 6.68651342e-01 -1.00445938e+00 -9.44911763e-02 -2.62119561e-01 -4.51416641e-01 1.14819896e+00 6.39446735e-01 -2.12215587e-01 7.70511806e-01 5.97987115e-01 7.32610598e-02 -2.07371697e-01 -5.94699323e-01 -1.05570763e-01 3.85181993e-01 2.52893209e-01 7.28938699e-01 2.13260695e-01 -5.03154159e-01 5.78739643e-01 1.13502190e-01 1.24071039e-01 7.95876980e-02 8.16640019e-01 -4.86920148e-01 -9.66557562e-01 -1.31219864e-01 9.60462272e-01 -7.73699224e-01 -4.63676035e-01 1.39858380e-01 5.11593401e-01 2.94660091e-01 4.17569816e-01 1.20996691e-01 -2.61573911e-01 2.20619719e-02 -1.13687478e-01 5.51480293e-01 -3.77629250e-01 -6.54918671e-01 3.94001931e-01 -2.76228577e-01 -6.33308113e-01 -4.17715698e-01 -6.17262065e-01 -1.64714313e+00 -5.67243211e-02 -2.28302240e-01 -1.28253162e-01 3.04660767e-01 8.26748431e-01 3.88872683e-01 1.06613922e+00 1.92198798e-01 -6.98044002e-01 -4.14225161e-01 -1.00769103e+00 -5.86273313e-01 2.42300797e-02 4.85483319e-01 -2.90673345e-01 2.62224495e-01 -1.50639221e-01]	[14.562223434448242, -2.614645481109619]
107fa7e6-013a-46a8-ad68-2b83e9d28202	rgb-multispectral-matching-dataset-learning-1	2206.07047	null	https://arxiv.org/abs/2206.07047v1	https://arxiv.org/pdf/2206.07047v1.pdf	RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation	We address the problem of registering synchronized color (RGB) and multi-spectral (MS) images featuring very different resolution by solving stereo matching correspondences. Purposely, we introduce a novel RGB-MS dataset framing 13 different scenes in indoor environments and providing a total of 34 image pairs annotated with semi-dense, high-resolution ground-truth labels in the form of disparity maps. To tackle the task, we propose a deep learning architecture trained in a self-supervised manner by exploiting a further RGB camera, required only during training data acquisition. In this setup, we can conveniently learn cross-modal matching in the absence of ground-truth labels by distilling knowledge from an easier RGB-RGB matching task based on a collection of about 11K unlabeled image triplets. Experiments show that the proposed pipeline sets a good performance bar (1.16 pixels average registration error) for future research on this novel, challenging task.	['Luigi Di Stefano', 'Stefano Mattoccia', 'Samuele Salti', 'Matteo Poggi', 'Pierluigi Zama Ramirez', 'Fabio Tosi']	2022-06-14	rgb-multispectral-matching-dataset-learning	http://openaccess.thecvf.com//content/CVPR2022/html/Tosi_RGB-Multispectral_Matching_Dataset_Learning_Methodology_Evaluation_CVPR_2022_paper.html	http://openaccess.thecvf.com//content/CVPR2022/papers/Tosi_RGB-Multispectral_Matching_Dataset_Learning_Methodology_Evaluation_CVPR_2022_paper.pdf	cvpr-2022-1	['stereo-matching-1']	['computer-vision']	[ 5.19081116e-01 1.46302119e-01 1.92929178e-01 -6.05042100e-01 -1.34818912e+00 -5.61572492e-01 4.49753553e-01 -2.96950024e-02 -7.61642098e-01 5.16712010e-01 -2.14450747e-01 -5.29403165e-02 1.26454324e-01 -6.17936909e-01 -9.99778688e-01 -5.78594625e-01 2.95288861e-01 6.81750715e-01 2.49387309e-01 -2.34538600e-01 1.62988067e-01 5.39333820e-01 -1.84109068e+00 3.15244496e-01 6.23528600e-01 1.15889561e+00 2.69323558e-01 5.02872646e-01 1.00844212e-01 6.83742225e-01 -5.43786623e-02 -4.47584748e-01 8.18062007e-01 -1.89463407e-01 -1.06632733e+00 1.80196822e-01 1.05311275e+00 -3.58485401e-01 -1.84120595e-01 9.83332157e-01 5.54481864e-01 6.71811178e-02 2.47960957e-03 -1.31328380e+00 -1.95548728e-01 7.89605007e-02 -5.84751546e-01 -7.44612515e-02 6.08932078e-01 3.06485474e-01 9.74045157e-01 -6.20345891e-01 5.33329964e-01 8.27415884e-01 7.83978283e-01 3.24658662e-01 -1.29816771e+00 -5.95711291e-01 -1.67654395e-01 1.10068448e-01 -1.51293683e+00 -5.86534977e-01 7.88505614e-01 -3.13865721e-01 9.96451616e-01 1.95802212e-01 7.10393012e-01 8.67546260e-01 -4.46388811e-01 3.56317699e-01 1.55408573e+00 -4.74631965e-01 5.42379282e-02 4.23967615e-02 -1.40850767e-01 7.45646656e-01 7.32558966e-02 1.44619107e-01 -7.53799856e-01 2.47897610e-01 9.55178440e-01 -1.18642129e-01 -2.64626294e-01 -6.70779586e-01 -1.55960679e+00 3.32898647e-01 9.03284550e-01 2.87931681e-01 -9.84228402e-02 2.53058761e-01 1.83270953e-03 2.18880683e-01 2.23299772e-01 2.86196977e-01 -6.89709544e-01 4.62225117e-02 -8.95888150e-01 -1.39805034e-01 3.09598029e-01 1.15330672e+00 1.54373693e+00 -2.62112170e-01 4.30944532e-01 3.69860649e-01 2.82417715e-01 7.32203305e-01 4.09799397e-01 -1.15902543e+00 6.55392170e-01 4.49022114e-01 2.40782484e-01 -8.61229658e-01 -6.81567132e-01 -1.04127251e-01 -7.76702642e-01 2.30500266e-01 6.76611781e-01 1.65133655e-01 -7.96054125e-01 1.59805965e+00 4.51404363e-01 3.85197997e-01 -4.50955965e-02 1.07018661e+00 7.72486031e-01 2.08406121e-01 -3.67048204e-01 1.16052896e-01 1.14769733e+00 -8.77993703e-01 -2.46482238e-01 -3.81232142e-01 3.60442936e-01 -7.38179207e-01 1.16807401e+00 2.57956952e-01 -8.11433256e-01 -6.78739429e-01 -1.04023647e+00 -4.51493829e-01 -4.94356334e-01 1.58224016e-01 7.58813024e-01 5.37110031e-01 -1.43934417e+00 5.16732752e-01 -9.59467351e-01 -4.49018329e-01 1.83255821e-01 5.63811660e-01 -7.76995599e-01 -2.42248163e-01 -7.64777064e-01 8.66442859e-01 3.47087979e-01 3.06135595e-01 -6.38606191e-01 -5.68842828e-01 -1.09305441e+00 -4.84089792e-01 1.33499622e-01 -8.00291479e-01 7.58393168e-01 -1.03445554e+00 -1.51790988e+00 1.61796916e+00 -4.43548709e-02 -6.87835515e-02 5.45769453e-01 -2.28006348e-01 -8.22860450e-02 2.03903750e-01 3.02553207e-01 8.78805161e-01 5.68856835e-01 -1.46750522e+00 -5.80324054e-01 -6.58886433e-01 2.59989858e-01 1.19752206e-01 1.07097421e-02 -2.20002860e-01 -6.51355147e-01 -1.49443612e-01 5.23242474e-01 -1.02562821e+00 -3.55710417e-01 8.61509517e-02 -4.34064031e-01 4.59391713e-01 2.84005642e-01 -5.60697019e-01 3.06342781e-01 -2.00899553e+00 2.12138042e-01 2.48808339e-01 -6.42647967e-02 -4.41422909e-02 -2.05077678e-01 1.38092069e-02 -1.38151422e-01 -3.90462130e-01 -4.63067830e-01 -7.03666627e-01 -1.23128973e-01 3.21063548e-01 -1.01680540e-01 8.56306672e-01 1.37714103e-01 8.76510799e-01 -1.02602196e+00 -5.10976195e-01 5.80418766e-01 5.23226202e-01 -3.97978753e-01 5.35082817e-01 -5.26419654e-03 1.09802461e+00 -7.86797851e-02 8.29763770e-01 8.50027740e-01 -3.24239045e-01 4.24216315e-02 -6.64937019e-01 -1.50487646e-01 1.55614167e-01 -1.54232395e+00 2.80039668e+00 -6.94469631e-01 6.94635868e-01 2.58189123e-02 -8.77550006e-01 7.53122449e-01 -9.55162942e-02 6.88895345e-01 -9.36183214e-01 1.68284878e-01 3.55384171e-01 -4.97610390e-01 -2.53585815e-01 6.22816324e-01 -1.24927893e-01 -4.45906222e-02 5.81199050e-01 2.53960133e-01 -4.23085600e-01 -1.61977157e-01 -2.27540419e-01 8.66679370e-01 4.78576481e-01 1.28973857e-01 7.58144036e-02 6.01119995e-01 4.75294106e-02 3.73724908e-01 5.55303991e-01 -1.03871152e-01 1.00768495e+00 -2.31182680e-01 -6.34464562e-01 -1.12827969e+00 -1.15580392e+00 -1.53410450e-01 6.59756780e-01 5.71717799e-01 -2.63832510e-01 -4.04676497e-01 -2.38853931e-01 -6.28543943e-02 -5.28800562e-02 -5.56282043e-01 2.02429414e-01 -6.27124190e-01 -6.03347778e-01 4.73179400e-01 3.81764412e-01 9.04249549e-01 -6.90487623e-01 -8.35090280e-01 -1.62134603e-01 -4.09792185e-01 -1.64128840e+00 -2.69538723e-02 3.52009922e-01 -7.82798052e-01 -1.25753522e+00 -6.13954544e-01 -6.55492723e-01 6.95429265e-01 4.00317520e-01 1.27371645e+00 -1.03685334e-01 -4.21950012e-01 5.79034626e-01 -1.54119611e-01 1.86539561e-01 2.00526230e-02 1.21414978e-02 2.53500324e-02 1.75012693e-01 1.85118318e-01 -6.69738054e-01 -5.76854587e-01 3.36766243e-01 -7.81364679e-01 2.69050300e-01 5.14849901e-01 6.30910575e-01 9.50405955e-01 -4.12221998e-01 -2.07278177e-01 -5.34488261e-01 -3.36970061e-01 2.71889139e-02 -1.03809941e+00 3.17312509e-01 -3.04367870e-01 6.22584596e-02 3.21827173e-01 4.68183914e-03 -8.66442621e-01 7.58360147e-01 -2.20835075e-01 -4.17699575e-01 -5.49957931e-01 -3.84233035e-02 -2.89722741e-01 -5.99351883e-01 5.78188598e-01 1.51929632e-01 -1.85191184e-02 -5.04138231e-01 7.86368608e-01 5.23858249e-01 1.01956904e+00 -6.34795785e-01 1.11123991e+00 9.31025743e-01 1.95741430e-01 -4.11258727e-01 -9.29386616e-01 -8.14914167e-01 -1.32663631e+00 -1.17338948e-01 9.21178043e-01 -1.44386601e+00 -7.77550638e-01 6.24492705e-01 -1.03115177e+00 -5.66134155e-01 -2.87001818e-01 4.77133393e-01 -9.82441247e-01 3.92831385e-01 -4.64852035e-01 -3.92009765e-01 -7.28362575e-02 -1.15116441e+00 1.70961773e+00 1.93079099e-01 1.89930379e-01 -7.93288112e-01 2.42705390e-01 6.32768512e-01 2.68088549e-01 5.45246124e-01 1.05518207e-01 -3.30857411e-02 -1.10346937e+00 -3.94454636e-02 -5.17355204e-01 -3.65269072e-02 3.18444043e-01 -4.33601797e-01 -1.47251022e+00 -2.16637805e-01 -2.21742734e-01 -7.10475802e-01 7.60971427e-01 2.39694100e-02 9.94145215e-01 3.29962730e-01 1.95769835e-02 1.25255024e+00 1.79261470e+00 -4.84827608e-01 6.31018579e-01 8.64273667e-01 1.10302401e+00 6.15045846e-01 7.59809077e-01 3.99375737e-01 8.60728443e-01 9.39007819e-01 6.50991797e-01 -6.68716848e-01 -1.65804505e-01 -6.22045510e-02 -4.87684496e-02 4.21616375e-01 -8.26436952e-02 4.11467761e-01 -1.06960988e+00 3.69365662e-01 -1.69666052e+00 -7.31834352e-01 -1.55625805e-01 2.27380300e+00 1.04861963e+00 -2.30145767e-01 -4.29199934e-02 2.09704489e-01 4.16714042e-01 1.14540406e-01 -4.44181204e-01 1.98500067e-01 -4.21371043e-01 3.05999309e-01 9.15866137e-01 6.40588343e-01 -1.30142474e+00 9.96701121e-01 5.91836119e+00 2.76015818e-01 -1.23787546e+00 1.01400234e-01 5.07618666e-01 1.24132462e-01 -3.06835681e-01 7.76510164e-02 -5.29555559e-01 1.30295172e-01 7.95545340e-01 3.90193641e-01 5.92184246e-01 5.60278833e-01 -1.48903638e-01 -4.06351179e-01 -1.24198401e+00 1.61600089e+00 2.34137088e-01 -1.34960866e+00 -3.94050390e-01 -1.54390067e-01 7.65490770e-01 5.18470705e-01 5.89494072e-02 -2.61497706e-01 3.79339248e-01 -7.47419298e-01 7.38633335e-01 5.07917523e-01 1.08609021e+00 -2.92790562e-01 5.95309675e-01 1.81201279e-01 -1.20442629e+00 1.30239502e-01 -2.66115248e-01 -5.51947355e-02 1.98764756e-01 4.76035565e-01 -4.36017722e-01 9.52673495e-01 1.03015745e+00 1.14018941e+00 -8.83060396e-01 8.46075833e-01 -2.50807911e-01 -3.35125178e-01 -4.84223813e-01 8.94648075e-01 -7.35094994e-02 -4.15024012e-01 -1.66289017e-01 9.76894557e-01 2.40634263e-01 7.08412379e-02 4.17242199e-02 8.01703513e-01 1.07044578e-01 -2.34110594e-01 -6.50191009e-01 5.34168839e-01 2.04058960e-01 1.43596351e+00 -8.72494280e-01 -1.21375628e-01 -4.60687608e-01 1.34574604e+00 4.48066205e-01 2.60088682e-01 -7.18178034e-01 -3.40721682e-02 7.19258785e-01 -1.83096111e-01 1.59554526e-01 -3.89466941e-01 -3.83850098e-01 -1.47725666e+00 1.38721645e-01 -5.46630919e-01 1.16046950e-01 -1.19914758e+00 -1.17241633e+00 6.51067436e-01 -2.61631191e-01 -1.45924783e+00 -3.52587700e-01 -7.45720744e-01 -8.96737874e-02 9.67102230e-01 -2.18231130e+00 -1.58648634e+00 -9.90791082e-01 1.03914809e+00 -1.01001658e-01 1.68035388e-01 9.10175502e-01 5.57783961e-01 -4.00322735e-01 4.70841676e-01 -5.20064123e-02 1.47856295e-01 9.87870932e-01 -1.23853719e+00 2.82473654e-01 7.83104658e-01 3.76969367e-01 4.46930438e-01 4.63077903e-01 3.53917144e-02 -1.56528282e+00 -1.08213329e+00 7.00312316e-01 -6.66937232e-01 4.33696628e-01 -2.89525092e-01 -5.17587006e-01 7.49672651e-01 -5.96461520e-02 5.35985172e-01 7.52654970e-01 -1.17933512e-01 -4.90439296e-01 -4.78269279e-01 -1.16579008e+00 -9.06845555e-03 1.17445838e+00 -1.11417270e+00 -2.38516346e-01 4.09683138e-01 6.32125199e-01 -9.43132937e-01 -9.84276831e-01 3.38320047e-01 4.04982626e-01 -1.36659825e+00 1.35813606e+00 -1.21364288e-01 2.22577304e-01 -5.94253957e-01 -5.26415884e-01 -8.97975981e-01 2.03325495e-01 -2.41921350e-01 5.16692221e-01 1.17244518e+00 6.41554892e-02 -3.54334772e-01 9.42928433e-01 7.63014197e-01 -1.54414415e-01 -1.74519286e-01 -1.17497206e+00 -4.87688214e-01 -3.72155339e-01 -5.31356335e-01 5.93329310e-01 1.12951350e+00 -3.32977921e-01 -5.51926205e-05 -3.98860633e-01 4.97028768e-01 8.89015794e-01 5.20668030e-01 1.19456506e+00 -1.01453722e+00 -2.58867234e-01 -1.46179810e-01 -7.39150822e-01 -1.03743124e+00 3.07816714e-01 -7.89401531e-01 1.73102170e-01 -1.26828432e+00 1.41549995e-02 -7.82837093e-01 -1.72678918e-01 5.91829360e-01 -8.86197835e-02 8.24732900e-01 2.90962141e-02 2.66033739e-01 -9.22417402e-01 3.30530107e-01 7.96104372e-01 -1.61510751e-01 7.92741701e-02 -2.83490419e-01 -3.26225728e-01 5.68289161e-01 5.15309989e-01 -1.13415547e-01 -2.24931821e-01 -8.16784501e-01 2.41180375e-01 -2.33835378e-03 6.00949645e-01 -1.04378867e+00 4.01168376e-01 -1.83359496e-02 4.08910036e-01 -5.42164207e-01 6.07781589e-01 -1.28572440e+00 4.08081889e-01 1.77110001e-01 -1.15981378e-01 6.71532005e-02 2.50624776e-01 3.73426735e-01 -3.00630093e-01 3.08263481e-01 6.90847278e-01 -2.47460902e-01 -1.09466374e+00 3.34111542e-01 4.26755071e-01 8.48277509e-02 9.53097463e-01 -3.53789419e-01 -1.23006448e-01 -9.80861410e-02 -7.15709388e-01 2.05428451e-02 1.01383519e+00 1.58468470e-01 5.22124887e-01 -1.33629775e+00 -2.03568056e-01 5.36102533e-01 5.58463097e-01 3.44666272e-01 1.91350549e-01 7.82830536e-01 -7.07177579e-01 3.30948710e-01 -6.31499231e-01 -1.05335593e+00 -9.50873613e-01 3.34860861e-01 5.92460811e-01 -2.48320773e-02 -4.61417258e-01 9.84486103e-01 -2.47176543e-01 -7.62476087e-01 2.14348421e-01 -4.20291066e-01 6.48636669e-02 2.76255328e-02 2.71337241e-01 1.15878105e-01 4.78680193e-01 -1.10982394e+00 -5.33539712e-01 1.03429437e+00 5.94786227e-01 -1.71137154e-01 1.36695611e+00 -5.38695335e-01 -3.69745821e-01 5.15729010e-01 1.43912578e+00 -2.29200259e-01 -1.43106592e+00 -5.58533728e-01 2.09812894e-02 -9.40845132e-01 -1.69095176e-04 -4.69182581e-01 -1.21039331e+00 8.14680338e-01 9.75455344e-01 -4.63746130e-01 1.29960883e+00 9.91567373e-02 5.72353721e-01 3.61158550e-01 8.71918857e-01 -8.94043326e-01 7.94824809e-02 3.24388117e-01 4.60798681e-01 -2.00126004e+00 6.84786541e-03 -3.12916309e-01 -3.56754601e-01 1.12027645e+00 5.85594177e-01 -2.03196984e-03 4.52007741e-01 1.73868135e-01 4.01860148e-01 -1.74209058e-01 -1.36733398e-01 -7.52330959e-01 1.84363663e-01 8.97076488e-01 3.54776531e-01 -1.26439437e-01 4.58730340e-01 7.66069889e-02 -3.39584053e-01 -1.62514925e-01 3.02892059e-01 8.12520683e-01 -1.32166848e-01 -1.23401046e+00 -4.10238206e-01 -1.82431191e-01 5.72601594e-02 -1.51419908e-01 -1.70371518e-01 6.73939526e-01 2.58995235e-01 8.91687691e-01 2.62074143e-01 -5.33019722e-01 4.04353142e-01 -2.92611569e-01 8.16007733e-01 -4.14208949e-01 -3.86576951e-01 -3.47656235e-02 -1.44855991e-01 -1.22908783e+00 -1.21137428e+00 -6.01673603e-01 -1.04293311e+00 -1.73920617e-01 -4.33280766e-02 -2.83014953e-01 8.21319938e-01 9.84423399e-01 1.33466303e-01 2.76614726e-01 7.12782443e-01 -1.39416385e+00 -2.57107671e-02 -4.89931494e-01 -5.15809238e-01 6.76790059e-01 6.31233037e-01 -4.79707122e-01 -3.11086953e-01 3.20948333e-01]	[8.193516731262207, -2.2617876529693604]
8c6e8821-26ac-4c36-a1c6-98426d7ae4f3	optimal-activation-of-halting-multi-armed	2304.10302	null	https://arxiv.org/abs/2304.10302v1	https://arxiv.org/pdf/2304.10302v1.pdf	Optimal Activation of Halting Multi-Armed Bandit Models	We study new types of dynamic allocation problems the {\sl Halting Bandit} models. As an application, we obtain new proofs for the classic Gittins index decomposition result and recent results of the authors in `Multi-armed bandits under general depreciation and commitment.'	['Sheldon M. Ross', 'Michael N. Katehakis', 'Wesley Cowan']	2023-04-20	null	null	null	null	['multi-armed-bandits']	['miscellaneous']	[-3.25010747e-01 8.36568996e-02 -1.27462602e+00 -1.96092859e-01 -9.43957329e-01 -1.17313516e+00 -2.53058374e-01 -3.81993473e-01 -6.42238021e-01 1.51359129e+00 1.80068500e-02 -1.02272522e+00 -9.10820186e-01 -5.31335175e-01 -6.18924499e-01 -1.09834242e+00 7.43509233e-02 1.06103790e+00 -4.75893840e-02 -1.06113337e-01 7.14725181e-02 5.12010574e-01 -8.20291758e-01 2.16238946e-01 3.98450464e-01 1.65079272e+00 -2.28480890e-01 9.57339227e-01 5.60236536e-02 5.58650970e-01 -4.59527910e-01 -7.77593613e-01 8.76936316e-01 -1.56808183e-01 -1.02129328e+00 8.90222341e-02 -1.03991941e-01 -4.96853203e-01 -4.70296562e-01 1.02862382e+00 3.60888422e-01 3.38287890e-01 3.88671041e-01 -1.33743083e+00 -7.60868311e-01 1.18756747e+00 -1.29363739e+00 1.12569237e+00 -3.97698395e-02 -1.99198961e-01 1.63869882e+00 2.24874064e-01 8.32877159e-02 1.26874590e+00 6.42958343e-01 4.68022764e-01 -1.49706531e+00 -4.35856938e-01 3.20477784e-01 3.52609694e-01 -5.77164114e-01 -3.39310765e-01 4.39834982e-01 -9.79476273e-02 7.74909377e-01 1.08752549e+00 7.88548052e-01 4.99944955e-01 -5.74305356e-01 1.37138903e+00 1.42725325e+00 -7.96696067e-01 5.43944202e-02 -2.39079669e-01 7.81019330e-01 2.16078505e-01 1.06307876e+00 7.38302991e-02 -3.25745404e-01 -5.69771171e-01 6.61209166e-01 -8.11539665e-02 -2.58326173e-01 -1.02983095e-01 -6.79927230e-01 1.20297492e+00 -1.57096580e-01 -3.55068296e-02 -6.99096859e-01 7.78556228e-01 3.77894253e-01 4.54541087e-01 8.95819366e-01 6.19784035e-02 -6.84316874e-01 -1.10926986e-01 -7.13775098e-01 3.74147922e-01 9.59174335e-01 1.20381141e+00 2.52451539e-01 -6.43312633e-02 -4.35468554e-01 6.84938788e-01 1.08438209e-01 8.97480547e-01 -1.13608744e-02 -1.21082151e+00 1.08823061e+00 -6.08238995e-01 9.76770282e-01 -3.74498397e-01 -5.70228696e-01 -7.14009583e-01 -6.18538857e-01 -4.28703427e-01 5.53102493e-01 -3.52275819e-01 -3.72575253e-01 1.41392028e+00 9.64288414e-02 -1.52562752e-01 -5.27250059e-02 8.65135968e-01 -2.03214377e-01 5.82712948e-01 -5.73645532e-01 -1.08520281e+00 1.09869182e+00 -1.25769567e+00 -9.62814212e-01 -7.52110928e-02 3.36883157e-01 -6.11500740e-01 1.63500249e-01 8.13412547e-01 -1.71779847e+00 2.97397107e-01 -4.21258152e-01 4.44289237e-01 2.15037122e-01 -2.28901491e-01 1.23671651e+00 1.13571429e+00 -1.00134134e+00 2.83733934e-01 -2.90814757e-01 1.53704926e-01 5.14424384e-01 4.88030910e-01 3.64981651e-01 -1.90197080e-01 -7.85852313e-01 6.61927164e-01 5.13898671e-01 3.73474091e-01 -4.76931602e-01 -5.46738684e-01 4.82055768e-02 1.17712691e-01 8.23595464e-01 -6.00985944e-01 1.95426762e+00 -7.25951135e-01 -1.25897241e+00 7.58745432e-01 2.45164096e-01 -7.69068301e-01 7.35194623e-01 -1.26578659e-01 2.15388432e-01 1.46050304e-01 8.05145279e-02 -4.47527826e-01 1.92751750e-01 -8.46043766e-01 -1.13875628e+00 -6.01930201e-01 5.20140111e-01 1.79242820e-01 -4.21578549e-02 1.89500868e-01 1.19476639e-01 -6.94466054e-01 -2.78094411e-03 -1.13537025e+00 -3.11789125e-01 -9.22883630e-01 -4.53660309e-01 -2.79219061e-01 -3.64875793e-01 -5.60036063e-01 1.44202733e+00 -1.74481606e+00 8.82033110e-02 3.55356783e-01 -4.53174263e-01 -2.21309885e-01 1.56804383e-01 4.09672737e-01 -2.29850337e-01 4.43447977e-01 4.19028789e-01 -2.04949230e-01 6.40660346e-01 4.05272305e-01 -7.46806383e-01 8.49575818e-01 -1.04381931e+00 8.15994680e-01 -4.80155081e-01 -1.19592054e-02 -3.51548195e-01 -1.14497960e+00 -5.75488627e-01 -5.98651692e-02 -4.44369465e-01 -3.15259904e-01 -6.07775450e-01 6.91236675e-01 7.16410220e-01 -3.49025249e-01 9.00870785e-02 3.50628912e-01 -2.73312628e-01 2.61775106e-01 -9.32244241e-01 1.13183844e+00 -3.28692436e-01 2.81941950e-01 6.69357300e-01 -1.81396306e+00 -9.81421024e-02 5.55857003e-01 6.61161184e-01 -3.46822172e-01 1.62903681e-01 3.84970099e-01 -2.38940895e-01 -4.32309836e-01 2.50713944e-01 -5.18937349e-01 -3.40721041e-01 1.16483414e+00 -4.54056352e-01 -1.90059140e-01 2.86297441e-01 -4.23548333e-02 7.24431872e-01 -5.04719079e-01 1.02912150e-01 -5.88937461e-01 1.00246239e-02 1.39912516e-01 3.32769215e-01 1.42936087e+00 8.37142467e-02 3.45798023e-02 7.48805761e-01 -7.74946868e-01 -1.19937646e+00 -5.54549277e-01 -4.41430062e-02 2.05198050e+00 -3.06938171e-01 5.18514097e-01 -3.68276656e-01 -1.37392774e-01 4.86507893e-01 8.65700364e-01 -7.72470236e-01 5.02476692e-01 -2.53447950e-01 -1.52706099e+00 3.47633719e-01 4.35204595e-01 4.14197057e-01 -4.07506824e-01 -5.07763326e-01 4.03922707e-01 -5.41931152e-01 -8.16723585e-01 -6.47074461e-01 4.00417447e-01 -8.21750104e-01 -9.19616520e-01 -9.91134107e-01 -1.78036630e-01 1.94247186e-01 6.74459517e-01 9.25689101e-01 -4.94049862e-02 1.87604666e-01 6.55536830e-01 -2.86004961e-01 -9.02952850e-01 1.38123676e-01 9.92199928e-02 1.37623832e-01 -4.58453782e-02 5.95052987e-02 -2.87532479e-01 -9.10073340e-01 4.26237702e-01 -7.76977837e-01 -1.31360874e-01 1.44528940e-01 1.16223478e+00 2.26398245e-01 -3.13744545e-02 5.67153811e-01 -8.08341026e-01 7.61001468e-01 -5.18807769e-01 -1.23905897e+00 6.44320905e-01 -6.15797043e-01 -8.80699009e-02 1.94424570e-01 -4.81133640e-01 -1.04454494e+00 -6.14794135e-01 2.93032587e-01 -7.83417448e-02 6.12514198e-01 7.71560609e-01 4.61893529e-01 4.19719592e-02 3.31378877e-01 2.21086398e-01 -2.79955596e-01 -5.14034092e-01 2.48259827e-01 6.93711579e-01 2.58030504e-01 -1.15582073e+00 1.09838568e-01 6.62936866e-01 9.58603621e-02 3.20772320e-04 -1.45185459e+00 -5.79027772e-01 9.96924117e-02 1.15048150e-02 3.53676379e-01 -3.54293048e-01 -1.54970884e+00 3.46627802e-01 -1.24230838e+00 -5.08690238e-01 -4.55343783e-01 7.81430602e-01 -1.40726447e+00 2.16206804e-01 -5.94869971e-01 -1.64061606e+00 -2.45779812e-01 -5.22996664e-01 3.94901097e-01 1.93933874e-01 5.15776575e-01 -8.67470801e-01 3.94675136e-01 8.60704601e-01 2.59101868e-01 -3.69948000e-02 7.26358414e-01 -7.06033945e-01 -6.63028061e-01 -2.96240628e-01 -2.93871820e-01 3.65738481e-01 -2.76782900e-01 -5.84713519e-01 -4.80063528e-01 -5.33792198e-01 1.44149333e-01 -1.97701395e-01 8.82156253e-01 1.17639232e+00 1.14405715e+00 -1.16053593e+00 -3.39375407e-01 4.68781143e-01 1.68250728e+00 6.02269113e-01 2.45465934e-01 9.41387236e-01 -2.85662204e-01 1.50393307e-01 7.32596397e-01 1.00582910e+00 -8.38947110e-03 5.45137525e-01 5.48644900e-01 1.90896854e-01 9.46015358e-01 3.55198085e-01 -2.76751637e-01 2.32042104e-01 -7.42120445e-01 -5.35773218e-01 -7.15214431e-01 8.97699416e-01 -2.51006222e+00 -1.36412168e+00 1.11614183e-01 2.04872823e+00 9.91030097e-01 -1.03803307e-01 9.54181135e-01 1.20358281e-01 8.72450411e-01 4.24322858e-02 -4.84309554e-01 -8.20183992e-01 -1.96762398e-01 1.32066727e-01 1.53156638e+00 6.19064271e-01 -7.04570055e-01 6.14713550e-01 7.94858885e+00 1.00577712e+00 -2.32373178e-01 5.06883681e-01 1.13043427e+00 -8.45449626e-01 -4.03255194e-01 -2.21249104e-01 -8.91764879e-01 4.49996740e-01 9.64345634e-01 -7.76191175e-01 9.10917878e-01 8.85924339e-01 1.46995321e-01 -3.37144345e-01 -6.30262256e-01 1.12065125e+00 -2.14023024e-01 -1.42575586e+00 -6.18180513e-01 3.67004097e-01 1.02054250e+00 -2.73851842e-01 3.39820594e-01 -7.99488835e-03 1.12237000e+00 -5.08180797e-01 8.47129583e-01 4.23627108e-01 5.22302032e-01 -1.15155995e+00 5.95350027e-01 4.20880884e-01 -3.69622290e-01 -8.40883911e-01 -5.67572892e-01 -3.49861264e-01 3.62773627e-01 4.33684260e-01 -3.94439816e-01 5.73140860e-01 5.09911895e-01 -3.10150772e-01 5.50282776e-01 1.56339478e+00 1.36646301e-01 7.80522168e-01 -8.23936462e-01 -1.62008256e-01 6.35161936e-01 -6.69555843e-01 3.32506776e-01 8.97669613e-01 3.07583123e-01 1.02036357e+00 -7.49625638e-02 3.02408844e-01 1.13496825e-01 -1.22246474e-01 -2.54873216e-01 7.91819915e-02 8.13438892e-02 5.08357763e-01 -8.07607889e-01 -3.24906796e-01 -3.54463607e-01 3.91454637e-01 -4.33442071e-02 4.39112157e-01 -9.45242524e-01 6.62533119e-02 4.66845423e-01 -2.26399288e-01 7.39254415e-01 -1.68457612e-01 -5.89849651e-01 -9.36831057e-01 -9.49181169e-02 -4.04330552e-01 1.07569444e+00 -5.18899560e-01 -1.15434015e+00 -1.10054515e-01 5.89860260e-01 -3.64944130e-01 -2.49880224e-01 -5.85906029e-01 -1.28047496e-01 7.77860463e-01 -1.53634048e+00 -9.57887948e-01 9.19333518e-01 6.12507403e-01 4.66678947e-01 -7.55218267e-02 3.57840687e-01 4.99944463e-02 -6.13950968e-01 3.84764552e-01 1.08153641e+00 -3.00005227e-01 -1.75850630e-01 -1.21612883e+00 -1.67006701e-01 7.32903540e-01 -1.12589292e-01 2.71178663e-01 1.07622755e+00 -2.33592112e-02 -1.35744274e+00 -3.76291156e-01 6.89708143e-02 1.64988071e-01 1.26149821e+00 1.97905868e-01 1.58755295e-02 1.28890789e+00 4.15775090e-01 -3.89400303e-01 9.58451152e-01 4.11877096e-01 -1.01035260e-01 -4.55810964e-01 -1.00447106e+00 -4.10922319e-02 9.97108102e-01 7.82268867e-02 -4.70511973e-01 1.00747359e+00 7.13711619e-01 -3.65545273e-01 -7.03902304e-01 6.95866570e-02 9.21564937e-01 -7.52360702e-01 9.04745102e-01 -1.14131272e+00 -2.28433982e-01 7.83507764e-01 -3.11440915e-01 -1.22797811e+00 -6.83870196e-01 -1.39373279e+00 -5.87007515e-02 6.99191034e-01 5.40340364e-01 -9.49057639e-01 8.27656031e-01 9.15245831e-01 -6.49300963e-02 -4.76748973e-01 -1.71116853e+00 -1.24119997e+00 3.08799744e-01 -3.95760238e-01 6.35649383e-01 8.27303231e-01 4.68990654e-01 -2.45766297e-01 -8.55443776e-01 -1.06205635e-01 7.53619015e-01 5.60507715e-01 2.37061188e-01 -7.43538618e-01 -9.34734285e-01 -7.30957031e-01 4.84975755e-01 -1.45243728e+00 2.23464921e-01 -4.66295213e-01 -9.53716189e-02 -1.27709162e+00 3.94815654e-01 -7.85651624e-01 -7.30807543e-01 5.51130831e-01 3.87110442e-01 2.00073048e-01 4.25064176e-01 1.69114098e-01 -8.33137691e-01 -2.27521002e-01 9.39843059e-01 -4.14951295e-01 3.16242985e-02 1.11398458e+00 -1.01665235e+00 1.22235760e-01 8.76575589e-01 -5.52843869e-01 -2.83105552e-01 -6.86759591e-01 1.05445850e+00 8.60622227e-01 -5.35048451e-03 -5.39975939e-03 2.08080947e-01 -1.02040303e+00 -4.91575748e-01 -1.03988314e+00 2.25756809e-01 -7.12678134e-01 4.27005202e-01 6.67025328e-01 -3.02520186e-01 2.66547501e-01 3.29306334e-01 8.37312043e-01 4.20994878e-01 -8.24935853e-01 6.74135387e-01 -5.50998747e-01 3.04656625e-01 3.11162949e-01 -4.69191551e-01 -9.37299151e-03 9.42007184e-01 -1.52403358e-02 -6.07424319e-01 -7.22443998e-01 -1.14710176e+00 4.71419334e-01 -1.13039844e-01 -4.72550571e-01 -1.70156918e-02 -1.26919937e+00 -7.01543927e-01 -5.01031458e-01 -6.52243912e-01 -2.69269526e-01 1.57560036e-01 1.19703519e+00 -5.30527353e-01 1.31076658e+00 1.52610302e-01 -1.39471367e-01 -1.22144008e+00 8.93115699e-01 1.87441602e-01 -5.94072104e-01 1.71626806e-01 9.29088354e-01 -9.04550552e-02 5.90651453e-01 3.83625515e-02 -1.79158464e-01 3.46991658e-01 5.18706977e-01 4.45891738e-01 1.02151251e+00 -3.32305208e-02 1.62061781e-01 2.83630681e-03 -1.77174015e-03 -1.51875108e-01 -7.81090319e-01 1.99934185e+00 -5.70423245e-01 -5.76775014e-01 5.25144696e-01 5.77822804e-01 -2.63904452e-01 -7.28571057e-01 -4.60722446e-01 9.09807980e-02 -8.80234599e-01 3.59822670e-03 -6.40725195e-01 -1.02758789e+00 2.67453730e-01 -1.72900986e-02 1.28865385e+00 1.05693853e+00 7.54903778e-02 4.34210032e-01 4.63776290e-01 8.12095284e-01 -1.42234373e+00 -3.09080899e-01 2.17820644e-01 9.86497879e-01 -6.72860265e-01 3.09928000e-01 -6.48136660e-02 -2.40778551e-01 8.61927211e-01 -2.72946656e-01 -5.85772358e-02 6.76020086e-01 -8.90242904e-02 -6.41769409e-01 1.60848811e-01 -9.81141746e-01 -3.97997171e-01 -1.51096672e-01 2.40461409e-01 -2.25900784e-01 3.16826552e-01 -1.00829542e+00 8.20061862e-01 -3.82426292e-01 4.86632623e-02 8.27740252e-01 8.95811677e-01 -5.36620557e-01 -8.50210726e-01 -8.73921096e-01 6.30607247e-01 -1.18361366e+00 -1.58027843e-01 4.40017274e-03 5.57195127e-01 -5.54999411e-01 7.70636141e-01 2.04504039e-02 5.72920501e-01 1.14929788e-01 1.87986884e-02 9.77559209e-01 -4.31165576e-01 -1.69474393e-01 5.51467061e-01 3.17306101e-01 2.38443181e-01 -6.96208835e-01 -1.00806725e+00 -2.08481029e-01 -7.57656038e-01 -1.08513331e+00 7.95744121e-01 4.74305481e-01 8.21885407e-01 -4.35659677e-01 7.40251970e-03 1.03604388e+00 -3.85320008e-01 -1.14103973e+00 -9.74225104e-01 -1.23662031e+00 9.74884350e-03 5.02589226e-01 -3.09464067e-01 -6.13139451e-01 -2.48356327e-01]	[4.5008440017700195, 3.2752442359924316]
fe94ed9c-2de1-4e6f-a328-5dc2c223a9cd	high-performance-neural-networks-for-visual	1102.0183	null	https://arxiv.org/abs/1102.0183v1	https://arxiv.org/pdf/1102.0183v1.pdf	High-Performance Neural Networks for Visual Object Classification	We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants. Our feature extractors are neither carefully designed nor pre-wired, but rather learned in a supervised way. Our deep hierarchical architectures achieve the best published results on benchmarks for object classification (NORB, CIFAR10) and handwritten digit recognition (MNIST), with error rates of 2.53%, 19.51%, 0.35%, respectively. Deep nets trained by simple back-propagation perform better than more shallow ones. Learning is surprisingly rapid. NORB is completely trained within five epochs. Test error rates on MNIST drop to 2.42%, 0.97% and 0.48% after 1, 3 and 17 epochs, respectively.	['Jürgen Schmidhuber', 'Luca M. Gambardella', 'Jonathan Masci', 'Ueli Meier', 'Dan C. Cireşan']	2011-02-01	null	null	null	null	['handwritten-digit-recognition']	['computer-vision']	[-1.70872375e-01 -8.83546695e-02 1.27216682e-01 -4.34785724e-01 -2.42387652e-01 -6.44339979e-01 6.31908119e-01 2.77137220e-01 -8.24553668e-01 8.46189141e-01 -2.36962020e-01 -3.89793158e-01 6.14765584e-02 -9.23205793e-01 -8.31558824e-01 -6.84034646e-01 -2.99695283e-01 4.09940481e-01 4.25667614e-01 -1.50155216e-01 2.37750202e-01 7.68670797e-01 -1.34803307e+00 5.69926322e-01 -1.34658348e-02 1.51591337e+00 -3.62116218e-01 1.26717436e+00 2.82649517e-01 1.20298195e+00 -7.05665469e-01 -5.14106929e-01 3.15598667e-01 2.00090244e-01 -9.69004691e-01 -9.81657952e-02 3.46136719e-01 -5.24271607e-01 -5.81410408e-01 7.61463225e-01 5.02685547e-01 -8.97365883e-02 6.53141022e-01 -9.45077419e-01 -5.78803182e-01 6.79542005e-01 -4.34919268e-01 2.29852259e-01 -2.91408986e-01 3.02192688e-01 7.22445011e-01 -9.66107726e-01 3.61625582e-01 1.02891135e+00 1.11804926e+00 5.31008065e-01 -1.22846353e+00 -5.05263507e-01 -2.45495409e-01 5.67099117e-02 -1.32090974e+00 -2.38985598e-01 -1.81898810e-02 -5.18591583e-01 1.59499800e+00 3.50919008e-01 5.01666009e-01 1.31235290e+00 5.06426394e-01 4.94238973e-01 1.13763821e+00 -1.46440148e-01 1.52336076e-01 3.66205126e-02 8.31924736e-01 8.98971140e-01 7.18485892e-01 -2.52820621e-03 -4.58578557e-01 -1.23553604e-01 1.02450299e+00 9.89557579e-02 -1.74018573e-02 2.39530325e-01 -1.18465650e+00 8.35659981e-01 6.38731599e-01 1.34403601e-01 -4.03613567e-01 5.44019103e-01 7.71436691e-01 1.97033271e-01 1.54177651e-01 4.21535820e-01 -6.54432297e-01 -3.05828869e-01 -7.22700417e-01 1.48308605e-01 1.00474906e+00 1.22362685e+00 7.73848593e-01 2.38096505e-01 -3.35398704e-01 6.66565180e-01 8.23018923e-02 3.64665747e-01 5.77912509e-01 -7.01081812e-01 1.82432994e-01 4.16815966e-01 -3.12443208e-02 -8.92090619e-01 -7.94317424e-01 -7.28870392e-01 -1.44075465e+00 3.18546981e-01 6.76179290e-01 -3.42759013e-01 -1.23824418e+00 9.64529514e-01 -1.17028616e-01 -1.59539685e-01 5.83153628e-02 7.27541149e-01 1.08418906e+00 6.04620934e-01 1.68593284e-02 5.40785730e-01 1.54507458e+00 -1.29623699e+00 -1.58395201e-01 -2.03569323e-01 5.24629354e-01 -9.02625799e-01 9.31239307e-01 7.67834961e-01 -1.20918405e+00 -6.30129635e-01 -1.17270482e+00 -4.40215379e-01 -4.35239106e-01 3.31362903e-01 1.02330899e+00 7.39227414e-01 -1.05143976e+00 9.01557744e-01 -1.03673911e+00 -5.32663576e-02 9.47282195e-01 6.60155892e-01 -2.07251534e-01 2.93521564e-02 -4.69844341e-01 6.15823805e-01 4.90132451e-01 1.03922561e-01 -1.16536725e+00 -5.65929711e-01 -3.03445220e-01 2.45582834e-01 -3.12152624e-01 -5.06925941e-01 1.42052221e+00 -8.80270362e-01 -1.81799042e+00 7.79621899e-01 1.59410864e-01 -8.68962586e-01 5.12988031e-01 -3.21644545e-01 -1.55304700e-01 -6.28289878e-02 -3.55836362e-01 6.71656311e-01 5.93343198e-01 -6.04087293e-01 -6.49165571e-01 -1.40948772e-01 1.10116772e-01 -4.78946120e-01 -3.69546980e-01 1.51946679e-01 -2.56880015e-01 -6.23804510e-01 -8.53309557e-02 -9.61962938e-01 -3.74873012e-01 3.71201150e-02 -6.98057473e-01 -1.63048133e-01 5.72000146e-01 -4.88208503e-01 6.93587244e-01 -1.96144176e+00 -4.23538417e-01 1.88100949e-01 2.72049844e-01 4.84260201e-01 -1.29204676e-01 1.60744011e-01 8.96383226e-02 1.18942540e-02 -8.65649655e-02 -1.71141848e-01 -8.09785277e-02 1.30726710e-01 -2.05613717e-01 2.45206520e-01 3.90705675e-01 9.05954182e-01 -6.72920704e-01 1.24677546e-01 3.25850435e-02 6.13527477e-01 -8.37012887e-01 8.10071453e-02 2.16363639e-01 8.15817788e-02 -2.23332793e-02 7.11372197e-01 7.36827433e-01 -5.77355385e-01 -2.85291616e-02 -2.76282877e-01 -1.92923561e-01 4.99819279e-01 -8.33555341e-01 1.34769762e+00 -3.92633468e-01 1.10501695e+00 -4.90476906e-01 -9.64293420e-01 1.12957251e+00 1.20932236e-01 -5.56674153e-02 -5.67080438e-01 2.95933843e-01 3.08290362e-01 3.09260041e-01 -2.30386272e-01 4.37026739e-01 3.65761131e-01 4.84836800e-03 9.21557024e-02 4.74719137e-01 4.49562728e-01 2.96149671e-01 -8.03766027e-02 1.44339049e+00 -3.29829037e-01 2.97927022e-01 -5.34968078e-01 2.77775377e-01 1.06841430e-01 4.29137826e-01 1.25395238e+00 4.88768555e-02 7.91518569e-01 7.62528658e-01 -1.23042524e+00 -1.24861407e+00 -8.73134613e-01 -5.70226550e-01 1.22364283e+00 -4.37572092e-01 -6.06707931e-01 -6.47071779e-01 -4.47419316e-01 3.27540338e-02 1.28226101e-01 -7.37344503e-01 3.10207885e-02 -6.98324144e-01 -1.17469394e+00 9.42360282e-01 9.57712591e-01 1.12481987e+00 -1.10199082e+00 -7.79839039e-01 5.51385939e-01 4.79577363e-01 -1.20893359e+00 3.31437260e-01 6.48131192e-01 -1.08925593e+00 -9.75518346e-01 -8.17213655e-01 -8.88936043e-01 5.93569160e-01 -2.88192689e-01 1.40171599e+00 2.70200282e-01 -4.04262990e-01 -2.52925336e-01 -1.49765864e-01 -3.70606929e-01 2.85410546e-02 5.63248575e-01 -1.07442297e-01 -1.71226010e-01 2.81254947e-01 -5.33984482e-01 -6.45215154e-01 2.42900401e-01 -3.90361160e-01 -5.05914958e-03 7.34752953e-01 1.33990133e+00 3.69362354e-01 -2.25125477e-01 1.65769503e-01 -1.03028417e+00 1.70877114e-01 -9.21078250e-02 -8.24740052e-01 3.95247675e-02 -4.25066680e-01 -7.53555400e-03 7.10958064e-01 -6.33245349e-01 -7.53556550e-01 2.76235253e-01 -4.54165131e-01 -2.59038638e-02 -4.60655957e-01 2.10962430e-01 4.60248053e-01 -4.28673297e-01 1.02589083e+00 -5.95306279e-03 -6.43035889e-01 -5.65320969e-01 -2.11086750e-01 5.66484511e-01 6.48250878e-01 -3.93430173e-01 3.40923488e-01 3.58051866e-01 -2.04772279e-02 -8.28061938e-01 -6.46419466e-01 -1.35933548e-01 -4.74455893e-01 2.93104321e-01 6.60943747e-01 -9.27268147e-01 -1.20220447e+00 9.46256936e-01 -1.30715787e+00 -8.03952992e-01 -1.48293659e-01 4.35287923e-01 -2.00483277e-01 -1.62817419e-01 -1.33749974e+00 -3.09836626e-01 -7.98180282e-01 -1.12395823e+00 9.05221164e-01 1.67351887e-01 -9.23653916e-02 -7.38032997e-01 -3.11245322e-01 -9.46114510e-02 7.36474216e-01 2.08085433e-01 5.81109762e-01 -6.39172792e-01 -7.20842302e-01 -1.87709898e-01 -6.89023733e-01 4.76812869e-01 -5.17063066e-02 2.77048260e-01 -1.21176755e+00 -4.98615742e-01 -2.86901832e-01 -6.51393652e-01 1.02998722e+00 2.35585436e-01 1.50988388e+00 -7.07203686e-01 -7.80267492e-02 1.00859165e+00 1.51251054e+00 2.04040676e-01 7.97895133e-01 6.00589693e-01 6.08947694e-01 1.33628002e-03 -2.22808212e-01 7.92738616e-01 -2.16425881e-02 3.08345556e-01 3.62713844e-01 -7.89810624e-03 -7.66798258e-02 5.00865936e-01 6.98452219e-02 6.54770970e-01 -5.62982857e-01 -4.71441485e-02 -1.38861966e+00 2.24222273e-01 -1.56013644e+00 -3.79632652e-01 -5.70890486e-01 1.77715504e+00 9.30718422e-01 5.75082839e-01 4.37001931e-03 2.37490058e-01 3.36919636e-01 -2.65047908e-01 -2.23636404e-01 -6.72126830e-01 -1.89632460e-01 7.80085623e-01 8.99567068e-01 1.39606327e-01 -1.37137914e+00 9.99232054e-01 6.41859531e+00 4.72490549e-01 -1.42001307e+00 -5.44361845e-02 1.01602829e+00 -5.33654578e-02 5.02648473e-01 -2.92284936e-01 -1.06419826e+00 3.59252602e-01 1.07911944e+00 2.83370763e-01 3.66344422e-01 1.06383288e+00 -5.04133940e-01 2.33121049e-02 -1.12367344e+00 1.15396500e+00 -4.50027525e-01 -1.65816069e+00 -1.81953330e-02 -1.58311222e-02 9.30800974e-01 5.48635662e-01 2.04788774e-01 5.61302483e-01 5.68719625e-01 -1.23360109e+00 7.54102468e-01 3.66532475e-01 6.10191882e-01 -1.04021561e+00 1.19119215e+00 1.11617766e-01 -8.36478829e-01 -1.98924839e-02 -1.00597155e+00 -5.53757310e-01 -5.48054814e-01 7.55919933e-01 -7.88435578e-01 2.59303525e-02 1.22708249e+00 5.51949501e-01 -9.24896359e-01 1.12579203e+00 -1.78628191e-01 7.91337132e-01 -3.83876324e-01 -5.36372662e-01 7.32642353e-01 5.10265648e-01 -5.95538132e-02 1.64382648e+00 5.47509305e-02 1.99379370e-01 -1.84019700e-01 4.34211582e-01 -3.06987613e-01 -2.20063359e-01 -2.13958696e-01 1.53510943e-01 8.51853564e-02 1.46179354e+00 -9.26676810e-01 -6.76354885e-01 -1.23143151e-01 1.06693649e+00 5.58902740e-01 4.39873189e-01 -9.69718397e-01 -9.44524050e-01 5.18363774e-01 -2.29901254e-01 6.39103949e-01 -2.10619062e-01 -6.66844666e-01 -1.23159766e+00 -8.21451396e-02 -7.38762677e-01 -2.26530395e-02 -4.13919061e-01 -1.24905849e+00 1.02143896e+00 -6.35595441e-01 -7.48909056e-01 -2.06651703e-01 -1.39722073e+00 -5.73786974e-01 7.12639511e-01 -1.19459403e+00 -7.01089799e-01 -6.22610152e-01 4.96177524e-01 1.79514810e-01 -4.60253000e-01 1.18104279e+00 4.54479843e-01 -7.84265816e-01 9.54948485e-01 2.91541815e-01 7.13023007e-01 2.17673913e-01 -1.07595801e+00 9.75706637e-01 4.17622775e-01 5.05984761e-02 5.72655082e-01 3.46684188e-01 -7.88191780e-02 -1.23921514e+00 -1.30917156e+00 8.48275602e-01 -2.13581011e-01 6.28825665e-01 -7.65849471e-01 -9.24598634e-01 8.10977340e-01 2.46238962e-01 6.73760235e-01 4.71100062e-01 3.52611810e-01 -6.52200937e-01 -2.33632460e-01 -1.05961680e+00 5.41890860e-01 9.39943373e-01 -3.35439205e-01 -1.38307631e-01 4.00309354e-01 3.79198760e-01 -6.90253794e-01 -1.00193274e+00 3.76139760e-01 7.47450113e-01 -1.18939292e+00 9.84652460e-01 -8.61067057e-01 5.90474427e-01 1.68037906e-01 -9.62470844e-02 -7.17975736e-01 -6.68473661e-01 -4.72540975e-01 -1.21676229e-01 8.64600480e-01 6.11997783e-01 -8.57671201e-01 1.10058677e+00 1.54126972e-01 -1.15268342e-01 -1.08582783e+00 -7.37731397e-01 -9.25383210e-01 1.70422167e-01 -3.86146486e-01 5.03261924e-01 8.73158276e-01 -5.32417238e-01 3.62795621e-01 -2.68334180e-01 1.41597027e-03 4.67145234e-01 2.62601636e-02 7.17920065e-01 -1.11899602e+00 -5.58118939e-01 -6.09200478e-01 -7.30020463e-01 -9.26943541e-01 -4.03455079e-01 -6.72529161e-01 -2.13559747e-01 -1.15226722e+00 1.90105736e-01 -5.40605247e-01 -5.00717998e-01 1.00504112e+00 2.95296967e-01 9.07763302e-01 -2.87198275e-02 9.57227647e-02 -3.55206251e-01 1.08311921e-01 7.55283654e-01 -2.32224911e-01 1.03770636e-01 -3.02835163e-02 -2.18197346e-01 1.10179901e+00 1.34972930e+00 -5.64700365e-01 1.94023594e-01 -8.31373572e-01 8.88611376e-02 -3.47908318e-01 5.89227021e-01 -1.39636326e+00 3.37974638e-01 3.64172727e-01 1.01882255e+00 -4.96501833e-01 1.63904756e-01 -4.33635682e-01 -2.86586672e-01 7.94038892e-01 -3.10752034e-01 2.09853128e-01 5.36070585e-01 2.80095357e-02 -1.00249700e-01 -2.69404143e-01 8.84988427e-01 -3.63151915e-02 -6.07721567e-01 2.83975512e-01 -5.96331000e-01 -2.43754849e-01 5.73279619e-01 -4.93950136e-02 -4.63355958e-01 7.47372881e-02 -7.39295781e-01 -3.25202942e-01 -2.58238614e-01 8.41257647e-02 5.26271284e-01 -1.28814280e+00 -7.92972028e-01 2.56621152e-01 -1.60144538e-01 1.35685161e-01 -8.23964924e-02 5.50880432e-01 -1.16527224e+00 7.10993826e-01 -6.63440704e-01 -7.36531854e-01 -1.11858928e+00 2.24239156e-01 4.26068425e-01 -4.36944991e-01 -6.25644207e-01 1.17466724e+00 -6.41205311e-02 -2.02974752e-01 4.69620556e-01 -6.74069047e-01 2.00643733e-01 -2.62817830e-01 6.77754581e-01 5.81814408e-01 5.84784389e-01 -1.83743462e-02 -4.50157404e-01 2.85073310e-01 -3.59405756e-01 2.12201566e-01 1.51477265e+00 8.25475156e-01 -1.79343820e-01 2.18654379e-01 1.44177067e+00 -5.64571857e-01 -1.17501819e+00 5.41408136e-02 3.46205413e-01 -1.57099334e-03 5.72579689e-02 -9.31108057e-01 -1.19586062e+00 1.04896522e+00 6.62523091e-01 1.43529862e-01 1.08984089e+00 -3.91334683e-01 7.46655285e-01 1.30803335e+00 3.07877481e-01 -7.86869109e-01 9.61692259e-02 1.26184607e+00 8.45794082e-01 -1.08392048e+00 7.27739697e-03 -1.59152731e-01 5.98712116e-02 1.59148312e+00 7.07887113e-01 -6.82658732e-01 6.69050932e-01 8.38208377e-01 -2.02179849e-01 1.03415847e-02 -9.26160455e-01 1.88064411e-01 2.91466147e-01 1.42410040e-01 7.14278758e-01 -1.69994198e-02 1.01081096e-02 7.11247504e-01 -5.12429059e-01 -4.32562791e-02 3.34162593e-01 1.10209692e+00 -2.76374429e-01 -7.35146940e-01 -1.38144851e-01 5.00463486e-01 -8.72340977e-01 -4.74242777e-01 -1.70634344e-01 8.49307775e-01 -9.49148275e-03 3.60460967e-01 4.79408503e-01 -4.37471867e-01 2.66578913e-01 -1.63339198e-01 5.89204848e-01 -4.56249565e-01 -1.14423001e+00 -9.36775357e-02 1.35026917e-01 -5.98811924e-01 -9.88150090e-02 -1.72969237e-01 -1.15977025e+00 -7.41509259e-01 -1.19522467e-01 -2.45479584e-01 7.54111469e-01 5.48614204e-01 3.19819242e-01 7.15411425e-01 3.48396033e-01 -8.90298009e-01 -4.34047431e-01 -9.70466375e-01 -3.99664074e-01 1.62024740e-02 3.04035008e-01 -1.54800177e-01 -1.33822650e-01 -9.12160277e-02]	[8.998150825500488, 2.434209108352661]
43967bf1-0084-402d-8a6d-2fc26d7df0c8	real-time-localized-photorealistic-video	2010.10056	null	https://arxiv.org/abs/2010.10056v1	https://arxiv.org/pdf/2010.10056v1.pdf	Real-time Localized Photorealistic Video Style Transfer	We present a novel algorithm for transferring artistic styles of semantically meaningful local regions of an image onto local regions of a target video while preserving its photorealism. Local regions may be selected either fully automatically from an image, through using video segmentation algorithms, or from casual user guidance such as scribbles. Our method, based on a deep neural network architecture inspired by recent work in photorealistic style transfer, is real-time and works on arbitrary inputs without runtime optimization once trained on a diverse dataset of artistic styles. By augmenting our video dataset with noisy semantic labels and jointly optimizing over style, content, mask, and temporal losses, our method can cope with a variety of imperfections in the input and produce temporally coherent videos without visual artifacts. We demonstrate our method on a variety of style images and target videos, including the ability to transfer different styles onto multiple objects simultaneously, and smoothly transition between styles in time.	['Jiawen Chen', 'Brian Kulis', 'Abby Chang', 'Zheng Sun', 'Wei-Sheng Lai', 'Tianfan Xue', 'Xide Xia']	2020-10-20	null	null	null	null	['video-style-transfer']	['computer-vision']	[ 6.83475673e-01 -2.33368412e-01 1.69665039e-01 -5.02405763e-01 -5.45949340e-01 -1.20875108e+00 4.45530862e-01 -4.32567894e-01 -2.73214340e-01 5.35032153e-01 -2.79678460e-02 9.37823951e-02 2.51377910e-01 -6.52437747e-01 -9.82359350e-01 -3.41447145e-01 3.47321033e-01 4.50546265e-01 2.63874412e-01 -2.20260113e-01 4.19510692e-01 7.98062742e-01 -1.24442029e+00 4.40293550e-01 4.93509263e-01 1.03895676e+00 6.24778420e-02 9.90807176e-01 1.12023558e-02 9.11426306e-01 -7.43808329e-01 -3.49425137e-01 7.02787519e-01 -6.76512778e-01 -9.77896929e-01 7.20246673e-01 9.80335891e-01 -6.09019995e-01 -4.98476118e-01 1.06655681e+00 1.37359291e-01 3.81129950e-01 4.53192800e-01 -1.13691497e+00 -9.16610777e-01 2.91554064e-01 -5.14437497e-01 5.88693433e-02 2.91288584e-01 5.31562984e-01 7.11156607e-01 -7.60715485e-01 1.02249825e+00 1.44822788e+00 5.17063498e-01 7.73637354e-01 -1.84806967e+00 -5.35912156e-01 2.17308313e-01 -1.09119311e-01 -1.08502471e+00 -4.75702554e-01 1.02554226e+00 -4.92831558e-01 3.70125949e-01 2.48971745e-01 7.80924320e-01 1.33326304e+00 1.56742275e-01 8.28315377e-01 1.14328682e+00 -2.87591815e-01 3.14049453e-01 -8.05319324e-02 -5.76676488e-01 7.41751671e-01 -4.75831717e-01 1.87983155e-01 -6.20756090e-01 -3.52428891e-02 1.45577347e+00 5.10735437e-02 -2.63743281e-01 -5.45801818e-01 -1.35800350e+00 5.59301078e-01 3.44654053e-01 3.85757163e-02 -5.68418093e-02 5.29844642e-01 2.98434258e-01 6.42168939e-01 4.72949833e-01 7.28533030e-01 -4.12860692e-01 -2.84950230e-02 -1.17636108e+00 1.81057364e-01 4.81118143e-01 1.17780769e+00 8.09026241e-01 3.15191627e-01 -2.10330367e-01 6.92476869e-01 -1.65360361e-01 5.08495033e-01 1.59659743e-01 -1.60024655e+00 9.43079963e-02 2.35918790e-01 4.13039088e-01 -8.99559140e-01 6.81921467e-02 1.73101854e-02 -6.13781393e-01 7.59129465e-01 4.21274692e-01 -2.92596638e-01 -1.20518935e+00 1.87812591e+00 1.31230652e-01 -2.50604115e-02 -2.85100728e-01 1.06697369e+00 3.96188706e-01 7.53786147e-01 6.74441159e-02 1.09808140e-01 8.98714960e-01 -1.00785208e+00 -4.08895284e-01 -3.16846520e-01 -3.22846621e-02 -1.00187457e+00 1.19580269e+00 5.10562122e-01 -1.55323327e+00 -7.60570109e-01 -7.57507503e-01 -5.46910644e-01 -1.35683879e-01 -1.85355276e-03 4.01987284e-01 2.14803651e-01 -1.42766845e+00 9.26619887e-01 -6.74493730e-01 -4.10527587e-01 5.37199080e-01 3.62007707e-01 -2.97983229e-01 5.78290783e-02 -7.70454466e-01 5.73029041e-01 1.88280419e-01 -7.20879287e-02 -1.18126607e+00 -8.46406817e-01 -8.07328582e-01 -1.43846041e-02 2.56719857e-01 -1.12380838e+00 1.21523952e+00 -2.12576485e+00 -1.76341569e+00 1.07593358e+00 -3.96629535e-02 -1.13675289e-01 8.33241820e-01 -3.13022375e-01 -2.36955896e-01 3.93764734e-01 6.22089766e-02 1.46246016e+00 1.30204034e+00 -1.33144796e+00 -6.02314651e-01 -9.11719874e-02 2.13599056e-01 3.43734443e-01 -1.51868507e-01 2.26685882e-01 -5.69767416e-01 -1.16532445e+00 -2.89496243e-01 -1.19710422e+00 -2.59573311e-01 5.52100182e-01 -2.52412200e-01 2.71376073e-01 1.20727706e+00 -6.60143495e-01 5.26537657e-01 -2.31192565e+00 7.12056935e-01 8.88388008e-02 4.90084067e-02 -3.41035426e-02 -4.49951261e-01 1.38682693e-01 2.30032578e-02 6.12329692e-03 -3.22083622e-01 -3.66505355e-01 -2.90173143e-01 8.95692110e-02 -3.33133668e-01 2.99926788e-01 3.20134312e-01 9.77294326e-01 -1.13989401e+00 -3.95199656e-01 4.01414514e-01 3.30285430e-01 -7.30190516e-01 3.32853585e-01 -6.56155884e-01 9.08796430e-01 -3.58086973e-01 5.55224419e-01 3.43340546e-01 -2.12061390e-01 -5.01076691e-02 -1.47158295e-01 2.17815623e-01 -1.59702256e-01 -9.42527831e-01 2.21829748e+00 -5.31297922e-01 1.02506769e+00 2.49147549e-01 -6.51779354e-01 7.44520545e-01 2.39737540e-01 6.42147422e-01 -2.62847871e-01 2.37180129e-01 8.60071629e-02 -4.37042385e-01 -3.65294486e-01 6.22901678e-01 -2.58291960e-01 -1.88705042e-01 7.26831138e-01 1.82298139e-01 -5.45353830e-01 1.43342093e-01 1.35747835e-01 1.01636159e+00 5.31537712e-01 -1.68423250e-01 -3.74045968e-01 9.78051051e-02 1.59483384e-02 4.71980453e-01 6.01996183e-01 -1.02342717e-01 1.13899803e+00 2.53926367e-01 -8.01876605e-01 -1.53779316e+00 -1.32301307e+00 2.36265987e-01 1.16893017e+00 3.79580319e-01 1.60508901e-01 -6.59155369e-01 -7.92785823e-01 -1.22878753e-01 5.44872642e-01 -7.49490201e-01 -8.90441015e-02 -8.13111603e-01 2.01249436e-01 2.81601071e-01 6.11249149e-01 4.78733480e-01 -1.58631051e+00 -5.73775411e-01 2.03429684e-01 -6.78086281e-02 -1.15968931e+00 -1.32972372e+00 -8.98596793e-02 -9.34821248e-01 -8.47237170e-01 -8.64172518e-01 -9.66003895e-01 7.99914837e-01 3.11940312e-01 1.47976983e+00 -9.90805626e-02 -2.46092319e-01 5.85770965e-01 4.67019193e-02 7.79309273e-02 -7.44014740e-01 -1.15607277e-01 -1.71090782e-01 3.17566246e-01 -1.31853074e-01 -8.43196929e-01 -8.05788100e-01 2.65072286e-01 -1.33599532e+00 3.28778476e-01 2.86893457e-01 8.42198730e-01 5.16781390e-01 -2.02699065e-01 2.27926522e-01 -9.83275533e-01 2.65858293e-01 -6.18999004e-02 -7.17340469e-01 1.24598570e-01 -1.10752165e-01 1.62447900e-01 6.84431612e-01 -6.86076105e-01 -1.11831522e+00 3.46398026e-01 3.41468811e-01 -1.15223145e+00 -3.81864130e-01 -2.96675771e-01 -2.78303735e-02 -3.17823350e-01 6.69954419e-01 1.52574167e-01 -2.22315788e-02 -2.93445557e-01 8.05799603e-01 2.13918477e-01 8.29226732e-01 -7.58450747e-01 8.68316650e-01 7.22504914e-01 -7.74727464e-02 -5.05490243e-01 -8.21184278e-01 -4.24440801e-02 -8.95443738e-01 -1.95690542e-01 9.25783038e-01 -8.73267531e-01 -3.59143823e-01 5.24267435e-01 -1.17723286e+00 -7.75715292e-01 -6.99296355e-01 -5.54330498e-02 -9.66872573e-01 2.45560676e-01 -7.02073097e-01 -1.48772299e-01 -2.39662483e-01 -1.14231622e+00 1.40644491e+00 2.62841433e-01 -5.43911040e-01 -1.11333287e+00 -2.78100610e-01 2.40420923e-01 4.02934790e-01 4.32504743e-01 7.72380650e-01 9.62059274e-02 -1.00971746e+00 1.21489868e-01 -2.19373241e-01 4.15143847e-01 5.53994298e-01 1.49201721e-01 -7.49390781e-01 -4.17346090e-01 -2.26020381e-01 -5.48615456e-01 8.27114105e-01 3.63852262e-01 1.45050836e+00 -4.29827154e-01 -2.29471177e-02 8.70009243e-01 1.35704160e+00 3.79188627e-01 4.95803088e-01 1.92963034e-01 9.72811639e-01 5.38221776e-01 2.78645486e-01 7.81747103e-02 -2.38957405e-01 6.75360084e-01 2.19471127e-01 -3.72809172e-01 -3.22538435e-01 -2.65285075e-01 4.49496597e-01 6.07712343e-02 5.37207685e-02 -3.18606526e-01 -2.11180463e-01 6.58506334e-01 -1.65282059e+00 -1.06824076e+00 5.83192945e-01 2.13346434e+00 1.04154587e+00 8.61953199e-02 3.36253405e-01 -3.25688988e-01 7.80587733e-01 2.31822297e-01 -8.92179608e-01 -6.33376598e-01 -2.24268824e-01 1.50230482e-01 4.68787462e-01 4.40175056e-01 -1.19717193e+00 1.23463571e+00 6.80126762e+00 6.47625208e-01 -1.47081935e+00 -6.40781224e-02 1.02807546e+00 -5.40543854e-01 -5.28228164e-01 4.00940049e-03 -8.71478617e-02 4.11280662e-01 3.34958255e-01 3.90534918e-03 1.01627791e+00 5.68208933e-01 2.72744656e-01 2.01597854e-01 -1.52018750e+00 9.55789387e-01 2.15478927e-01 -1.59537017e+00 2.92827696e-01 -1.78930104e-01 1.32377064e+00 -2.47537419e-01 3.27085227e-01 -2.22868890e-01 7.68634975e-01 -9.68740940e-01 1.26065648e+00 5.00558555e-01 1.15018725e+00 -5.82830489e-01 -1.56042995e-02 -3.29288542e-01 -6.88987792e-01 -4.21024412e-02 7.92855583e-03 1.42104506e-01 2.99848765e-01 2.38467932e-01 -2.83274561e-01 9.07886624e-02 6.85922861e-01 8.85921061e-01 -6.36630356e-01 7.30226159e-01 7.79295200e-03 2.94987410e-01 -2.45788172e-01 3.24876636e-01 3.10092241e-01 -3.46626312e-01 7.03584552e-01 1.06474733e+00 2.09733561e-01 1.05426259e-01 2.61382699e-01 1.26813138e+00 -3.50873351e-01 -2.35102400e-01 -8.10832143e-01 4.88413759e-02 2.93098807e-01 1.20545149e+00 -9.10717130e-01 -3.94984394e-01 -1.92341968e-01 1.62919557e+00 8.64756033e-02 7.92417049e-01 -6.96615458e-01 -2.16911077e-01 7.08154380e-01 1.00145647e-02 3.88231665e-01 -3.00656945e-01 -5.77843070e-01 -1.21792781e+00 2.08408944e-03 -9.34679568e-01 2.01978758e-01 -1.35034704e+00 -1.17421460e+00 7.33196259e-01 -2.01009870e-01 -1.32487595e+00 -1.03822619e-01 -4.30401236e-01 -6.79139078e-01 5.84556818e-01 -7.92622805e-01 -1.10626471e+00 -2.89722204e-01 6.94371104e-01 9.98978555e-01 -1.95325226e-01 3.60600680e-01 1.51873708e-01 -7.54713342e-02 3.89884531e-01 -7.02194357e-03 1.67672545e-01 9.25545096e-01 -1.37325525e+00 5.82215011e-01 9.00604427e-01 3.74330014e-01 2.52212763e-01 8.35505605e-01 -3.89542103e-01 -1.07495081e+00 -1.33164239e+00 3.61469358e-01 -5.62880635e-01 4.84552652e-01 -4.01405454e-01 -6.44399881e-01 9.35764253e-01 6.77644610e-01 -6.69820681e-02 5.63535951e-02 -3.13009918e-01 -3.66589963e-01 -1.17853090e-01 -1.18584192e+00 1.09157884e+00 1.35145116e+00 -5.35504937e-01 -3.80847394e-01 4.14651632e-01 7.51097143e-01 -5.70298731e-01 -7.24761009e-01 2.24476740e-01 4.12180007e-01 -8.16581190e-01 1.02266574e+00 -8.03937137e-01 8.14952493e-01 -4.06591803e-01 -2.07538906e-05 -1.41784394e+00 -3.63304615e-01 -1.10435581e+00 3.15315902e-01 1.12969160e+00 2.27330014e-01 9.55250172e-04 7.33758867e-01 7.73782313e-01 -3.75982411e-02 -2.96948671e-01 -6.33303702e-01 -6.42947257e-01 -1.64516289e-02 -3.70560549e-02 4.94472325e-01 7.05740035e-01 -6.31254256e-01 3.20493251e-01 -6.42736375e-01 -3.43129113e-02 6.62647307e-01 5.89906156e-01 8.37125182e-01 -8.75414789e-01 -3.87077123e-01 -6.46987259e-01 -3.55777472e-01 -1.04002976e+00 1.12144768e-01 -5.27286530e-01 1.19157933e-01 -1.03488171e+00 3.52309011e-02 -3.66573244e-01 -5.95095232e-02 4.93099064e-01 2.32325960e-02 7.31307149e-01 3.57970089e-01 2.51501977e-01 -6.44502580e-01 5.95691264e-01 1.70548534e+00 -3.97522748e-01 -2.97266275e-01 -1.87311471e-01 -5.92543304e-01 8.19220960e-01 5.63879192e-01 -3.57660562e-01 -4.74545240e-01 -6.92829311e-01 5.34056760e-02 2.88257211e-01 4.85510439e-01 -7.90735900e-01 -1.92033634e-01 -5.69124222e-01 8.41660023e-01 -3.02392896e-02 3.78669769e-01 -7.06638753e-01 3.91064405e-01 6.28533065e-02 -7.83371866e-01 1.02272555e-01 2.72884220e-01 7.27427125e-01 -5.97333051e-02 5.63241877e-02 1.19490719e+00 -2.32528061e-01 -8.70329678e-01 3.79554957e-01 -2.31125444e-01 1.96245402e-01 9.69419181e-01 -3.02979261e-01 5.59496842e-02 -5.72330058e-01 -1.10213482e+00 1.22416569e-02 1.19047868e+00 6.59106314e-01 5.18275261e-01 -1.63217795e+00 -4.98439521e-01 3.31614256e-01 -2.54769586e-02 -3.60617824e-02 2.17879876e-01 2.08401173e-01 -9.03835058e-01 -2.46035028e-02 -5.69129586e-01 -7.93021142e-01 -1.10497999e+00 7.82293320e-01 5.16481936e-01 2.62236804e-01 -8.58079493e-01 7.84984469e-01 6.69372857e-01 -1.10993877e-01 8.61013457e-02 -3.26634765e-01 3.37052345e-01 -5.35659313e-01 2.44132176e-01 -6.05715290e-02 -2.45658219e-01 -4.92050797e-01 2.39838883e-02 8.06094587e-01 8.18302929e-02 -5.23640871e-01 1.09029305e+00 -4.85310853e-01 -6.84636906e-02 4.89289105e-01 1.16723824e+00 8.49043578e-02 -2.13893223e+00 -2.71881729e-01 -4.38359708e-01 -7.48543620e-01 -1.32438377e-01 -8.49980712e-01 -1.47526670e+00 5.56071222e-01 5.52731335e-01 -3.76048274e-02 1.41022968e+00 -2.49331910e-02 1.06000257e+00 1.53833658e-01 3.92183185e-01 -1.01921368e+00 6.46888793e-01 9.20342728e-02 1.09644079e+00 -1.19778919e+00 -4.13153172e-01 -1.37036830e-01 -7.40198255e-01 1.19070220e+00 5.69215655e-01 -5.97290218e-01 4.16680306e-01 4.88973856e-02 3.88681144e-01 -3.72783281e-02 -6.12454712e-01 2.33428672e-01 3.88610989e-01 4.86568928e-01 1.26798213e-01 -1.18494540e-01 2.52857506e-01 -1.46711946e-01 -1.50753364e-01 2.02919573e-01 7.67570674e-01 7.75943875e-01 -1.15853056e-01 -1.06660140e+00 -3.59002411e-01 1.68958470e-01 -3.98655087e-01 -9.05254185e-02 -5.85808635e-01 4.51926649e-01 1.21486410e-01 6.99503064e-01 3.62960279e-01 -1.87943518e-01 9.19290558e-02 -2.38994565e-02 8.35349083e-01 -5.99216342e-01 -5.32797277e-01 2.78032035e-01 -1.82227686e-01 -7.73059070e-01 -4.81710583e-01 -8.19686830e-01 -8.12040687e-01 -3.90692234e-01 3.44086826e-01 -3.03426117e-01 2.28198290e-01 9.26787496e-01 5.03617585e-01 4.30129260e-01 8.00044358e-01 -1.29563010e+00 -2.06394903e-02 -5.59392452e-01 -5.25301337e-01 9.61794853e-01 4.51551318e-01 -3.54754210e-01 -2.42609769e-01 7.95182645e-01]	[11.377276420593262, -0.6455422043800354]
7b61b0a7-e616-4302-a409-cdf704d6b117	breaking-the-cycle-colleagues-are-all-you-1	null	null	http://openaccess.thecvf.com/content_CVPR_2020/html/Nizan_Breaking_the_Cycle_-_Colleagues_Are_All_You_Need_CVPR_2020_paper.html	http://openaccess.thecvf.com/content_CVPR_2020/papers/Nizan_Breaking_the_Cycle_-_Colleagues_Are_All_You_Need_CVPR_2020_paper.pdf	Breaking the Cycle - Colleagues Are All You Need	This paper proposes a novel approach to performing image-to-image translation between unpaired domains. Rather than relying on a cycle constraint, our method takes advantage of collaboration between various GANs. This results in a multi modal method, in which multiple optional and diverse images are produced for a given image. Our model addresses some of the shortcomings of classical GANs: (1) It is able to remove large objects, such as glasses. (2) Since it does not need to support the cycle constraint, no irrelevant traces of the input are left on the generated image. (3) It manages to translate between domains that require large shape modifications. Our results are shown to outperform those generated by state-of-the-art methods for several challenging applications on commonly-used datasets, both qualitatively and quantitatively.	[' Ayellet Tal', 'Ori Nizan']	2020-06-01	null	null	null	cvpr-2020-6	['multimodal-unsupervised-image-to-image']	['computer-vision']	[ 6.56163931e-01 2.91944265e-01 2.08642140e-01 2.06513461e-02 -7.52328336e-01 -8.07652056e-01 7.31267750e-01 -3.69022757e-01 -1.23147257e-01 9.56934869e-01 -1.06359702e-02 1.10324085e-01 1.08370677e-01 -8.34016323e-01 -7.58111715e-01 -7.99092710e-01 5.77121794e-01 6.87631190e-01 5.97098947e-01 -3.10791612e-01 5.44797676e-03 5.69698393e-01 -1.49946725e+00 1.82933509e-01 1.01795483e+00 1.00831151e+00 3.13641667e-01 4.23367113e-01 4.42659482e-02 4.69617337e-01 -5.82507312e-01 -4.40464199e-01 4.45915610e-01 -1.12460637e+00 -7.05553532e-01 5.26144564e-01 6.75673008e-01 -2.23392040e-01 8.51919279e-02 1.02236831e+00 4.95424956e-01 -7.19330460e-02 8.23251963e-01 -1.15306211e+00 -7.15545893e-01 3.12606335e-01 -8.18845272e-01 -3.38223696e-01 3.58192444e-01 3.41760308e-01 5.86830020e-01 -7.75872946e-01 1.01548994e+00 1.06728566e+00 4.94852006e-01 7.94018507e-01 -1.65772760e+00 -4.64333206e-01 -3.35193016e-02 -3.12465429e-01 -1.20978844e+00 -5.50457120e-01 7.17909813e-01 -5.14919341e-01 5.59967518e-01 2.89033443e-01 6.46242678e-01 9.86145139e-01 2.31331632e-01 3.74774188e-01 1.42454398e+00 -6.39723063e-01 2.00059399e-01 9.76741612e-02 -5.69357872e-01 6.65601075e-01 2.37006202e-01 1.73477769e-01 -4.02055442e-01 1.98456496e-02 8.89080107e-01 -3.41511428e-01 -3.03020209e-01 -4.37280446e-01 -1.27614117e+00 6.97208822e-01 1.88914061e-01 4.78816360e-01 -3.65834922e-01 2.39341736e-01 8.85754079e-02 2.52606243e-01 5.29139757e-01 3.10504586e-01 -5.00607677e-02 3.51512358e-02 -1.20944512e+00 1.85392171e-01 3.95402700e-01 1.02642167e+00 9.51305449e-01 2.06145555e-01 -2.50692964e-01 6.38627887e-01 1.32053420e-01 6.18839324e-01 2.84469098e-01 -1.10200119e+00 3.36476505e-01 5.41712165e-01 6.27150908e-02 -6.99655533e-01 -9.53411609e-02 -2.04056486e-01 -9.47705030e-01 6.24684632e-01 4.00608897e-01 -2.00615570e-01 -1.32327926e+00 1.77107036e+00 2.76772738e-01 -1.32659018e-01 -1.13427363e-01 6.29669309e-01 8.78147840e-01 3.30709189e-01 -2.30520278e-01 -2.53042877e-01 1.05799603e+00 -1.07102835e+00 -7.44711876e-01 -3.13261688e-01 1.35456502e-01 -9.67223942e-01 1.15968251e+00 3.00597429e-01 -1.60574341e+00 -5.76150417e-01 -9.20350432e-01 -5.34836613e-02 -2.58190215e-01 -1.30203208e-02 3.91583830e-01 7.23608911e-01 -1.47502530e+00 3.55415851e-01 -4.76288736e-01 -4.90422845e-01 5.19007087e-01 3.94080222e-01 -4.46172118e-01 -7.13531151e-02 -7.02859223e-01 9.11855042e-01 3.82373154e-01 -1.85135931e-01 -9.15302396e-01 -6.34037077e-01 -7.65913427e-01 -1.36029333e-01 2.95958042e-01 -1.20911694e+00 9.57857311e-01 -1.42253983e+00 -1.86931658e+00 1.17905927e+00 -2.42616117e-01 -2.97246333e-02 1.03111112e+00 2.81053465e-02 -1.36544615e-01 2.22859696e-01 1.46499038e-01 9.96524572e-01 1.07149112e+00 -1.60018206e+00 -4.50462490e-01 -3.99897844e-02 7.10237473e-02 1.00438461e-01 -1.07047081e-01 -1.78968441e-02 -7.26121306e-01 -8.57816517e-01 4.63214889e-02 -1.15078795e+00 -1.49291396e-01 1.31438002e-02 -5.40750861e-01 2.47385621e-01 1.00130069e+00 -3.68577957e-01 8.70136321e-01 -1.98037231e+00 5.45374155e-01 4.53401953e-02 1.87810048e-01 2.33455136e-01 -2.54877776e-01 5.20033062e-01 1.51359960e-01 1.10921696e-01 -5.90114236e-01 -6.95667267e-01 -2.07227960e-01 2.97384381e-01 -1.98762521e-01 3.56757969e-01 1.89556286e-01 1.05954599e+00 -5.72872937e-01 -6.63380444e-01 2.86059916e-01 4.57461029e-01 -6.24046683e-01 1.17967017e-01 -4.26866025e-01 9.43494260e-01 -1.04122587e-01 5.26166677e-01 9.78473246e-01 -2.50987321e-01 1.24527998e-01 -1.59171477e-01 6.14855923e-02 -1.02808937e-01 -1.06236887e+00 1.74246669e+00 -3.29810351e-01 3.93066645e-01 5.58743067e-02 -7.32404947e-01 6.86857045e-01 3.59918624e-01 4.19340253e-01 -7.11291671e-01 1.05019482e-02 3.46340001e-01 -2.52769321e-01 -9.00561139e-02 3.24669123e-01 -4.05317605e-01 -6.85057938e-02 4.93727118e-01 3.11514825e-01 -6.55381739e-01 5.05050540e-01 9.34300721e-02 9.14312303e-01 4.55380797e-01 1.36678696e-01 -3.40498805e-01 6.28052592e-01 -3.16187926e-02 6.39237106e-01 5.91257811e-01 1.13599226e-01 1.21273148e+00 4.70290750e-01 -2.17989132e-01 -1.19486558e+00 -1.14849913e+00 2.15181768e-01 6.03104353e-01 1.66932419e-01 -2.15297826e-02 -9.49260473e-01 -7.11657643e-01 -3.52954984e-01 4.62543339e-01 -6.55750513e-01 8.75271186e-02 -4.90893990e-01 -5.09004474e-01 5.04692852e-01 3.86631399e-01 5.99392712e-01 -1.14722919e+00 -5.97108424e-01 6.19429313e-02 -3.90265405e-01 -1.31118977e+00 -7.65085578e-01 -1.09369807e-01 -1.00058591e+00 -9.58117723e-01 -9.86027002e-01 -7.41594732e-01 8.85170281e-01 1.60005257e-01 1.45390677e+00 4.49788608e-02 -1.05323724e-01 4.63992596e-01 -1.31106347e-01 -2.64592916e-01 -6.98176086e-01 -1.79311987e-02 -1.63995445e-01 1.20979145e-01 -2.60970026e-01 -7.54784167e-01 -5.18660367e-01 4.76398528e-01 -1.19993138e+00 3.06842089e-01 6.44147396e-01 9.43088949e-01 8.72915685e-01 2.11305302e-02 5.57393909e-01 -1.06665170e+00 5.16586065e-01 3.78173478e-02 -7.49360442e-01 3.50046337e-01 -5.96819282e-01 -3.92075703e-02 6.53959513e-01 -4.81531769e-01 -1.20044386e+00 3.75973254e-01 1.37669146e-01 -2.91356355e-01 -1.84964672e-01 -1.99713185e-02 -2.59198129e-01 -3.19252521e-01 6.83641255e-01 2.71100938e-01 1.11436382e-01 -3.01078916e-01 5.30520678e-01 2.92724460e-01 5.62988639e-01 -5.11720657e-01 1.05232370e+00 7.86079466e-01 1.63424954e-01 -6.68436110e-01 -3.58869493e-01 -5.89520391e-03 -8.48020554e-01 -3.30230981e-01 1.05942345e+00 -8.25289607e-01 -4.33953077e-01 6.43730044e-01 -1.14368665e+00 -4.47250843e-01 -5.32774091e-01 1.11711361e-01 -9.04704452e-01 2.99839348e-01 -5.44753790e-01 -5.10035932e-01 -2.45453581e-01 -1.23811471e+00 1.19206274e+00 3.38282883e-01 -2.46014491e-01 -1.07388282e+00 -8.52931291e-03 4.59843248e-01 6.05763018e-01 6.53800011e-01 7.63771415e-01 1.11753277e-01 -7.02632487e-01 2.32563049e-01 -1.27684414e-01 3.60772580e-01 4.42837238e-01 8.35655704e-02 -8.87352765e-01 -4.72869128e-01 -1.18607603e-01 -3.70495230e-01 8.18657041e-01 3.68180126e-01 8.29918265e-01 -1.63319886e-01 -2.63794869e-01 6.55837715e-01 1.50835562e+00 2.12436810e-01 1.02741170e+00 1.83773071e-01 6.65658474e-01 5.84866107e-01 5.05151510e-01 4.19355221e-02 1.64400712e-01 8.67646515e-01 5.19851208e-01 -5.61913133e-01 -6.28674924e-01 -2.32195228e-01 4.40805316e-01 4.95985985e-01 -3.20375472e-01 -2.88929105e-01 -6.48292720e-01 6.82338774e-01 -1.87187421e+00 -8.24588060e-01 -2.23822087e-01 2.10155725e+00 7.45695233e-01 -1.06687084e-01 2.38948777e-01 -1.10482462e-01 6.73018456e-01 1.74711928e-01 -4.37361628e-01 -3.33164901e-01 -3.87843460e-01 4.04390514e-01 4.55899745e-01 4.07669395e-01 -8.51803184e-01 9.27031338e-01 7.18608284e+00 8.15126002e-01 -1.16029835e+00 3.18830699e-01 5.76435745e-01 -4.28408906e-02 -5.38596272e-01 7.81838223e-02 -4.38634247e-01 5.15703857e-01 3.34772974e-01 -7.55721405e-02 4.52527404e-01 4.14782494e-01 3.69407088e-02 -3.96397054e-01 -1.01216733e+00 7.70985842e-01 2.54846185e-01 -1.49029243e+00 9.86772925e-02 1.96541309e-01 1.26345801e+00 -2.49222174e-01 2.48234689e-01 -3.27420831e-01 3.48237485e-01 -1.13844693e+00 1.04604363e+00 4.81524527e-01 1.21781003e+00 -6.01414025e-01 5.52617311e-01 1.91805750e-01 -8.71581674e-01 3.28873068e-01 -2.05209568e-01 3.68737578e-01 3.30964267e-01 7.29590774e-01 -5.04196048e-01 8.53071034e-01 5.88672519e-01 3.91343504e-01 -5.74850023e-01 7.69403458e-01 -4.05330479e-01 2.82053620e-01 -3.50622773e-01 5.00888169e-01 4.18748613e-03 -3.98256004e-01 5.17170191e-01 9.54877615e-01 5.82498193e-01 -2.37263128e-01 -6.56478927e-02 1.16522729e+00 -1.03179865e-01 -1.20183676e-01 -8.85433435e-01 6.20640069e-02 1.41657740e-01 1.06036019e+00 -9.05983984e-01 -2.76196241e-01 -2.94491619e-01 1.45945334e+00 5.25173126e-03 3.67532849e-01 -8.43422949e-01 -6.42502308e-02 2.70777196e-01 3.83125544e-01 6.75925910e-01 -1.39241755e-01 -3.68345857e-01 -1.05490828e+00 2.03761861e-01 -1.02603769e+00 2.59937525e-01 -8.16300392e-01 -1.22399163e+00 7.56851494e-01 -4.28572334e-02 -1.40668523e+00 -3.36012512e-01 -2.36448169e-01 -5.34260333e-01 9.65038359e-01 -1.40358293e+00 -1.68438232e+00 -3.48074347e-01 8.04438651e-01 2.72230715e-01 -1.76997334e-01 9.30396199e-01 3.85783166e-01 -9.91683751e-02 4.48514760e-01 -4.49990481e-02 -2.47535735e-01 8.45180869e-01 -1.01814568e+00 2.64665544e-01 1.07814538e+00 9.96806026e-02 3.60909939e-01 7.20026910e-01 -6.21794701e-01 -1.12578475e+00 -9.48570371e-01 7.82464445e-01 -3.90735716e-01 1.55904740e-01 -3.19624305e-01 -5.98635137e-01 6.82308078e-01 5.74837983e-01 1.76799774e-01 3.79910916e-01 -3.20636749e-01 -1.53868407e-01 -2.02888131e-01 -1.38358712e+00 4.88866627e-01 1.05555665e+00 -2.97974706e-01 -2.34387428e-01 1.36276439e-01 4.24270630e-01 -6.26276851e-01 -6.15881443e-01 2.63605386e-01 4.02701765e-01 -1.29158247e+00 8.16552997e-01 -1.91196531e-01 6.75347805e-01 -5.69465816e-01 3.35334092e-02 -1.47756219e+00 -3.06170017e-01 -8.35245013e-01 -7.34475926e-02 1.38030910e+00 4.46105570e-01 -7.34754503e-01 6.49310470e-01 4.34728652e-01 1.80186145e-02 -4.48314756e-01 -1.06672943e+00 -9.59206760e-01 1.22912101e-01 4.65460308e-02 6.19038105e-01 8.61476958e-01 -5.64477921e-01 3.29342276e-01 -5.54057717e-01 -1.19324200e-01 6.85557842e-01 3.08659673e-01 1.00699031e+00 -1.13716769e+00 -4.86025214e-01 -3.97707850e-01 -2.85011202e-01 -7.67321646e-01 -1.67225242e-01 -5.78643799e-01 -1.20159693e-01 -1.67376101e+00 1.16649806e-01 -4.61013526e-01 -2.60709645e-03 6.62164927e-01 9.88804027e-02 9.30379987e-01 4.46486682e-01 1.94651648e-01 -3.83849621e-01 4.55324948e-01 1.57875466e+00 -1.47497267e-01 -1.49602950e-01 -1.93826422e-01 -8.39347005e-01 6.45051479e-01 6.93812072e-01 -5.61456203e-01 -5.85358500e-01 -4.61583138e-01 1.09224297e-01 -2.09869184e-02 3.19166034e-01 -9.49038386e-01 -1.71097994e-01 -3.06326985e-01 3.91861469e-01 -3.23892534e-01 4.02019739e-01 -9.39062774e-01 7.92230844e-01 4.95385021e-01 2.78753728e-01 7.55595490e-02 2.02495858e-01 3.12143445e-01 -3.60481769e-01 -1.58607945e-01 1.26588750e+00 -2.97934860e-01 -4.35061604e-01 1.17462113e-01 -1.79860368e-01 5.98557070e-02 1.35450816e+00 -3.95076931e-01 -3.54543239e-01 -5.15401185e-01 -5.48620284e-01 -1.73971251e-01 1.10297024e+00 2.99427003e-01 3.98647368e-01 -1.49183106e+00 -7.44470298e-01 2.30292007e-01 4.60024625e-02 1.67085379e-01 1.89111680e-01 8.94947171e-01 -6.42014980e-01 1.30707920e-01 -3.81321907e-01 -7.29696691e-01 -1.30144024e+00 4.25944209e-01 3.85892034e-01 -4.73991662e-01 -7.36145437e-01 5.50645709e-01 4.95473564e-01 -2.97365546e-01 -2.61897922e-01 -3.84801812e-02 1.52120993e-01 1.53684184e-01 2.16898456e-01 7.78684989e-02 2.22077057e-01 -7.87862778e-01 -3.69139701e-01 9.47198212e-01 1.68208063e-01 -4.56673145e-01 1.43116808e+00 -1.56977355e-01 -2.94349641e-01 1.23454809e-01 7.18764782e-01 2.67890751e-01 -1.40361118e+00 -5.97349228e-03 -5.15234649e-01 -6.73111320e-01 -1.47934198e-01 -1.04826736e+00 -1.41224766e+00 6.69166207e-01 5.35648644e-01 9.71417576e-02 1.61661160e+00 3.14183161e-02 8.13545883e-01 -3.21310997e-01 4.80196357e-01 -1.10535538e+00 2.37076700e-01 3.01544577e-01 9.91025567e-01 -1.04599750e+00 7.68954307e-02 -4.97955799e-01 -7.75466263e-01 9.59394097e-01 5.16225636e-01 5.92981502e-02 1.91480950e-01 3.69942337e-01 1.57579362e-01 -1.22959793e-01 -5.02180338e-01 -3.67148548e-01 3.12994123e-01 1.00042820e+00 2.96557516e-01 -1.45768359e-01 -5.91201425e-01 -3.32403108e-02 4.62593790e-03 1.08626120e-01 6.43625498e-01 7.61675596e-01 6.52339086e-02 -1.47657800e+00 -4.00673389e-01 1.01176158e-01 -4.67047334e-01 6.86888993e-02 -5.81397831e-01 8.49481165e-01 3.78773063e-01 8.68206263e-01 -1.05141111e-01 -1.15769483e-01 3.63930255e-01 -1.24862038e-01 8.83048534e-01 -5.34630835e-01 -5.86731315e-01 2.15146258e-01 -5.00368439e-02 -5.78739107e-01 -7.55360425e-01 -6.35360479e-01 -9.90731895e-01 -2.87825108e-01 -2.54757404e-01 -2.75556743e-01 4.23212975e-01 7.36344159e-01 5.54721951e-01 7.24917531e-01 4.65937763e-01 -1.04576445e+00 -2.91088037e-02 -6.87941015e-01 -5.11421800e-01 7.06183612e-01 2.61473715e-01 -6.63421154e-01 -2.40478143e-01 4.60349381e-01]	[11.650792121887207, -0.5441509485244751]
afe0ebd8-ac22-4d22-941f-b48d7df0ea89	time-sequence-channel-inference-for-beam	1812.0122	null	http://arxiv.org/abs/1812.01220v1	http://arxiv.org/pdf/1812.01220v1.pdf	Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks	In this paper, we propose a learning-based low-overhead beam alignment method for vehicle-to-infrastructure communication in vehicular networks. The main idea is to remotely infer the optimal beam directions at a target base station in future time slots, based on the CSI of a source base station in previous time slots. The proposed scheme can reduce channel acquisition and beam training overhead by replacing pilot-aided beam training with online inference from a sequence-to-sequence neural network. Simulation results based on ray-tracing channel data show that our proposed scheme achieves a $8.86\%$ improvement over location-based beamforming schemes with a positioning error of $1$m, and is within a $4.93\%$ performance loss compared with the genie-aided optimal beamformer.	['Zhiyuan Jiang', 'Sheng Zhou', 'Zhisheng Niu', 'Sheng Chen']	2018-12-04	null	null	null	null	['neural-network-simulation']	['computer-code']	[-9.03553050e-03 4.16615695e-01 -2.80573905e-01 -4.10133421e-01 -1.05332422e+00 -1.83030546e-01 -1.52791478e-02 -3.67352694e-01 -4.83683556e-01 1.05460656e+00 -3.13700825e-01 -1.22573733e+00 -1.05272710e-01 -9.56623793e-01 -8.03490520e-01 -1.10222197e+00 -7.36543298e-01 1.42817110e-01 -4.69951555e-02 -3.91562432e-02 1.24831587e-01 2.88397074e-01 -6.05920672e-01 -5.10923088e-01 4.70887870e-01 1.12178147e+00 4.46472853e-01 7.94787049e-01 -5.57937510e-02 3.06303769e-01 -5.27396321e-01 -1.94663048e-01 2.41088361e-01 -3.81097853e-01 -1.57246310e-02 -1.75529689e-01 9.10917595e-02 -4.81451064e-01 -8.36165249e-01 8.64107907e-01 6.87923312e-01 -4.46232140e-01 3.20497483e-01 -1.45976865e+00 3.29772085e-01 7.94631839e-01 -6.53625667e-01 8.01785737e-02 -8.16272050e-02 -9.03451666e-02 5.81923306e-01 -7.87432134e-01 2.77163655e-01 9.32971418e-01 9.92262363e-01 2.90842354e-01 -3.96134347e-01 -1.54755712e+00 -3.25109243e-01 6.03822231e-01 -1.85559118e+00 -7.92034507e-01 5.52554131e-01 -1.34154812e-01 5.35333097e-01 6.03213534e-02 4.73499417e-01 1.50764555e-01 2.82051891e-01 5.41395485e-01 5.50954401e-01 -4.12094444e-01 3.21794420e-01 -2.69329417e-02 -3.53842825e-01 1.00845611e+00 6.50225878e-01 2.87364721e-01 -2.60721833e-01 -7.14314654e-02 5.97069025e-01 -5.24780273e-01 -3.46505046e-01 -1.94071189e-01 -7.76967824e-01 8.44291329e-01 5.10862052e-01 1.24433130e-01 -4.24699217e-01 6.81043923e-01 -1.37854695e-01 3.34255815e-01 1.82451025e-01 -1.31402791e-01 -2.87886888e-01 4.22062799e-02 -9.46495950e-01 2.26793945e-01 6.60585344e-01 1.56305981e+00 8.62812340e-01 6.46798551e-01 -1.46476388e-01 2.82135963e-01 1.02905524e+00 1.32945073e+00 -6.06578410e-01 -9.39879417e-01 8.74424756e-01 -5.06803572e-01 2.35452756e-01 -8.29618037e-01 -8.60179186e-01 -1.27974772e+00 -1.13490236e+00 2.33795568e-02 2.45432347e-01 -9.60577428e-01 -7.57084489e-01 1.70549595e+00 2.95035690e-01 7.05082953e-01 4.39991415e-01 5.34421265e-01 4.89180654e-01 8.20727050e-01 -4.13287193e-01 -6.70654655e-01 7.31521010e-01 -6.37069404e-01 -8.68122339e-01 -3.34132493e-01 9.00186777e-01 -6.77776456e-01 -2.23330513e-01 2.30173439e-01 -1.16816640e+00 -3.11404407e-01 -1.39911485e+00 9.96936738e-01 2.69231290e-01 1.46747932e-01 4.98514324e-01 1.49366736e+00 -1.17393160e+00 -3.96744817e-01 -3.78899306e-01 6.71767304e-03 5.64977050e-01 3.57859135e-01 3.00820410e-01 -2.29865119e-01 -1.09492981e+00 4.78743345e-01 1.64605707e-01 2.33235180e-01 -7.89580822e-01 -1.01387858e+00 -9.56309021e-01 -5.41541912e-02 2.46239662e-01 -4.17684317e-01 1.43238664e+00 1.70126557e-01 -1.36251950e+00 -3.97766888e-01 -9.61478353e-01 -8.69365752e-01 -8.03800207e-03 3.61784428e-01 -4.82371479e-01 -6.79104775e-02 1.66782454e-01 2.51503319e-01 3.10174197e-01 -1.50468075e+00 -1.21273136e+00 -2.25038752e-02 -2.12893218e-01 -1.53766662e-01 9.25394669e-02 -4.77292329e-01 -6.88422620e-01 -3.07511061e-01 5.57317913e-01 -1.15263271e+00 -6.83657885e-01 -2.31258109e-01 -4.53387558e-01 1.48440972e-01 8.40370417e-01 -5.84516406e-01 1.19191515e+00 -1.68055356e+00 -4.41108286e-01 9.75238144e-01 -4.69580404e-02 1.57578960e-01 -1.08058557e-01 3.75795603e-01 3.45633656e-01 -9.88558009e-02 2.23627776e-01 -3.96677822e-01 -4.24751222e-01 1.02062583e-01 -1.39429986e-01 6.74886942e-01 -7.07545340e-01 5.86291909e-01 -8.47077012e-01 -1.59085527e-01 1.04722641e-01 3.34116071e-01 -7.47905612e-01 -5.76291718e-02 3.33545476e-01 7.21400619e-01 -4.61746514e-01 4.97253418e-01 1.24498653e+00 7.28586167e-02 4.85288113e-01 -1.56496391e-01 -3.41217846e-01 9.45996344e-02 -1.10223854e+00 1.52762246e+00 -9.26795065e-01 1.02894175e+00 4.48106974e-01 -9.46056604e-01 5.80982685e-01 6.17678165e-01 5.57921708e-01 -1.02314651e+00 3.10924351e-01 1.62617162e-01 2.22669393e-01 -2.50810504e-01 3.00046176e-01 3.95020097e-02 -2.11773947e-01 3.16223443e-01 -7.11039007e-02 1.40001878e-01 -6.55232221e-02 2.15486497e-01 1.18895078e+00 -6.39828265e-01 9.31670051e-03 -1.04169976e-02 6.64413750e-01 -3.11991185e-01 7.49023080e-01 1.05368292e+00 4.08326447e-01 -2.70510644e-01 -2.29476348e-01 2.82046854e-01 -9.43334818e-01 -8.34741771e-01 -3.03709507e-03 6.09985590e-01 4.71101016e-01 -2.70841390e-01 -4.59286034e-01 -1.63362995e-01 2.19428670e-02 1.05605984e+00 -2.06665527e-02 1.99772120e-01 -5.73183060e-01 -5.82330883e-01 7.16837347e-01 3.28656137e-01 7.32997477e-01 2.94131815e-01 -1.42216370e-01 4.31818306e-01 -9.49124619e-02 -1.21778989e+00 -2.17761453e-02 -1.41472504e-01 -3.38513732e-01 -7.54596829e-01 -5.81183434e-01 -7.12298870e-01 6.65021300e-01 9.04606640e-01 3.97906512e-01 2.63709068e-01 2.60282010e-01 9.24436375e-02 -3.06741923e-01 -7.19836056e-01 -1.81224227e-01 -4.90584821e-02 1.64400667e-01 -3.28002637e-03 -1.17416561e-01 -3.06976467e-01 -5.85703433e-01 4.37470347e-01 1.18432589e-01 1.13419099e-02 6.90262556e-01 6.69673681e-01 8.98452848e-02 5.26821494e-01 6.17405951e-01 -3.12292129e-01 3.02999634e-02 -7.41714597e-01 -1.01473820e+00 -2.14501843e-01 -5.51889122e-01 -1.63549662e-01 1.72905669e-01 6.38479769e-01 -1.15799940e+00 -2.63624787e-02 -7.52947927e-01 1.24450348e-01 3.89273763e-01 5.11507213e-01 -4.18387264e-01 -8.17003191e-01 1.13717400e-01 2.05984399e-01 -3.04248393e-01 -6.65805265e-02 3.38086545e-01 7.99802005e-01 4.55673277e-01 7.26603419e-02 1.54409957e+00 5.37187219e-01 4.06164110e-01 -1.13740599e+00 -2.80925691e-01 -5.76560318e-01 -1.65370539e-01 -5.51176548e-01 2.44749710e-01 -1.41679287e+00 -9.15685892e-01 2.44336590e-01 -1.26757693e+00 -3.36321235e-01 6.20683789e-01 8.62352550e-01 -3.56438488e-01 2.13725403e-01 -9.20408517e-02 -1.27466357e+00 -2.50416845e-01 -1.01026642e+00 5.14820039e-01 1.59909636e-01 2.26244181e-01 -8.40994000e-01 -4.83576834e-01 9.03456509e-02 8.19896758e-01 -1.43699035e-01 5.87199032e-01 7.15347182e-04 -1.16228831e+00 -2.18186215e-01 -3.07067931e-01 -3.70540679e-01 -3.63096669e-02 -8.35325420e-01 -6.28906012e-01 -6.83197975e-01 -3.51127297e-01 3.41019958e-01 5.42486131e-01 8.26187968e-01 9.59690869e-01 -5.02617240e-01 -1.01041317e+00 7.93445826e-01 1.48012149e+00 8.31437588e-01 7.55637109e-01 -2.83685531e-02 4.66553599e-01 -3.08448851e-01 8.72097969e-01 5.67173183e-01 7.02386081e-01 7.74284601e-01 6.51523650e-01 -1.13577733e-03 -1.12105869e-01 -1.92276210e-01 -1.40317142e-01 4.17110860e-01 2.46531978e-01 -7.78101742e-01 -6.38289154e-01 5.76522708e-01 -1.51364601e+00 -1.02873695e+00 -4.68256205e-01 2.03055835e+00 4.78998244e-01 4.30596977e-01 -2.96279192e-01 2.53249824e-01 3.50159675e-01 6.94414973e-02 -2.06953615e-01 -7.14976341e-02 1.27750739e-01 1.25644684e-01 1.63945150e+00 1.01664495e+00 -6.34794116e-01 5.90521932e-01 5.74113941e+00 1.15921092e+00 -1.07701373e+00 4.70579505e-01 2.75037885e-01 7.48515427e-02 -5.09402275e-01 -2.43233740e-01 -1.03655601e+00 4.43163037e-01 1.04538250e+00 -2.38112971e-01 -1.15054652e-01 5.14347315e-01 7.67848670e-01 -4.38182324e-01 -7.85526276e-01 1.05241668e+00 -2.55141836e-02 -2.06164646e+00 -5.48491240e-01 3.51076812e-01 6.22595191e-01 1.11878470e-01 5.75048896e-03 4.54189144e-02 4.14048821e-01 -7.05033362e-01 6.53676212e-01 2.45946050e-01 8.16072285e-01 -1.07939696e+00 9.07725573e-01 4.37888950e-01 -1.54928553e+00 -2.76665300e-01 -2.25421283e-02 -8.25267434e-02 8.68645132e-01 8.29273164e-01 -1.58348012e+00 8.78274858e-01 4.11396831e-01 4.13814150e-02 2.91570783e-01 1.74215066e+00 -3.63294542e-01 1.31021452e+00 -4.62283820e-01 -2.88015455e-01 3.62664312e-01 1.27495289e-01 6.97297871e-01 1.28840864e+00 9.67643380e-01 4.65493292e-01 3.83370407e-02 -2.88153496e-02 1.08256765e-01 -2.51603216e-01 -5.55106461e-01 9.23741400e-01 1.19648957e+00 8.91956449e-01 -1.69690400e-01 -1.82280764e-01 -4.43556815e-01 3.73827487e-01 -5.48306048e-01 7.22382843e-01 -8.88092816e-01 -6.68020010e-01 7.57981002e-01 -8.73543397e-02 7.09370255e-01 -9.14447069e-01 -6.41537189e-01 1.15656685e-02 -2.96726644e-01 -1.03034422e-01 -3.51787776e-01 -4.67970848e-01 -2.10851416e-01 1.23030216e-01 -2.66040862e-01 -1.36902869e+00 -4.08510029e-01 -1.28046960e-01 -5.91371000e-01 9.75495517e-01 -1.79909611e+00 -8.91735733e-01 -1.99315369e-01 2.04902366e-01 2.85868704e-01 -5.11268854e-01 4.64658827e-01 7.02520907e-01 -2.52048701e-01 1.17127860e+00 5.33330142e-01 3.74467820e-01 -1.05283342e-01 -4.67724025e-01 2.79348850e-01 9.70535159e-01 -2.74546653e-01 2.46135116e-01 1.00382280e+00 -4.34658945e-01 -1.92047310e+00 -1.41624117e+00 1.07046223e+00 4.23152089e-01 2.82269567e-01 -2.16544643e-01 -2.04971075e-01 5.22013366e-01 6.25586867e-01 -5.19880652e-01 9.02176380e-01 -1.46798119e-01 1.58541262e-01 -3.25136453e-01 -1.22013772e+00 5.42618394e-01 1.20406520e+00 1.19251326e-01 2.98355937e-01 3.24896216e-01 1.89247474e-01 -7.92618632e-01 -3.44282955e-01 5.37806749e-01 6.09912992e-01 -3.25580418e-01 9.68240201e-01 2.07586974e-01 -6.46881342e-01 -5.49701691e-01 -3.46496642e-01 -1.32971466e+00 -5.07645905e-01 -9.83633101e-01 2.34029084e-01 8.03833783e-01 8.38946283e-01 -4.82694805e-01 1.23818398e+00 -1.53007910e-01 -1.59282029e-01 -5.00930130e-01 -1.54519331e+00 -5.87554753e-01 -3.04637432e-01 -1.24121475e+00 7.01086640e-01 1.09772116e-01 -2.03012139e-01 3.31048608e-01 -6.54347837e-01 1.29362214e+00 1.23392141e+00 -3.46557677e-01 1.29368067e+00 -7.53398716e-01 -1.72233254e-01 -8.09750855e-02 -3.54782820e-01 -1.86852431e+00 1.87225893e-01 -5.70618153e-01 5.29791534e-01 -1.64578080e+00 -4.73947674e-01 -1.26684475e+00 3.68245840e-02 2.54720569e-01 2.61481971e-01 4.45603371e-01 -3.66901536e-03 -4.95929748e-01 -3.49954039e-01 4.64713663e-01 8.61432433e-01 -3.58600527e-01 1.80962965e-01 6.87715173e-01 -5.91284573e-01 6.41631603e-01 1.06570113e+00 -2.50560582e-01 -6.23059630e-01 -6.84949219e-01 4.79602180e-02 8.09098423e-01 1.57189652e-01 -1.39975011e+00 5.42447090e-01 -1.79131135e-01 1.31286353e-01 -1.11900651e+00 5.67666233e-01 -1.09104061e+00 2.15756685e-01 8.87142360e-01 2.51866668e-01 -5.65079153e-01 3.57066065e-01 8.07813704e-01 2.94915527e-01 -1.47547424e-02 4.20746654e-01 5.56104660e-01 -9.80975091e-01 3.42262059e-01 -8.49969625e-01 -5.78805864e-01 1.12474680e+00 -1.97149709e-01 -1.22296410e-02 -1.02897966e+00 -7.66225979e-02 7.65471816e-01 -3.50971729e-01 1.86276883e-01 6.60093486e-01 -1.24057281e+00 -8.44252110e-01 3.26293319e-01 -8.18902850e-02 -4.79715973e-01 3.72544497e-01 6.16789281e-01 -1.28558204e-01 1.36495495e+00 3.06850791e-01 -8.06544662e-01 -1.48929453e+00 -4.58938777e-01 3.30353320e-01 3.16808581e-01 -5.75037487e-02 1.36309755e+00 -2.88488597e-01 7.88188800e-02 3.86084795e-01 6.74645901e-02 4.61396016e-02 -5.65151691e-01 5.63467085e-01 2.96805561e-01 2.49307454e-01 -7.39071548e-01 -2.49645814e-01 6.59084022e-01 3.83330613e-01 -4.51948404e-01 7.59181261e-01 -6.23796940e-01 3.18558812e-01 -3.78305346e-01 1.19279242e+00 3.28568161e-01 -1.02568889e+00 -5.12135923e-01 -3.34476054e-01 -7.89236605e-01 5.09669662e-01 -4.95494664e-01 -1.37745261e+00 4.11968410e-01 8.71654868e-01 -1.53169498e-01 8.25951338e-01 9.18244419e-04 8.83104742e-01 5.43631315e-01 1.28260589e+00 -7.69350350e-01 -5.28717339e-01 6.02245688e-01 2.72004068e-01 -7.91475594e-01 -1.51656136e-01 -6.45738065e-01 2.90411353e-01 7.75943518e-01 3.68244588e-01 5.84212422e-01 1.16808116e+00 5.42602241e-01 8.68396163e-02 -5.89837730e-02 -3.78652930e-01 -3.79568338e-01 -2.96068430e-01 7.88845539e-01 -5.62269539e-02 1.33541480e-01 -4.32551205e-01 1.68249309e-01 -4.54456151e-01 1.78648625e-02 4.35850948e-01 1.04496658e+00 -1.07077861e+00 -1.25060308e+00 -6.36694133e-01 4.91761804e-01 -1.14133805e-02 -6.70391023e-02 8.67437780e-01 4.99923527e-01 2.73770303e-01 1.58370769e+00 2.47759983e-01 -7.00299025e-01 2.27012292e-01 -4.37140375e-01 3.71831536e-01 -2.44684324e-01 8.11338246e-01 9.08840820e-02 5.95477164e-01 -3.95581841e-01 -2.66576856e-01 -4.60592777e-01 -1.53794634e+00 -4.78046477e-01 -1.47458583e-01 6.69657469e-01 9.91755962e-01 1.21145654e+00 3.71864080e-01 6.55169487e-01 1.28096473e+00 -9.33856964e-01 1.29495412e-01 -6.23231113e-01 -4.29196239e-01 -9.50447142e-01 6.16758347e-01 -6.59210026e-01 2.86867637e-02 -4.04479176e-01]	[6.27890682220459, 1.219303011894226]
d8d4bab0-69f6-458c-8a8e-22071b54aebc	robin-a-benchmark-for-robustness-to	2111.14341	null	https://arxiv.org/abs/2111.14341v4	https://arxiv.org/pdf/2111.14341v4.pdf	OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images	Enhancing the robustness of vision algorithms in real-world scenarios is challenging. One reason is that existing robustness benchmarks are limited, as they either rely on synthetic data or ignore the effects of individual nuisance factors. We introduce OOD-CV, a benchmark dataset that includes out-of-distribution examples of 10 object categories in terms of pose, shape, texture, context and the weather conditions, and enables benchmarking models for image classification, object detection, and 3D pose estimation. In addition to this novel dataset, we contribute extensive experiments using popular baseline methods, which reveal that: 1. Some nuisance factors have a much stronger negative effect on the performance compared to others, also depending on the vision task. 2. Current approaches to enhance robustness have only marginal effects, and can even reduce robustness. 3. We do not observe significant differences between convolutional and transformer architectures. We believe our dataset provides a rich testbed to study robustness and will help push forward research in this area.	['Adam Kortylewski', 'Alan Yuille', 'Ju He', 'Angtian Wang', 'Shenxiao Mei', 'Mingxin Yu', 'Wufei Ma', 'Shaozuo Yu', 'Bingchen Zhao']	2021-11-29	null	null	null	null	['3d-pose-estimation']	['computer-vision']	[-6.37272820e-02 -5.67282498e-01 2.33353227e-01 -2.41540253e-01 -4.86111909e-01 -1.05601430e+00 9.34268951e-01 -4.11538966e-02 -5.07373333e-01 3.80081147e-01 2.56655991e-01 -6.66782781e-02 1.38023019e-01 -4.67437297e-01 -8.98723364e-01 -6.95471585e-01 -2.51487434e-01 4.76053841e-02 5.94821692e-01 -3.31344366e-01 3.58313531e-01 8.02379787e-01 -1.72092927e+00 -4.62869443e-02 4.11583513e-01 8.88210893e-01 -7.58551583e-02 8.44776094e-01 6.30539119e-01 4.42556262e-01 -9.38881099e-01 -4.21968758e-01 7.15027332e-01 -1.95997041e-02 -3.48967433e-01 4.74718101e-02 1.05273676e+00 -4.31806117e-01 -6.42303288e-01 9.59360957e-01 8.89625371e-01 2.54442003e-02 7.20733166e-01 -1.32605779e+00 -7.55915821e-01 1.43471062e-01 -6.26278222e-01 1.53753966e-01 3.02559435e-01 8.46331418e-01 6.00344837e-01 -6.10649645e-01 6.05837464e-01 1.42424381e+00 1.00181317e+00 5.75990140e-01 -1.29523504e+00 -5.28415501e-01 2.40980372e-01 9.94420126e-02 -1.06549144e+00 -6.22977614e-01 5.31919539e-01 -4.14602965e-01 8.74425828e-01 3.40553582e-01 1.99884564e-01 1.61553717e+00 1.67518154e-01 4.29488689e-01 1.24117625e+00 -1.75268367e-01 2.08801225e-01 2.26289742e-02 -5.15900888e-02 3.74143243e-01 3.75009924e-01 6.28787637e-01 -3.56072664e-01 2.73228511e-02 4.24466550e-01 -2.59109139e-01 -3.98661196e-01 -6.26195848e-01 -1.43296325e+00 4.87930834e-01 6.20596826e-01 -1.73032418e-01 1.27673447e-01 1.90741450e-01 4.96960670e-01 4.37245339e-01 1.48882553e-01 7.56325066e-01 -5.71911335e-01 -1.26292994e-02 -6.19270265e-01 7.08917379e-01 6.30078375e-01 7.75015414e-01 4.07599986e-01 8.69421214e-02 -2.95255095e-01 6.60734177e-01 1.17215797e-01 8.56005073e-01 1.19253464e-01 -1.07264698e+00 2.95537204e-01 2.22136348e-01 3.94717664e-01 -1.20112610e+00 -5.91324329e-01 -3.77708435e-01 -5.96861899e-01 7.41754472e-01 7.25938559e-01 -9.39164460e-02 -1.20663488e+00 1.79683590e+00 1.16921313e-01 7.86452740e-03 -7.23878890e-02 1.08005857e+00 1.14740789e+00 1.61491483e-01 -7.79155968e-03 2.89770722e-01 1.21016037e+00 -8.07781219e-01 -2.31523424e-01 -3.98576051e-01 1.56824872e-01 -1.22889698e+00 1.24084032e+00 3.06677848e-01 -9.13773358e-01 -6.46480381e-01 -1.02529275e+00 2.29971528e-01 -6.08337104e-01 4.75906655e-02 4.59325194e-01 8.25290382e-01 -1.08402288e+00 5.43564439e-01 -5.26193261e-01 -6.15096748e-01 2.79916614e-01 8.42459127e-02 -5.12448967e-01 -1.89359441e-01 -8.61760557e-01 1.26255381e+00 2.04765171e-01 -6.83555230e-02 -1.13388264e+00 -7.27351308e-01 -7.68544674e-01 -5.76738596e-01 3.55056316e-01 -5.87682486e-01 1.14584255e+00 -5.99232972e-01 -1.15399408e+00 7.86372364e-01 3.10756713e-01 -3.71155769e-01 9.59232628e-01 -2.07825124e-01 -3.30193937e-01 -6.79287910e-02 -1.07912436e-01 1.01882708e+00 1.06943476e+00 -1.42847157e+00 -2.19941020e-01 -2.54769295e-01 2.15511531e-01 7.99754784e-02 -1.39329135e-01 9.26821306e-02 -6.73736095e-01 -8.27295542e-01 -1.96823001e-01 -1.21821356e+00 -1.73149064e-01 1.80110738e-01 -5.17201841e-01 1.46456584e-01 1.03888845e+00 -4.40480500e-01 5.39075375e-01 -2.16839480e+00 -3.40619124e-02 -1.44079491e-01 -2.38250755e-02 3.56774896e-01 -4.71879661e-01 2.69127607e-01 -1.48625925e-01 2.71661162e-01 -6.21646270e-02 -1.31244540e-01 3.96199226e-02 -8.28624442e-02 -4.21506226e-01 6.23667240e-01 4.87935036e-01 7.52474189e-01 -5.34574687e-01 -6.82913661e-02 6.56893313e-01 4.35308605e-01 -3.60717058e-01 4.39303592e-02 -1.67732656e-01 4.84796107e-01 -4.19881716e-02 7.07249999e-01 9.85205054e-01 2.10378423e-01 -4.28486854e-01 -5.52864552e-01 -1.51532114e-01 -2.14884058e-02 -1.29926419e+00 1.24676335e+00 -2.25420654e-01 7.86338270e-01 -8.94688219e-02 -4.79949445e-01 6.62762761e-01 -9.24837515e-02 1.38777539e-01 -7.97501326e-01 9.78885740e-02 -3.96154635e-02 1.43284068e-01 -4.80798334e-01 5.52639723e-01 3.05939198e-01 5.64072765e-02 2.06299022e-01 -1.55154914e-01 -4.63476956e-01 2.78822333e-01 1.85181737e-01 1.30753088e+00 1.79257438e-01 -7.94937089e-02 -2.41343081e-01 -1.46827102e-02 -1.22433573e-01 3.25097740e-01 1.02188122e+00 -5.56172013e-01 1.13700342e+00 4.18648839e-01 -5.81781805e-01 -1.13722622e+00 -1.20015776e+00 -3.57241929e-01 7.97525585e-01 3.07353586e-01 -1.91052243e-01 -5.64655066e-01 -6.99726343e-01 1.71203613e-01 5.98326504e-01 -7.74090886e-01 -3.18907142e-01 -2.58467555e-01 -1.09138525e+00 8.02151442e-01 6.70883656e-01 5.07799745e-01 -9.07324135e-01 -8.26078475e-01 -4.08938944e-01 6.04520552e-02 -1.45443380e+00 -2.93067217e-01 -1.27365775e-02 -6.44549727e-01 -1.21431303e+00 -4.93113786e-01 -3.27186674e-01 4.42236185e-01 7.14570284e-01 1.51657701e+00 1.67220041e-01 -4.00908083e-01 5.05744159e-01 -4.49973375e-01 -7.17780888e-01 -2.51129597e-01 -1.88213706e-01 3.45997304e-01 -3.85982901e-01 7.89508373e-02 -3.50518584e-01 -7.74900675e-01 7.96828985e-01 -8.30250859e-01 -3.55569929e-01 5.38859129e-01 5.14405131e-01 2.10058093e-01 2.97456924e-02 3.88372183e-01 -3.47928613e-01 4.69816208e-01 -1.46001965e-01 -7.72660196e-01 1.17489360e-01 -3.59454960e-01 -5.47185801e-02 3.42125237e-01 -5.67862272e-01 -8.11016381e-01 1.00989401e-01 1.10726230e-01 -4.77907896e-01 -5.45439541e-01 -1.53764337e-01 -1.45921350e-01 -4.13168639e-01 1.16659009e+00 -1.39306799e-01 -1.80122301e-01 -4.33360338e-01 3.16627473e-01 2.13194355e-01 7.86017299e-01 -5.66043377e-01 1.22190201e+00 4.77282703e-01 4.92197648e-02 -9.36168492e-01 -4.86109495e-01 -1.16028480e-01 -3.93608779e-01 -1.97710156e-01 6.53161943e-01 -9.75208759e-01 -6.26029909e-01 8.73759627e-01 -1.03601313e+00 -5.04774272e-01 5.35226939e-03 5.21509409e-01 -4.21626598e-01 4.49862987e-01 -4.06553119e-01 -5.60428560e-01 6.93745166e-02 -1.42629635e+00 1.08524156e+00 3.48122001e-01 -8.22123364e-02 -6.17417932e-01 -7.19062835e-02 2.55347222e-01 5.29451251e-01 4.68027920e-01 5.74754179e-01 -2.74075419e-01 -4.92831945e-01 -2.91109204e-01 -4.70138103e-01 2.90726244e-01 -6.18090928e-02 5.44316530e-01 -1.24669659e+00 -6.04224205e-01 -3.46296877e-01 -8.21577907e-01 1.16227388e+00 3.92848313e-01 1.15747797e+00 4.67226841e-02 -6.96912035e-02 7.23419189e-01 1.29442358e+00 -3.17350030e-01 8.69191408e-01 4.29365396e-01 5.78027010e-01 6.91577911e-01 5.59100330e-01 2.37004057e-01 1.59765244e-01 9.35654759e-01 9.33209002e-01 -1.61315352e-01 -4.45166409e-01 4.41583917e-02 5.20794630e-01 -1.30705476e-01 -3.22702676e-01 -3.59695733e-01 -9.68816817e-01 4.05050725e-01 -1.51788473e+00 -8.40795159e-01 -1.27832890e-01 2.31563115e+00 5.79042196e-01 3.06804508e-01 2.79054463e-01 1.25192583e-01 6.10313237e-01 2.00152740e-01 -6.42976522e-01 -4.34660390e-02 -4.10556644e-01 -1.19647428e-01 8.33846450e-01 2.07678124e-01 -1.36805820e+00 8.78568411e-01 7.27937365e+00 5.55644512e-01 -1.31592572e+00 -3.97788316e-01 4.79290187e-01 -3.28658223e-01 1.00764763e-02 -4.34885323e-01 -7.15786159e-01 4.49448228e-01 5.68906605e-01 4.81342912e-01 4.74068522e-01 7.40964592e-01 1.80600390e-01 -3.13351572e-01 -1.18838942e+00 8.17174733e-01 2.07165539e-01 -1.02120256e+00 -2.52715081e-01 -9.39058792e-03 7.58997798e-01 4.93251771e-01 4.90600675e-01 2.06392780e-01 4.75421995e-01 -1.05363858e+00 9.19924796e-01 4.41310883e-01 7.19781339e-01 -6.53025210e-01 7.75690913e-01 1.49441049e-01 -7.56247997e-01 2.38354541e-02 -4.76917863e-01 6.16280315e-03 -3.27629924e-01 4.46293563e-01 -7.60931849e-01 2.76751995e-01 1.34318721e+00 4.15454865e-01 -1.34097946e+00 1.29271030e+00 -2.17136875e-01 5.71589768e-01 -4.18491125e-01 1.16276763e-01 1.29747298e-02 2.94378966e-01 8.26000452e-01 1.29987192e+00 1.07731283e-01 -3.02900285e-01 1.20040089e-01 6.06366217e-01 8.27259272e-02 -2.98747838e-01 -8.46345067e-01 1.98642179e-01 4.41863328e-01 1.19503176e+00 -9.56655741e-01 1.68510705e-01 -4.37792808e-01 8.02303374e-01 4.00007062e-04 3.94298315e-01 -9.43292260e-01 -2.78935820e-01 9.65383053e-01 -7.90226460e-02 4.36752319e-01 -4.26921934e-01 -4.58565176e-01 -1.16253698e+00 1.71720147e-01 -1.22327983e+00 1.59038872e-01 -9.00283635e-01 -1.35321057e+00 4.85027462e-01 8.80271718e-02 -1.17915308e+00 -1.35846943e-01 -8.90710235e-01 -6.26184821e-01 6.96132958e-01 -1.42166579e+00 -1.22192562e+00 -5.92451572e-01 5.19194424e-01 3.80994350e-01 -2.14402959e-01 7.39751458e-01 3.81585881e-02 -7.40995586e-01 8.07913840e-01 -1.77439913e-01 2.07404047e-01 1.16221774e+00 -1.14645743e+00 9.11050439e-01 1.08608699e+00 1.18071444e-01 4.95917588e-01 1.19679213e+00 -3.45893085e-01 -1.42478228e+00 -1.17284107e+00 3.02465796e-01 -1.13327682e+00 4.87791657e-01 -4.17596281e-01 -7.06637025e-01 3.18488032e-01 1.40576750e-01 3.12974006e-01 3.40813816e-01 2.00555265e-01 -9.79777992e-01 -1.08615227e-01 -1.25477362e+00 9.10846233e-01 1.11840713e+00 -2.84141243e-01 -3.51625443e-01 2.31167749e-01 8.03516090e-01 -4.92049485e-01 -5.36648870e-01 7.32452214e-01 6.74679399e-01 -1.40149200e+00 1.27999663e+00 -6.25838399e-01 4.00369734e-01 -5.93759000e-01 -4.18934107e-01 -1.56707275e+00 -3.28208953e-01 -1.75157830e-01 -1.02454135e-02 1.31034529e+00 4.70938265e-01 -4.69304740e-01 5.83539724e-01 5.98603725e-01 -5.30642308e-02 -3.78571540e-01 -5.63092649e-01 -1.06540608e+00 1.20429217e-03 -6.31525517e-01 5.70864856e-01 6.78645492e-01 -7.13405311e-01 1.28735274e-01 -5.04103720e-01 3.44708025e-01 6.34678483e-01 -1.09874785e-01 1.16646719e+00 -9.26891625e-01 -1.78402334e-01 -5.07157981e-01 -6.18048847e-01 -5.10309696e-01 -8.37116987e-02 -2.94654191e-01 1.43805578e-01 -1.05467129e+00 1.47380784e-01 -4.54645187e-01 -2.87549108e-01 4.07625049e-01 -2.38495424e-01 9.14512157e-01 3.98906946e-01 5.69178388e-02 -5.68756342e-01 2.42566451e-01 1.08455539e+00 -2.62471348e-01 3.61795276e-02 7.67385140e-02 -6.55813754e-01 6.90443218e-01 1.07444096e+00 -1.72574043e-01 -3.58113110e-01 -7.57078409e-01 1.42884612e-01 -5.78803778e-01 8.23011577e-01 -1.32309628e+00 -1.56514615e-01 -3.28220367e-01 7.26911783e-01 -3.34302366e-01 3.16539049e-01 -7.59148240e-01 -2.28712767e-01 4.08528775e-01 -1.99575692e-01 1.94464296e-01 5.28841197e-01 6.52199388e-01 1.91574439e-01 6.91636726e-02 1.03027058e+00 -3.78037207e-02 -8.65397930e-01 1.62307277e-01 -2.16036931e-01 3.04909438e-01 8.87418509e-01 -2.25554168e-01 -5.88249147e-01 -3.39686215e-01 -1.73682705e-01 -1.02979932e-02 9.60198998e-01 8.48531008e-01 3.46288145e-01 -1.26561141e+00 -9.38366652e-01 1.67537823e-01 5.12552261e-01 -2.03380659e-01 1.76688001e-01 5.67854047e-01 -5.44951677e-01 1.81797758e-01 -5.15662968e-01 -7.71951735e-01 -1.30104542e+00 7.55826116e-01 3.67888331e-01 2.04816863e-01 -2.59930700e-01 8.86236787e-01 6.66310713e-02 -6.41960323e-01 5.96663833e-01 -2.12822765e-01 4.33787145e-02 7.01362360e-03 6.11282408e-01 4.83788580e-01 4.13850695e-01 -6.73434913e-01 -5.77855885e-01 7.19906151e-01 6.86058700e-02 5.37703186e-02 1.14206982e+00 1.83313370e-01 1.99952126e-01 4.63537201e-02 8.25515449e-01 8.96508098e-02 -1.54227376e+00 -6.85592592e-02 -3.20353210e-01 -6.89015031e-01 9.86320712e-03 -1.12680364e+00 -1.16273868e+00 8.58978510e-01 9.16529834e-01 9.23904404e-02 1.14375484e+00 1.25219522e-03 2.97953963e-01 5.09264529e-01 3.28438669e-01 -1.13913691e+00 3.75809431e-01 6.29987180e-01 1.17522955e+00 -1.61076081e+00 1.48348749e-01 -3.24898541e-01 -5.64505994e-01 9.09266829e-01 9.51064527e-01 -3.69065180e-02 3.43478352e-01 3.83293658e-01 4.43026900e-01 1.38909265e-01 -6.44517660e-01 -3.08287829e-01 2.99346358e-01 1.12658191e+00 3.20401013e-01 -1.04028322e-01 1.51732311e-01 -4.81811177e-04 -3.44350934e-01 -4.08324599e-01 4.19382364e-01 6.21001303e-01 -1.88775420e-01 -8.50702107e-01 -7.48061121e-01 1.88697547e-01 -3.92468035e-01 1.55396655e-01 -8.92711818e-01 8.63312542e-01 2.95751393e-01 1.09059596e+00 -2.06700653e-01 -7.37522364e-01 5.84417939e-01 -3.64013672e-01 7.25001454e-01 -3.26472461e-01 -4.72152293e-01 -3.18863213e-01 1.24559507e-01 -7.19463289e-01 -1.43384159e-01 -6.88497305e-01 -5.87835312e-01 -5.51311135e-01 -2.80573547e-01 -4.65262711e-01 7.65801609e-01 5.64268053e-01 3.08571309e-01 3.29948038e-01 4.82735753e-01 -1.32416046e+00 -7.50091791e-01 -9.89897490e-01 -9.70393345e-02 5.74056804e-01 5.26279092e-01 -8.16580176e-01 -5.15552580e-01 -5.36121614e-02]	[8.075532913208008, -1.406450629234314]
8cee172f-40ae-4ecc-9758-e6bf645935b8	on-training-sketch-recognizers-for-new	2104.0885	null	https://arxiv.org/abs/2104.08850v1	https://arxiv.org/pdf/2104.08850v1.pdf	On Training Sketch Recognizers for New Domains	Sketch recognition algorithms are engineered and evaluated using publicly available datasets contributed by the sketch recognition community over the years. While existing datasets contain sketches of a limited set of generic objects, each new domain inevitably requires collecting new data for training domain specific recognizers. This gives rise to two fundamental concerns: First, will the data collection protocol yield ecologically valid data? Second, will the amount of collected data suffice to train sufficiently accurate classifiers? In this paper, we draw attention to these two concerns. We show that the ecological validity of the data collection protocol and the ability to accommodate small datasets are significant factors impacting recognizer accuracy in realistic scenarios. More specifically, using sketch-based gaming as a use case, we show that deep learning methods, as well as more traditional methods, suffer significantly from dataset shift. Furthermore, we demonstrate that in realistic scenarios where data is scarce and expensive, standard measures taken for adapting deep learners to small datasets fall short of comparing favorably with alternatives. Although transfer learning, and extensive data augmentation help deep learners, they still perform significantly worse compared to standard setups (e.g., SVMs and GBMs with standard feature representations). We pose learning from small datasets as a key problem for the deep sketch recognition field, one which has been ignored in the bulk of the existing literature.	['T. Metin Sezgin', 'Kemal Tugrul Yesilbek']	2021-04-18	null	null	null	null	['sketch-recognition']	['computer-vision']	[ 3.46469611e-01 -2.68105209e-01 -2.18606949e-01 -3.49349678e-01 -6.62843287e-01 -9.90145922e-01 7.15454996e-01 -1.24524593e-01 -5.69050074e-01 8.48007321e-01 8.74463171e-02 -3.35326791e-01 -1.74732700e-01 -8.56327176e-01 -8.26206625e-01 -2.99686998e-01 1.15400322e-01 5.77507675e-01 -8.56495053e-02 -2.20709071e-01 4.93895859e-01 8.27557981e-01 -1.67964315e+00 1.33070379e-01 6.99204087e-01 1.04305744e+00 2.57700160e-02 5.66177249e-01 -2.94798225e-01 3.39396000e-01 -6.81099176e-01 -5.56110263e-01 4.30769026e-01 -1.20330909e-02 -7.76736379e-01 2.94406973e-02 1.10722446e+00 -7.52633989e-01 -3.21945667e-01 5.80928326e-01 5.46828270e-01 2.26820096e-01 7.05440938e-01 -1.45687628e+00 -7.60611653e-01 2.58906335e-01 -6.36704117e-02 7.59901404e-02 2.00406805e-01 3.00928593e-01 1.03856647e+00 -1.05464149e+00 7.07745016e-01 9.49889421e-01 1.02688766e+00 7.82802045e-01 -1.51538932e+00 -9.33485031e-01 2.40177542e-01 -1.63827494e-01 -1.16170549e+00 -7.22728789e-01 9.68759954e-01 -4.51580733e-01 6.32631898e-01 3.40027362e-01 7.22634733e-01 1.73405552e+00 -3.88478667e-01 8.67938519e-01 1.14574802e+00 -2.87026614e-01 4.25097227e-01 3.27759027e-01 4.82925586e-02 4.44540888e-01 6.68592513e-01 2.86984384e-01 -5.94936728e-01 -2.34241709e-01 9.97661829e-01 1.05248168e-01 2.58936677e-02 -6.44833922e-01 -9.65591371e-01 6.45260930e-01 1.01293378e-01 3.02180439e-01 -1.69438973e-01 1.26499534e-01 5.00927210e-01 5.24834394e-01 2.35715881e-01 7.73822546e-01 -5.24778962e-01 -3.99662375e-01 -9.53551173e-01 6.86372697e-01 9.11679685e-01 1.02334654e+00 7.11799741e-01 2.59785563e-01 2.40894392e-01 9.51455534e-01 -2.03682542e-01 3.46881270e-01 4.95914519e-01 -7.60496676e-01 5.22740483e-01 4.90457594e-01 1.18983582e-01 -1.03306341e+00 -1.27233773e-01 -3.85195374e-01 -6.32728040e-01 3.69774759e-01 1.02254987e+00 -1.23870395e-01 -7.52105117e-01 1.89329565e+00 -3.78266387e-02 8.72673839e-02 -1.83594853e-01 8.27952206e-01 7.25868046e-01 1.84009314e-01 2.13993922e-01 3.48548919e-01 9.08555388e-01 -4.94546264e-01 -2.38466054e-01 -5.05910218e-01 3.91299993e-01 -6.04512990e-01 1.71346796e+00 5.64489484e-01 -9.52916265e-01 -6.58713043e-01 -1.10438359e+00 -4.01368178e-02 -7.30069757e-01 5.40805832e-02 1.00402081e+00 8.67615223e-01 -8.35744321e-01 8.05844665e-01 -2.85610199e-01 -8.23266447e-01 8.19395363e-01 3.14268589e-01 -6.82834029e-01 -3.04536521e-01 -9.43326473e-01 9.40469444e-01 2.73983907e-02 -5.90646453e-02 -8.01620960e-01 -8.38763177e-01 -5.23753107e-01 1.65630672e-02 3.58487993e-01 -4.21571910e-01 1.27522767e+00 -1.30805111e+00 -1.18456602e+00 8.96588862e-01 2.01324895e-01 -1.97148353e-01 6.99860096e-01 -1.68567106e-01 -1.34719148e-01 -2.99295664e-01 -1.34359360e-01 6.14669740e-01 7.27329552e-01 -1.37726104e+00 -5.05608857e-01 -5.19427478e-01 2.16864422e-01 2.74255760e-02 -5.24353087e-01 -2.08018154e-01 -4.62501589e-03 -8.59817922e-01 -2.37482339e-01 -8.60319078e-01 -3.97653598e-03 3.59295577e-01 2.48441458e-01 -1.56639069e-01 7.91955709e-01 -4.31043535e-01 9.26408470e-01 -1.99258566e+00 -6.87049478e-02 1.96215823e-01 1.81525171e-01 4.59906369e-01 -3.07925820e-01 5.01210928e-01 3.36889252e-02 3.36772263e-01 -1.67719781e-01 -7.94569626e-02 1.84667498e-01 2.97408700e-01 -5.70885777e-01 1.78057894e-01 3.50854367e-01 1.02661633e+00 -7.38544583e-01 -2.32249826e-01 9.87804905e-02 2.43823767e-01 -5.21644652e-01 2.46671811e-01 -4.61329222e-02 1.25966445e-01 -2.84199655e-01 8.38137984e-01 5.82748413e-01 1.97043251e-02 1.41830727e-01 2.45695300e-02 6.00175895e-02 1.83550343e-01 -1.24284136e+00 1.73616743e+00 -4.84104812e-01 7.83545315e-01 -5.19430675e-02 -1.17556703e+00 1.02091217e+00 8.58112890e-03 2.98177600e-01 -7.38197267e-01 -7.68370032e-02 4.60866839e-01 4.37061265e-02 -3.60169888e-01 4.78861451e-01 -4.59297866e-01 -7.22140595e-02 6.34697914e-01 2.69606978e-01 -1.95713565e-01 -7.95788392e-02 -8.67457613e-02 1.13075995e+00 1.63384348e-01 -1.10021979e-02 -2.40975797e-01 -7.63875246e-02 1.48294449e-01 3.95510584e-01 9.07736123e-01 -3.84109139e-01 7.50967085e-01 3.65356028e-01 -8.23490083e-01 -1.44887745e+00 -1.16311061e+00 -1.74502805e-01 1.35600293e+00 -9.64354500e-02 -1.97751999e-01 -6.44973695e-01 -7.68917024e-01 5.52039087e-01 4.61943477e-01 -7.97133386e-01 -2.46152818e-01 -4.42417622e-01 -4.51211035e-01 8.98986697e-01 9.27391708e-01 2.61703372e-01 -1.13515925e+00 -6.56883419e-01 2.08224565e-01 2.47759417e-01 -9.18699205e-01 -1.63195774e-01 1.21330775e-01 -1.06844962e+00 -1.14337802e+00 -8.85337651e-01 -7.00527072e-01 5.57536483e-01 3.22811127e-01 1.24794543e+00 1.86650246e-01 -3.62886012e-01 8.20203781e-01 -1.67336822e-01 -6.01031244e-01 -1.87029392e-01 3.27768832e-01 7.15097412e-02 -1.15923293e-01 4.73202139e-01 -8.47612381e-01 -4.24896091e-01 2.75199622e-01 -9.70507920e-01 1.64230894e-02 8.20671618e-01 9.81940210e-01 -1.44584174e-03 -3.92322809e-01 8.83261800e-01 -1.04122758e+00 1.01722860e+00 -3.72777522e-01 -3.85309249e-01 3.83753777e-01 -6.63804531e-01 1.96085265e-03 6.23298526e-01 -8.46747696e-01 -8.25117826e-01 -1.00523844e-01 5.42706922e-02 -3.90667975e-01 -4.81983423e-01 3.52043718e-01 -2.23417610e-01 -2.57606417e-01 9.97161150e-01 1.64466232e-01 2.14525864e-01 -6.09824181e-01 2.30043918e-01 5.49505889e-01 2.86014348e-01 -1.22534609e+00 9.45713103e-01 3.19022179e-01 -1.90750718e-01 -9.92674053e-01 -3.27403158e-01 5.61908185e-02 -8.09630990e-01 -2.76506245e-01 1.59279957e-01 -6.65484309e-01 -5.54818809e-01 3.81209522e-01 -8.97163749e-01 -5.98961532e-01 -5.09590864e-01 1.88055009e-01 -6.08115792e-01 9.84655023e-02 -2.85253048e-01 -9.08838212e-01 -2.12206587e-01 -1.02256680e+00 7.84289658e-01 1.22460328e-01 -5.66504419e-01 -9.49331880e-01 1.49379373e-02 2.53416270e-01 7.60905266e-01 3.39815348e-01 8.54260504e-01 -7.75670528e-01 -5.20866096e-01 -4.29123938e-01 -2.93786585e-01 4.09426570e-01 1.84032485e-01 3.24025750e-02 -1.19614148e+00 -2.70930260e-01 -3.15063983e-01 -8.44414771e-01 6.75002992e-01 -1.57275513e-01 1.29154122e+00 -2.89801091e-01 -8.93095359e-02 5.10416269e-01 1.24961674e+00 1.43266782e-01 5.25803268e-01 3.10744077e-01 6.63006067e-01 6.84513271e-01 2.42623553e-01 2.54202843e-01 1.52846858e-01 6.59791768e-01 -7.55651593e-02 5.63523695e-02 -1.04843937e-01 -5.85465074e-01 6.92655444e-02 3.68271172e-01 -4.93232980e-02 9.30033401e-02 -1.29320014e+00 5.86708426e-01 -1.64975643e+00 -9.59204495e-01 5.40435791e-01 2.43877864e+00 7.47146785e-01 1.30293682e-01 5.18221498e-01 2.91750431e-01 2.83433050e-01 5.41370660e-02 -7.98696876e-01 -3.44862640e-01 -1.85611054e-01 4.77642745e-01 2.75851101e-01 1.78961039e-01 -9.31850791e-01 8.35172713e-01 6.59580851e+00 6.17345214e-01 -1.37248886e+00 -1.99965253e-01 5.91644585e-01 -1.67305335e-01 -3.96851927e-01 -7.64028728e-02 -3.65684271e-01 3.78746390e-01 8.06251049e-01 -1.39493421e-01 7.96590567e-01 9.74747896e-01 -2.89359242e-01 6.77334145e-02 -1.56080794e+00 1.22180915e+00 9.91999060e-02 -1.37083113e+00 1.65134445e-01 1.29817858e-01 5.28181612e-01 -1.94402948e-01 3.24471533e-01 6.02556229e-01 1.99509308e-01 -1.41076481e+00 7.59359777e-01 3.32187384e-01 1.07968199e+00 -5.66295922e-01 2.84246117e-01 2.15191483e-01 -8.26826274e-01 -1.46899164e-01 -4.81092244e-01 -3.42357546e-01 -5.02115369e-01 1.33997887e-01 -7.67713368e-01 -2.38479450e-02 4.71727103e-01 5.76224208e-01 -8.05632830e-01 8.81407380e-01 1.70367673e-01 6.54747903e-01 -3.13999474e-01 -2.24361971e-01 1.42303243e-01 2.40788832e-02 1.43047035e-01 1.17878270e+00 1.25754684e-01 -3.50492224e-02 -2.32718885e-01 9.63117480e-01 -2.71283120e-01 6.82732882e-03 -1.20951223e+00 -3.80685866e-01 5.31338394e-01 1.06178749e+00 -4.63445544e-01 -1.88183978e-01 -4.90046114e-01 8.04603517e-01 7.23713934e-01 5.34745693e-01 -3.32454622e-01 -2.81891733e-01 9.41181660e-01 3.42842370e-01 5.36222868e-02 -2.27150694e-01 -8.10960233e-01 -1.28759646e+00 3.49481463e-01 -1.26741564e+00 2.74280459e-01 -4.58030403e-01 -1.56703413e+00 1.38612434e-01 -1.40944257e-01 -1.00960350e+00 -8.00648108e-02 -9.63092446e-01 -6.77495241e-01 8.03901196e-01 -1.25314152e+00 -1.16507900e+00 -4.00072068e-01 3.92384738e-01 6.46387815e-01 -4.31014448e-01 1.01195419e+00 4.16568339e-01 -4.41723078e-01 9.42851663e-01 2.04030439e-01 3.86926383e-01 8.18575084e-01 -1.15916991e+00 7.99392223e-01 4.31284487e-01 4.59543556e-01 8.87526095e-01 4.38117623e-01 -5.14898658e-01 -1.78446734e+00 -7.29855895e-01 4.79764789e-01 -8.00256371e-01 4.63700354e-01 -8.86035204e-01 -1.09615922e+00 6.47475123e-01 -3.35332870e-01 2.52301455e-01 8.10995877e-01 5.87550700e-01 -7.52067029e-01 -2.51797795e-01 -1.25963986e+00 6.22245252e-01 1.39573228e+00 -8.07197034e-01 -5.61417937e-01 1.76096018e-02 9.12105367e-02 -2.23908722e-01 -7.90096819e-01 2.72398710e-01 1.40430260e+00 -8.69125724e-01 1.12944829e+00 -1.35911059e+00 5.68980336e-01 2.89969385e-01 -3.76997292e-01 -1.19461346e+00 -1.39231205e-01 -3.32493305e-01 3.16848420e-02 1.30954695e+00 3.31044286e-01 -4.77838635e-01 1.25866997e+00 1.21621060e+00 3.42210978e-01 -8.02311599e-01 -6.53332353e-01 -1.01857495e+00 6.98392034e-01 -6.62734628e-01 7.54791617e-01 1.23203766e+00 -1.15590043e-01 2.28258461e-01 -2.18397155e-01 -3.14406216e-01 6.36038780e-01 6.70197457e-02 1.32584727e+00 -1.68473148e+00 -5.42657496e-03 -7.59121716e-01 -4.40742910e-01 -7.32054889e-01 2.58335263e-01 -8.31454635e-01 -2.56707937e-01 -1.35091734e+00 4.61124592e-02 -9.85988319e-01 -3.04473102e-01 3.85689825e-01 -1.04755133e-01 1.05761111e-01 4.33598429e-01 1.14613019e-01 -3.13763827e-01 3.14754248e-01 8.96421552e-01 -2.36493081e-01 3.82497832e-02 -5.41367754e-02 -8.92903209e-01 5.10280669e-01 8.16837192e-01 -2.14830860e-01 -5.34393132e-01 -5.85546494e-01 1.36094138e-01 -3.50489527e-01 5.50985992e-01 -1.05065298e+00 1.62416741e-01 -4.56368923e-01 7.84563243e-01 -1.34715540e-02 3.71882051e-01 -1.08272183e+00 3.43165100e-02 1.95753723e-01 -5.74861825e-01 -1.11195762e-02 6.19913578e-01 4.57659155e-01 8.72943476e-02 -2.12787271e-01 6.15751266e-01 -1.86838731e-01 -7.49179423e-01 3.26875269e-01 -2.04375312e-01 4.01892334e-01 7.73595810e-01 -6.43485487e-01 -2.21237496e-01 -3.41686696e-01 -3.28340501e-01 -1.82232380e-01 7.01496959e-01 7.14681208e-01 6.38426363e-01 -1.53531790e+00 -5.64963222e-01 4.28101331e-01 3.88025612e-01 -1.04131579e-01 -4.26788814e-02 1.97697699e-01 -2.47718900e-01 2.41574198e-01 -6.22080266e-01 -2.36035481e-01 -9.28518951e-01 4.74509835e-01 1.77241325e-01 1.38351530e-01 -4.22067195e-01 7.26238668e-01 1.60322070e-01 -7.37546444e-01 5.37510157e-01 -3.64331990e-01 3.28511298e-01 1.63667247e-01 3.50179851e-01 3.51499975e-01 1.23122543e-01 -2.20002428e-01 -2.24607751e-01 3.21118027e-01 -1.52789026e-01 -1.50679171e-01 1.56529510e+00 5.52826524e-01 5.95350206e-01 6.24408305e-01 1.11175108e+00 -1.45491928e-01 -1.35554326e+00 -2.63546616e-01 1.48613110e-01 -7.53454745e-01 -2.42471844e-01 -1.03975284e+00 -8.98205578e-01 1.12477577e+00 5.43875098e-01 8.27427953e-02 7.63725460e-01 -3.24567705e-01 6.16245568e-01 6.94516420e-01 4.83065605e-01 -1.14110529e+00 1.05138093e-01 3.88163835e-01 1.06710386e+00 -1.50499558e+00 -4.80432957e-02 2.50801861e-01 -5.34882784e-01 1.18936467e+00 8.31935346e-01 -1.87741533e-01 3.65790278e-01 2.32113466e-01 -2.50026807e-02 1.98666975e-02 -7.05023468e-01 3.20625901e-02 1.71191588e-01 8.58935356e-01 3.93398225e-01 -9.91775692e-02 1.13978016e-03 6.70451522e-01 -2.74803549e-01 2.46082440e-01 2.80883163e-01 9.24550593e-01 -3.52355778e-01 -1.26735342e+00 -4.03992623e-01 8.08101714e-01 -7.16974679e-03 1.61841601e-01 -8.54619861e-01 1.13103628e+00 9.59397331e-02 4.63527739e-01 1.04235344e-01 -4.44445670e-01 5.82807124e-01 3.33584726e-01 7.55425096e-01 -5.56571603e-01 -6.36318803e-01 -6.66495502e-01 4.62869741e-02 -2.00475693e-01 5.66499569e-02 -8.26768339e-01 -5.59300065e-01 -5.18364012e-01 -6.81628287e-02 -1.66040331e-01 6.89985096e-01 8.03373098e-01 2.55643338e-01 -1.25046028e-02 2.71688908e-01 -9.01297987e-01 -8.08033347e-01 -8.10783565e-01 -4.61072892e-01 7.11358964e-01 3.01210105e-01 -8.31637859e-01 -2.36671641e-01 -1.33444801e-01]	[9.97230052947998, 2.5305545330047607]
6fcc621d-70b3-4834-9dce-2e1b8f217af0	material-recognition-from-local-appearance-in	1611.09394	null	http://arxiv.org/abs/1611.09394v3	http://arxiv.org/pdf/1611.09394v3.pdf	Material Recognition from Local Appearance in Global Context	Recognition of materials has proven to be a challenging problem due to the wide variation in appearance within and between categories. Global image context, such as where the material is or what object it makes up, can be crucial to recognizing the material. Existing methods, however, operate on an implicit fusion of materials and context by using large receptive fields as input (i.e., large image patches). Many recent material recognition methods treat materials as yet another set of labels like objects. Materials are, however, fundamentally different from objects as they have no inherent shape or defined spatial extent. Approaches that ignore this can only take advantage of limited implicit context as it appears during training. We instead show that recognizing materials purely from their local appearance and integrating separately recognized global contextual cues including objects and places leads to superior dense, per-pixel, material recognition. We achieve this by training a fully-convolutional material recognition network end-to-end with only material category supervision. We integrate object and place estimates to this network from independent CNNs. This approach avoids the necessity of preparing an impractically-large amount of training data to cover the product space of materials, objects, and scenes, while fully leveraging contextual cues for dense material recognition. Furthermore, we perform a detailed analysis of the effects of context granularity, spatial resolution, and the network level at which we introduce context. On a recently introduced comprehensive and diverse material database \cite{Schwartz2016}, we confirm that our method achieves state-of-the-art accuracy with significantly less training data compared to past methods.	['Ko Nishino', 'Gabriel Schwartz']	2016-11-28	null	null	null	null	['material-recognition']	['computer-vision']	[ 7.18696356e-01 -4.01594192e-01 -7.39215389e-02 -3.95176142e-01 -6.85457289e-01 -7.63741016e-01 8.14711750e-01 3.44803572e-01 -3.43601674e-01 3.64971101e-01 6.33258894e-02 1.02178685e-01 -8.09683427e-02 -8.68821263e-01 -1.22600126e+00 -8.51889670e-01 2.77578562e-01 2.90280640e-01 4.38501894e-01 1.00818947e-01 4.03126299e-01 6.81081414e-01 -1.80607426e+00 5.61767817e-01 4.24019098e-01 1.45328152e+00 4.73857939e-01 4.66507196e-01 -1.90568432e-01 5.20066202e-01 -3.77352417e-01 2.97926227e-03 5.15097678e-01 -8.90532881e-02 -7.26453662e-01 4.92624283e-01 1.19527948e+00 -2.80977547e-01 -1.16926678e-01 8.10361028e-01 2.45530978e-01 1.53852344e-01 8.39991987e-01 -5.39285719e-01 -1.00932741e+00 3.15755427e-01 -4.94708806e-01 -6.16803989e-02 1.57540098e-01 3.91671062e-01 1.07319546e+00 -1.04991734e+00 6.39225364e-01 9.01068509e-01 6.30453587e-01 3.35065961e-01 -1.53544259e+00 -4.28054899e-01 5.72563827e-01 1.19023636e-01 -1.44423449e+00 -4.79360789e-01 1.11797452e+00 -6.62329018e-01 1.04205370e+00 2.07269460e-01 5.73527873e-01 1.01793110e+00 -1.86886296e-01 8.01688612e-01 1.14205849e+00 -5.65855265e-01 3.81702811e-01 7.88661242e-02 1.10137612e-01 4.79280740e-01 3.06830496e-01 -1.13825828e-01 -4.78202105e-01 3.31949472e-01 9.00480926e-01 2.37740442e-01 -2.38767728e-01 -5.39259553e-01 -1.27830839e+00 3.87405038e-01 7.01470137e-01 2.69511193e-01 -4.71862316e-01 3.22631806e-01 6.40824512e-02 -9.45331827e-02 4.67453092e-01 4.25341070e-01 -4.87980545e-01 2.41302148e-01 -8.91665697e-01 1.31783247e-01 5.73987842e-01 9.50066328e-01 1.02121377e+00 -4.94325608e-02 -1.33083448e-01 9.99185145e-01 1.04133487e-01 6.74200356e-01 -1.72931761e-01 -8.22960615e-01 4.63709116e-01 6.64022207e-01 1.98801264e-01 -9.37426984e-01 -2.10182160e-01 -5.30999720e-01 -5.11690617e-01 3.34957004e-01 6.11412287e-01 4.18163955e-01 -1.28743696e+00 1.83089924e+00 3.66095513e-01 -1.70506164e-01 -2.57218331e-01 9.51055348e-01 7.05731690e-01 3.59920859e-01 1.27137780e-01 3.00112963e-01 1.41325271e+00 -1.04168463e+00 -2.20506996e-01 -5.73403955e-01 2.37399012e-01 -8.47367585e-01 1.18319571e+00 4.03006375e-01 -1.06939375e+00 -5.49533844e-01 -1.07152045e+00 -1.86581835e-01 -7.33408928e-01 2.07248986e-01 7.92075872e-01 4.25801992e-01 -8.45171809e-01 5.22369206e-01 -5.47408521e-01 -3.36558163e-01 7.81986773e-01 4.90405917e-01 -3.26041609e-01 -4.67273772e-01 -6.06940091e-01 6.25092566e-01 2.10339785e-01 2.95652866e-01 -7.31535256e-01 -7.64652312e-01 -8.05485427e-01 2.79169790e-02 5.24671435e-01 -5.75643420e-01 9.43141878e-01 -1.33619857e+00 -1.06136191e+00 8.82054210e-01 -2.93599572e-02 -2.43154494e-03 2.77874231e-01 -8.69373530e-02 -2.24653423e-01 2.22316965e-01 2.55102478e-02 9.19409871e-01 8.18696797e-01 -1.65937674e+00 -4.28971201e-01 -2.73794562e-01 2.93162555e-01 9.10084248e-02 -1.79690361e-01 -1.49375811e-01 -5.56059361e-01 -6.66351795e-01 2.60880202e-01 -1.03746009e+00 -8.56324062e-02 3.43394816e-01 -3.57977360e-01 -8.65276996e-03 5.17712235e-01 -5.47836185e-01 5.92922151e-01 -2.19072175e+00 -3.92129868e-02 1.52154103e-01 -4.49791290e-02 -2.15944815e-02 -2.92369127e-01 2.25184694e-01 4.72769178e-02 -7.61916637e-02 -2.57060647e-01 -3.40067327e-01 1.04997732e-01 -1.68460887e-02 -8.53389055e-02 4.33083206e-01 6.15005076e-01 9.97157276e-01 -7.43008196e-01 -3.23835850e-01 4.61720943e-01 7.53090739e-01 -5.70230067e-01 -1.90262809e-01 -5.61630011e-01 4.38379467e-01 -1.59512371e-01 9.81947601e-01 7.12737381e-01 -5.59258819e-01 9.99802351e-03 -5.83954334e-01 -6.92729428e-02 4.18217838e-01 -1.24473310e+00 1.91812170e+00 -6.29594266e-01 6.99207008e-01 2.69741118e-01 -8.87715936e-01 5.32666206e-01 6.14757426e-02 4.59962875e-01 -8.29795182e-01 9.72282961e-02 2.85695523e-01 7.75698712e-03 -1.65278301e-01 3.89026523e-01 -7.07423985e-02 1.45144805e-01 2.68223763e-01 -1.08609714e-01 -9.60345939e-02 9.28142294e-02 -1.26084059e-01 1.18206513e+00 3.36033076e-01 4.50523046e-04 -1.65880680e-01 1.49275854e-01 -4.06952500e-02 2.72449493e-01 8.41406882e-01 4.93081138e-02 8.56680095e-01 -1.94458470e-01 -3.97908956e-01 -9.76889729e-01 -1.30618870e+00 -3.48521858e-01 1.12405980e+00 3.70594919e-01 -2.25271676e-02 -3.92107785e-01 -6.53794885e-01 2.10520580e-01 2.75948405e-01 -8.27629507e-01 7.23755807e-02 -6.58323467e-01 -3.61177236e-01 -1.44007817e-01 8.16458046e-01 4.30051327e-01 -1.25602698e+00 -3.90890539e-01 1.09679110e-01 4.36989591e-02 -1.37028301e+00 -4.17654723e-01 3.66773337e-01 -6.66931748e-01 -8.34270775e-01 -6.00329995e-01 -8.66766572e-01 9.93156195e-01 5.52685022e-01 1.44951212e+00 -4.71821427e-02 -5.17525136e-01 6.48461103e-01 -1.63490191e-01 -2.02069551e-01 -5.23351692e-02 -7.72422105e-02 -2.99367487e-01 1.22857086e-01 2.93913335e-01 -7.01438963e-01 -9.89678860e-01 2.92364031e-01 -1.01560259e+00 4.05870706e-01 1.11357915e+00 6.43750966e-01 8.01625609e-01 1.84361951e-03 4.19628173e-01 -8.85909617e-01 -1.25736922e-01 -3.34234327e-01 -3.03393185e-01 3.10642749e-01 -3.44188869e-01 -4.13832963e-02 4.35336471e-01 -6.06531620e-01 -9.82614398e-01 2.62025177e-01 2.56435126e-01 -3.59049499e-01 -5.17875135e-01 2.47009054e-01 -3.97080034e-01 -2.69722134e-01 5.13692021e-01 1.47575334e-01 -3.80478323e-01 -5.04490674e-01 4.74660099e-01 4.71868902e-01 4.53213722e-01 -8.32315326e-01 6.29796982e-01 6.51106894e-01 9.35646817e-02 -7.18757451e-01 -9.17803526e-01 -5.54052532e-01 -8.51954460e-01 -3.25602293e-01 8.23258817e-01 -9.97130752e-01 -5.78712106e-01 4.30458397e-01 -9.91608143e-01 -5.61743379e-01 -3.86502981e-01 3.22877914e-01 -4.20319736e-01 8.06976110e-02 -5.10985792e-01 -6.75474346e-01 -1.32172137e-01 -1.01890671e+00 1.34581327e+00 -2.34186992e-01 -7.52740353e-02 -9.19120252e-01 -5.45946598e-01 5.54947436e-01 5.75772941e-01 2.65025109e-01 8.44504774e-01 -1.51384056e-01 -1.20769060e+00 -1.82017162e-01 -6.72753930e-01 3.68682683e-01 6.36114240e-01 -1.65379331e-01 -1.28588092e+00 -7.81810656e-02 -1.98843643e-01 -2.37825826e-01 1.19362056e+00 2.64253646e-01 1.28808761e+00 -1.96781650e-01 -1.41266093e-01 3.07754666e-01 1.78324819e+00 -4.57098596e-02 3.54354858e-01 2.73905843e-01 1.14710999e+00 9.11735177e-01 3.33291173e-01 1.22488499e-01 1.33153632e-01 7.18139768e-01 4.16646779e-01 -2.02511191e-01 -6.98947668e-01 4.25893106e-02 2.72774071e-01 5.74165702e-01 -3.23991962e-02 -1.35105908e-01 -7.83532619e-01 7.67260730e-01 -1.53996515e+00 -9.04773474e-01 7.43989125e-02 2.20568919e+00 9.53779161e-01 3.19418341e-01 -5.15803732e-02 6.61885664e-02 5.95874846e-01 5.33696488e-02 -8.12843263e-01 1.70413461e-02 -3.85437638e-01 1.56886160e-01 7.32589185e-01 2.53095508e-01 -1.13214886e+00 7.40044534e-01 6.05277014e+00 9.28791046e-01 -1.41431808e+00 -1.15783766e-01 6.75907671e-01 -3.54605287e-01 -3.85124832e-01 -1.54927239e-01 -6.58022642e-01 4.82470959e-01 5.28589249e-01 7.32695222e-01 6.92039311e-01 7.52969801e-01 -2.33309679e-02 -3.16630751e-01 -1.48034668e+00 1.01599777e+00 1.79061204e-01 -1.33770907e+00 2.25183158e-03 1.39937371e-01 9.26817894e-01 1.16144821e-01 2.38929138e-01 -9.91148353e-02 1.81109428e-01 -8.33727777e-01 1.24998319e+00 3.49163562e-01 8.43571186e-01 -9.11565647e-02 2.53618479e-01 -5.83950654e-02 -1.39192235e+00 -1.26234651e-01 -9.73317549e-02 -2.85247657e-02 -1.00703575e-01 7.48393774e-01 -5.66092551e-01 4.02698755e-01 6.34022534e-01 6.77300930e-01 -7.31479883e-01 8.50401103e-01 3.09176780e-02 4.56794798e-01 -5.45481682e-01 1.38844416e-01 1.63280517e-01 -3.34210433e-02 4.44685407e-02 1.24052203e+00 4.75069471e-02 -1.49981439e-01 3.85402113e-01 1.14382660e+00 -1.72330558e-01 2.18022373e-02 -4.84077066e-01 -1.22098282e-01 2.81088263e-01 1.19679070e+00 -1.13775504e+00 -3.00159782e-01 -7.77602255e-01 7.79756010e-01 3.30089599e-01 3.43282044e-01 -5.33495665e-01 -4.82787415e-02 4.36084926e-01 4.06861514e-01 8.05955470e-01 -4.23172683e-01 -6.28772438e-01 -9.16070461e-01 6.25578105e-01 -4.52415019e-01 -1.23436481e-01 -8.60476375e-01 -1.64892948e+00 2.36408845e-01 -1.46596655e-01 -1.27973485e+00 2.34085768e-01 -1.09153259e+00 -2.01657817e-01 8.00406992e-01 -1.61386538e+00 -1.65281498e+00 -5.03487468e-01 2.56955177e-01 5.39386332e-01 3.22489202e-01 5.88040769e-01 4.77272332e-01 -2.21197039e-01 3.29556853e-01 1.56546272e-02 1.33499339e-01 7.19093204e-01 -1.19353855e+00 1.28477275e-01 5.62580943e-01 2.54375309e-01 6.21828020e-01 4.83315498e-01 -5.93081295e-01 -1.53035378e+00 -1.11878276e+00 3.84103179e-01 -7.39150107e-01 5.13024509e-01 -8.02760780e-01 -7.96914697e-01 4.20677722e-01 3.35432887e-02 2.60024220e-01 6.48339510e-01 4.07150984e-01 -8.24283361e-01 -3.09278458e-01 -9.83231962e-01 5.65926909e-01 1.32691777e+00 -8.27702820e-01 -1.78495929e-01 4.06167984e-01 7.97185004e-01 -9.35155973e-02 -8.56803358e-01 5.43153405e-01 6.24773026e-01 -8.86250198e-01 1.15843558e+00 -3.33201326e-02 5.90809822e-01 -2.96496153e-01 -6.34321034e-01 -7.67721534e-01 -4.95612711e-01 -1.63701512e-02 6.09838031e-03 1.38844430e+00 4.40718234e-01 -3.66257131e-01 8.95415068e-01 8.27816248e-01 -2.88076013e-01 -9.06104207e-01 -5.94836175e-01 -9.15904522e-01 3.81826125e-02 -6.50708973e-01 5.41081131e-01 8.05626094e-01 -4.88636583e-01 2.84390002e-01 1.65386461e-02 6.87659681e-02 5.36690295e-01 6.22057557e-01 4.90388662e-01 -1.08955538e+00 -4.82084334e-01 -6.72276497e-01 -4.17653799e-01 -1.08565009e+00 -2.22412180e-02 -8.01757455e-01 3.58723372e-01 -1.68797743e+00 3.70789260e-01 -9.31379199e-01 -7.20415413e-01 5.98775804e-01 -8.81760642e-02 5.95946610e-01 1.20350599e-01 3.34450483e-01 -8.52489114e-01 3.61160219e-01 1.20807707e+00 -5.90514362e-01 3.96224894e-02 -3.64859015e-01 -7.59996355e-01 4.37378138e-01 5.64005256e-01 2.37432830e-02 -2.67783672e-01 -7.79556155e-01 2.16829091e-01 -5.20192444e-01 6.18288159e-01 -1.20306921e+00 4.94045503e-02 -3.08181167e-01 7.06805408e-01 -6.44248128e-01 7.04838157e-01 -1.12720644e+00 1.67545810e-01 -6.73063993e-02 -2.90581554e-01 -4.12025541e-01 3.06899846e-01 6.35652184e-01 5.73751368e-02 -3.97235900e-02 6.15758359e-01 -2.21048832e-01 -8.50161433e-01 3.86482000e-01 5.88536710e-02 -2.18577385e-01 7.37544477e-01 -5.11583924e-01 -3.64791363e-01 1.71989664e-01 -5.54809153e-01 -2.96014875e-01 9.74278450e-01 3.36636961e-01 4.23569322e-01 -1.41161036e+00 -2.38573477e-01 1.24928445e-01 3.03428173e-01 3.43413770e-01 4.66414332e-01 5.68711758e-01 -2.48166412e-01 3.73604894e-01 -1.41505539e-01 -8.39789331e-01 -1.02166510e+00 8.19816470e-01 7.31880143e-02 9.27968100e-02 -5.54233015e-01 7.43785083e-01 7.15467632e-01 -1.87273383e-01 1.80907637e-01 -5.72316945e-01 2.34318823e-01 -1.34161815e-01 2.34390691e-01 -1.62955657e-01 2.67190576e-01 -5.91405034e-01 -2.87121326e-01 1.02238333e+00 -1.11111268e-01 5.99283539e-02 1.51501703e+00 -6.98410720e-02 -8.18000361e-02 6.60667539e-01 1.20017684e+00 2.95926720e-01 -1.68896937e+00 -5.35268962e-01 -1.35422707e-01 -6.51043832e-01 -1.05386600e-02 -1.12421024e+00 -1.19520247e+00 9.13371801e-01 5.48723400e-01 1.37460098e-01 1.18854344e+00 2.58543164e-01 5.63509762e-01 3.40819925e-01 4.83459145e-01 -1.02361846e+00 3.09379399e-01 1.15995653e-01 8.96090388e-01 -1.60766506e+00 1.15458667e-01 -7.11828887e-01 -9.84076932e-02 7.65778780e-01 6.82095587e-01 -1.00539126e-01 6.94467604e-01 1.31434903e-01 -1.30049005e-01 -2.98440516e-01 -6.04802787e-01 -3.90565991e-01 5.99330366e-01 4.75618750e-01 2.40542173e-01 1.21161468e-01 4.87236321e-01 3.95370960e-01 1.33680716e-01 -2.91931719e-01 -1.02226205e-01 1.18739974e+00 -3.90961647e-01 -9.28055227e-01 -3.48002762e-01 5.14700294e-01 -2.83032209e-01 -2.45310932e-01 -4.15704221e-01 5.54840505e-01 5.02836883e-01 7.46682048e-01 3.29057723e-01 -2.43326709e-01 2.09295094e-01 -1.42600223e-01 9.29444313e-01 -7.40982831e-01 -3.85225832e-01 5.85338920e-02 -2.92821322e-02 -4.46310937e-01 -6.56343579e-01 -7.88214624e-01 -1.00171554e+00 -9.80884135e-02 -4.13673639e-01 -4.68929559e-01 9.83547151e-01 9.75621104e-01 3.72444391e-01 6.34565294e-01 5.55786550e-01 -1.28992987e+00 -4.27789129e-02 -8.27586353e-01 -4.98035789e-01 8.36130321e-01 3.31073046e-01 -8.69860530e-01 -3.30188155e-01 2.80949503e-01]	[10.170536994934082, -0.10981159657239914]
69a3aee3-6052-4f0f-b58b-1e7adca26d99	language-embeddings-for-typology-and-cross	2106.02082	null	https://arxiv.org/abs/2106.02082v1	https://arxiv.org/pdf/2106.02082v1.pdf	Language Embeddings for Typology and Cross-lingual Transfer Learning	Cross-lingual language tasks typically require a substantial amount of annotated data or parallel translation data. We explore whether language representations that capture relationships among languages can be learned and subsequently leveraged in cross-lingual tasks without the use of parallel data. We generate dense embeddings for 29 languages using a denoising autoencoder, and evaluate the embeddings using the World Atlas of Language Structures (WALS) and two extrinsic tasks in a zero-shot setting: cross-lingual dependency parsing and cross-lingual natural language inference.	['Kenji Sagae', 'Taiqi He', 'Dian Yu']	2021-06-03	null	https://aclanthology.org/2021.acl-long.560	https://aclanthology.org/2021.acl-long.560.pdf	acl-2021-5	['cross-lingual-natural-language-inference']	['natural-language-processing']	[-4.5320669e-01 1.3132535e-01 -4.2874956e-01 -9.5028275e-01 -1.1836717e+00 -1.0248578e+00 8.7469667e-01 2.8007177e-01 -9.3186337e-01 6.4525127e-01 6.6551495e-01 -4.8186862e-01 4.8686931e-01 -6.0889423e-01 -9.6503133e-01 2.5775967e-02 -8.9532167e-02 8.1125897e-01 -3.3619338e-01 -3.0501109e-01 -4.9958456e-01 2.8207478e-01 -6.2004149e-01 2.2052586e-01 7.4334097e-01 3.7473518e-01 1.3300447e-01 5.4626894e-01 -4.3486276e-01 4.8495698e-01 -2.1522199e-01 -9.2075682e-01 2.8591520e-01 -2.1509854e-01 -8.5956341e-01 -3.6716411e-01 5.1101553e-01 -2.4074133e-01 -4.7770619e-01 9.6715200e-01 2.8937477e-01 -3.1157579e-02 5.2610332e-01 -7.1627128e-01 -1.2624596e+00 1.0192398e+00 -3.9146373e-01 3.9249128e-01 2.8110491e-02 8.7242447e-02 1.3977995e+00 -9.4673777e-01 1.0506777e+00 1.6356913e+00 7.6953584e-01 3.4096995e-01 -1.6525006e+00 -5.4556513e-01 5.5315580e-02 -2.8880605e-01 -1.0853516e+00 -6.4091867e-01 7.0605052e-01 -5.6160039e-01 1.4408247e+00 -6.4438933e-01 8.6207554e-02 1.6325281e+00 2.3118354e-01 5.8154297e-01 9.9992830e-01 -5.2654433e-01 -1.9137989e-01 1.6683016e-02 2.3606241e-01 1.0903820e+00 3.1582421e-01 2.1814519e-01 -5.5703431e-01 -4.0705763e-02 4.0788731e-01 -3.5760310e-01 1.8020393e-01 -2.3904212e-02 -1.2496804e+00 1.2666700e+00 4.5532984e-01 4.7364563e-01 -2.5570908e-01 1.6669953e-01 9.1277903e-01 4.5228267e-01 7.2727787e-01 7.4471349e-01 -9.4132429e-01 1.6135632e-01 -5.9304512e-01 -2.1592592e-01 7.8048402e-01 8.7997913e-01 1.0389932e+00 2.0605366e-01 3.1558788e-01 1.0012746e+00 3.0546004e-01 3.9743742e-01 7.3266608e-01 -7.3518914e-01 7.5146592e-01 4.0672758e-01 -4.5317227e-01 -4.2433760e-01 -2.8406066e-01 6.0579903e-02 -6.0981023e-01 -1.6804926e-01 2.4919277e-01 -5.7992876e-01 -7.4975407e-01 2.1560478e+00 1.4156629e-01 -3.6879781e-01 5.6461424e-01 3.7905538e-01 7.1333474e-01 6.4920497e-01 3.3061543e-01 2.9425356e-01 1.5726614e+00 -8.8683188e-01 -5.8497852e-01 -6.4963984e-01 8.7052959e-01 -7.3019367e-01 1.0215123e+00 -8.6160108e-02 -9.6903151e-01 -7.3088431e-01 -9.8044831e-01 -9.9254584e-01 -8.2741088e-01 1.6142344e-01 8.1770325e-01 -3.2492567e-02 -8.7831157e-01 3.2831907e-01 -1.1420342e+00 -2.4600755e-01 1.0279220e-01 3.5724621e-02 -1.0116065e+00 -2.9980266e-01 -1.4859419e+00 1.3241236e+00 5.8493358e-01 -1.8990051e-03 -9.6096396e-01 -8.0324453e-01 -1.6204243e+00 -2.3457426e-01 -3.2179041e-03 -5.7332391e-01 1.0480058e+00 -9.6776211e-01 -1.2243950e+00 1.3774976e+00 -5.9013885e-02 -5.2389181e-01 7.8494757e-02 -4.1228816e-01 -4.0930092e-01 -1.4260501e-01 5.5468088e-01 8.7422067e-01 2.5440493e-01 -7.5142872e-01 -2.8297201e-01 -5.7175833e-01 4.8174642e-02 5.4522883e-02 -1.5500341e-02 1.9826080e-01 -5.7974464e-01 -6.9049245e-01 -3.5717046e-01 -8.7251496e-01 -2.1044223e-01 -1.6354129e-01 -4.2965925e-01 -5.7879061e-01 2.2868049e-01 -1.1396135e+00 6.8754917e-01 -2.0175278e+00 4.3956432e-01 -1.9949196e-01 -1.8806159e-01 -1.5102942e-01 -6.4880693e-01 3.7414950e-01 1.7666897e-02 2.6955602e-01 -3.4173259e-01 -7.5812900e-01 8.0940515e-02 8.7543845e-01 -1.8691352e-01 4.8284617e-01 7.2355628e-01 8.7532067e-01 -8.1580275e-01 -3.6531025e-01 -4.7368813e-02 7.4145633e-01 -6.1280376e-01 3.4868905e-01 -1.9839542e-01 3.2226515e-01 -1.9861427e-01 4.7912791e-01 2.6854366e-01 1.9523790e-01 6.9676220e-01 -3.3863235e-01 -1.8572220e-01 8.8030750e-01 -4.0628186e-01 2.2025831e+00 -1.1739650e+00 5.9353262e-01 1.4660923e-01 -9.5164454e-01 1.0657432e+00 2.7715066e-01 1.6962575e-02 -7.7990389e-01 5.8290869e-02 1.9957510e-01 8.2145661e-02 -3.2187480e-01 2.6433212e-01 -3.6029109e-01 -8.0786198e-01 5.8503687e-01 9.2472869e-01 -1.6740210e-01 1.1835952e-01 1.0858480e-01 8.2750326e-01 2.7863437e-01 3.8999265e-01 -5.5157703e-01 1.5891182e-01 2.1033432e-02 7.8021628e-01 3.3423167e-01 -7.9931775e-03 2.3760891e-02 5.2918690e-01 -8.1365734e-01 -1.2506448e+00 -1.2591184e+00 -2.7186599e-01 1.6172293e+00 -5.1551968e-01 -3.7568355e-01 -4.7560915e-01 -8.5177064e-01 2.0880163e-01 8.4031403e-01 -7.7789104e-01 7.2402567e-02 -7.0179880e-01 -5.1921290e-01 1.0777743e+00 7.2935635e-01 -7.9710133e-02 -9.5744300e-01 1.8268181e-02 2.5660849e-01 1.0652418e-01 -1.6959916e+00 -5.5100816e-01 7.7103901e-01 -5.1768029e-01 -1.0298648e+00 -2.7988628e-01 -1.2584064e+00 5.3358769e-01 -5.7898438e-01 1.7542803e+00 -3.2716498e-01 -2.0049107e-01 1.7991973e-01 7.3081151e-02 -4.1634198e-02 -7.1778935e-01 5.3390455e-01 4.6507633e-01 -3.3044612e-01 7.3263955e-01 -4.6722218e-01 -3.9899286e-02 -1.9533733e-01 -5.4147559e-01 -1.4012381e-01 4.9130315e-01 1.1138941e+00 8.4065723e-01 -6.3775551e-01 5.0770831e-01 -1.2290517e+00 6.6006237e-01 -6.5457779e-01 -9.9320823e-01 2.6764044e-01 -7.9520069e-02 7.9625446e-01 8.7816799e-01 -2.0526458e-01 -1.1054040e+00 1.5453164e-01 -1.6393377e-01 -2.0777079e-01 -2.9823467e-01 5.9801459e-01 -1.7030220e-01 4.9947533e-01 6.1690336e-01 -1.4206922e-01 -3.5893407e-01 -6.6497374e-01 1.0693910e+00 4.1625682e-01 7.0819235e-01 -1.0331992e+00 5.0348848e-01 1.3764457e-01 -4.9904180e-01 -6.3018095e-01 -1.0845046e+00 3.4352481e-02 -1.3321199e+00 7.0490670e-01 1.4548951e+00 -1.4321425e+00 -1.4052719e-01 -2.2553532e-01 -1.5995924e+00 -4.0656075e-01 -1.6885783e-01 7.0473093e-01 -1.8924393e-01 -3.5355624e-02 -9.7093707e-01 -9.6928775e-02 -4.5372027e-01 -1.2120237e+00 1.1017315e+00 -1.8824694e-01 -3.1673855e-01 -1.3905436e+00 6.1785692e-01 8.0003269e-02 4.2546012e-02 2.2401001e-01 1.2389333e+00 -8.1146944e-01 -2.3957518e-01 -8.4921569e-02 -5.9189186e-02 6.2113231e-01 2.8969595e-01 -4.6908524e-02 -8.4018791e-01 -2.3952110e-01 -3.7645307e-01 -8.2364488e-01 6.9784188e-01 1.9310923e-01 8.2181597e-01 -1.5769444e-01 -5.8760419e-02 9.3340361e-01 1.4742876e+00 -2.9703221e-01 -7.6888934e-02 1.0351221e-02 9.3320143e-01 8.8242543e-01 -2.1748509e-01 -1.8275137e-01 7.4361652e-01 2.8216043e-01 -2.7914685e-01 -1.3434140e-01 -1.2731616e-01 -5.9270573e-01 5.4251415e-01 1.6268362e+00 3.8555393e-01 1.7074679e-01 -1.3113674e+00 1.0633953e+00 -1.1575284e+00 -4.2914352e-01 3.3473328e-01 1.6413171e+00 1.2014230e+00 4.9969744e-02 -3.4946620e-01 -7.8669769e-01 3.8307711e-01 1.0090662e-01 -6.5347904e-01 -9.9493569e-01 -2.4071965e-01 6.6144764e-01 6.0679805e-01 8.9440852e-01 -1.0239758e+00 1.4680995e+00 7.1390500e+00 1.1084906e-01 -1.1097794e+00 5.5036479e-01 7.2747791e-01 1.8993914e-01 -5.0992000e-01 8.3066307e-02 -9.5288390e-01 1.6828318e-01 1.4668156e+00 -1.6992033e-01 4.6941969e-01 8.9868903e-01 -3.7598369e-01 2.8668541e-01 -1.5175298e+00 5.8206880e-01 4.0118363e-02 -1.1572443e+00 -1.4310394e-01 -9.3541026e-02 7.1038234e-01 1.1553947e+00 -2.0100300e-01 6.7992508e-01 1.3330780e+00 -1.1135114e+00 2.6895875e-01 1.5650119e-01 1.0676295e+00 -7.7521831e-01 4.7892919e-01 7.1310855e-02 -1.1081331e+00 4.3638143e-01 -3.4452909e-01 1.8678471e-01 3.1269449e-01 2.4401440e-01 -7.5695235e-01 2.9322192e-01 5.1024914e-01 7.5130761e-01 -5.9560233e-01 -2.8064510e-01 -6.8043649e-01 6.1463541e-01 -4.1466355e-01 2.8626359e-01 4.8542190e-01 -1.7156184e-01 1.1324130e-01 1.5944542e+00 2.0048753e-04 -4.5892346e-01 4.1308710e-01 1.0135968e+00 -6.6451019e-01 1.5606637e-01 -1.1053213e+00 -4.6868631e-01 4.4866532e-01 1.0730287e+00 -4.2215280e-02 -5.6995022e-01 -8.8037294e-01 1.0930773e+00 9.6551847e-01 3.1530762e-01 -4.5030820e-01 -1.9292574e-01 1.1001400e+00 -3.7895045e-01 2.0070744e-01 -6.9771647e-01 -3.0779371e-01 -1.5410820e+00 -3.7079650e-01 -8.0924457e-01 5.1388240e-01 -5.0219965e-01 -2.0001388e+00 8.3542359e-01 -9.8321013e-02 -4.1176057e-01 -6.5618068e-01 -1.0677298e+00 -3.5051343e-01 1.2047869e+00 -1.6106421e+00 -1.4463429e+00 5.4060543e-01 5.8144772e-01 6.1092508e-01 -5.5706531e-01 1.3977939e+00 2.7333978e-01 -6.5664852e-01 8.2136983e-01 7.1279392e-02 8.9353871e-01 7.9879934e-01 -1.4026483e+00 1.0312304e+00 8.2340443e-01 5.8465129e-01 9.0138578e-01 5.8344942e-02 -3.5601795e-01 -1.7052157e+00 -1.3087008e+00 1.2744702e+00 -6.3514870e-01 1.2043008e+00 -8.8706517e-01 -1.0009650e+00 1.2875304e+00 7.1435130e-01 5.8687866e-01 1.0228717e+00 8.2640499e-01 -1.0160227e+00 3.1407513e-02 -7.8855723e-01 4.5444179e-01 8.3108014e-01 -1.5532291e+00 -1.0266798e+00 2.5226766e-01 1.0334680e+00 -7.1819402e-02 -1.3761338e+00 -4.6133924e-02 3.9977449e-01 -2.2330070e-01 8.5482848e-01 -1.0713774e+00 6.3346696e-01 1.3128644e-01 -5.4060292e-01 -1.5676420e+00 -2.7435195e-01 -2.3760475e-01 4.3060160e-01 1.2853613e+00 7.8662431e-01 -5.3666872e-01 9.5062532e-02 3.5497653e-01 -1.8689872e-01 -3.2781550e-01 -1.0675541e+00 -5.8611345e-01 8.6325622e-01 -4.7554469e-01 4.1619563e-01 1.5211306e+00 -2.5386423e-01 1.0347904e+00 -2.0167965e-01 3.6339280e-01 5.0830883e-01 -3.7504129e-02 6.6506463e-01 -1.0615548e+00 -6.1271065e-01 -1.3087812e-01 -2.0393120e-01 -6.3191617e-01 1.1880623e+00 -1.5766809e+00 1.9427679e-01 -1.2275016e+00 -8.1161559e-02 -2.0353782e-01 -3.9910090e-01 6.2424237e-01 8.0477491e-02 -4.4376245e-03 -1.3163142e-01 -1.5060648e-01 -3.0121315e-01 6.1723512e-01 6.0610515e-01 -8.6693183e-02 2.3983872e-01 -9.9892080e-01 -6.5621662e-01 9.8062056e-01 4.9945587e-01 -6.6532105e-01 -1.6866080e-02 -1.4795355e+00 1.8753657e-01 1.7845433e-02 -1.3953012e-01 -3.1329900e-01 -4.1414168e-02 -7.4870768e-03 4.1184726e-01 -3.1199980e-01 2.9536107e-01 -5.2770752e-01 -4.5585895e-01 1.1861886e-01 -4.5456874e-01 7.0657319e-01 4.6127781e-01 4.8480520e-01 -4.2605665e-01 4.5769890e-03 6.9251394e-01 -3.5686192e-01 -6.9943178e-01 2.8922918e-01 -2.5403628e-01 5.0171781e-01 5.0312144e-01 5.7620168e-01 -1.5305313e-01 1.8959616e-01 -7.0028818e-01 2.0348419e-01 4.6430546e-01 7.0444936e-01 -1.7747969e-03 -1.5481435e+00 -8.1609994e-01 4.4384146e-01 3.1833097e-01 5.1449768e-02 -2.6661462e-01 1.5805686e-01 -3.5886830e-01 2.9479897e-01 -2.2037503e-01 -3.8890374e-01 -6.8098307e-01 4.2622045e-01 4.1637444e-01 -4.3378830e-01 -5.3811127e-01 8.2904184e-01 3.7780464e-01 -1.3149155e+00 -1.8824427e-01 -4.9338493e-01 2.3284620e-01 6.1908826e-02 2.0095468e-01 -4.4496235e-01 -1.5314092e-01 -8.5735381e-01 -5.5537313e-01 4.8046458e-01 -1.5098433e-01 -3.6160770e-01 1.6673223e+00 1.2652294e-01 -9.1862194e-02 8.4761333e-01 1.6472592e+00 2.1178095e-01 -1.1270422e+00 -5.0920445e-01 4.0856522e-01 1.4795117e-01 1.7701714e-01 -6.9245923e-01 -8.2115912e-01 1.1009172e+00 3.2217517e-01 -4.0911260e-01 6.1212635e-01 3.7646499e-01 8.4152746e-01 5.5480790e-01 1.8411234e-01 -1.1355981e+00 -2.0539376e-01 9.3275619e-01 9.0719187e-01 -1.6767570e+00 -3.0752045e-01 1.8955933e-01 -7.2017980e-01 1.0159692e+00 5.3327268e-01 -6.8519926e-01 8.4174663e-01 7.3326933e-01 2.3721823e-01 -2.2433603e-01 -1.0084108e+00 -1.9792107e-01 2.9462740e-01 5.4411834e-01 1.1071725e+00 4.9644858e-01 -1.7215274e-02 7.7988267e-01 -3.9825305e-01 -4.1440076e-01 7.3400930e-02 4.9371317e-01 2.3714878e-01 -1.4349928e+00 1.3365611e-01 -1.0195167e-01 -5.5709088e-01 -6.1659938e-01 -3.5795641e-01 8.7011307e-01 3.5315034e-01 3.7230575e-01 5.7866037e-01 8.0830447e-02 1.9117925e-01 4.8916852e-01 4.8648056e-01 -8.5973978e-01 -4.4963530e-01 -1.8077365e-01 3.8936940e-01 -4.8441735e-01 -2.2516279e-01 -5.4577297e-01 -1.1219072e+00 -8.1522077e-02 1.6639359e-01 -1.4206792e-01 8.8424617e-01 9.5990884e-01 5.9898591e-01 5.0515771e-01 2.0658268e-01 -5.5247426e-01 -3.0007088e-01 -1.1801096e+00 -7.6451682e-02 5.8918828e-01 1.6867684e-01 -3.3410752e-01 -1.3299696e-01 1.6257261e-01]	[11.005242347717285, 9.904871940612793]
d6b6a20a-00fd-482b-a2e8-7037d6147a85	the-rl-perceptron-generalisation-dynamics-of	2306.10404	null	https://arxiv.org/abs/2306.10404v3	https://arxiv.org/pdf/2306.10404v3.pdf	The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions	Reinforcement learning (RL) algorithms have proven transformative in a range of domains. To tackle real-world domains, these systems often use neural networks to learn policies directly from pixels or other high-dimensional sensory input. By contrast, much theory of RL has focused on discrete state spaces or worst-case analysis, and fundamental questions remain about the dynamics of policy learning in high-dimensional settings. Here, we propose a solvable high-dimensional model of RL that can capture a variety of learning protocols, and derive its typical dynamics as a set of closed-form ordinary differential equations (ODEs). We derive optimal schedules for the learning rates and task difficulty - analogous to annealing schemes and curricula during training in RL - and show that the model exhibits rich behaviour, including delayed learning under sparse rewards; a variety of learning regimes depending on reward baselines; and a speed-accuracy trade-off driven by reward stringency. Experiments on variants of the Procgen game "Bossfight" and Arcade Learning Environment game "Pong" also show such a speed-accuracy trade-off in practice. Together, these results take a step towards closing the gap between theory and practice in high-dimensional RL.	['Adrew Saxe', 'Sebastian Goldt', 'Stefano Sarao Mannelli', 'Sebastian Lee', 'Nishil Patel']	2023-06-17	null	null	null	null	['atari-games']	['playing-games']	[ 5.67676611e-02 1.36172637e-01 -1.79455936e-01 -9.94182006e-03 -7.94558525e-01 -8.22441459e-01 7.24862576e-01 -1.21640369e-01 -9.23324764e-01 9.56988335e-01 -8.19018260e-02 -4.42345500e-01 -5.56051731e-01 -4.48376566e-01 -7.52580285e-01 -1.15691257e+00 -4.57899570e-01 5.09460628e-01 1.02408655e-01 -5.43758571e-01 2.64693260e-01 4.49563563e-01 -1.62784076e+00 -2.66213953e-01 6.50826037e-01 7.77554572e-01 3.88025761e-01 1.05151439e+00 1.74553230e-01 8.11357200e-01 -4.52073902e-01 1.71860680e-01 6.04824007e-01 -6.76472366e-01 -6.59072101e-01 -1.37600467e-01 -5.57197928e-02 -2.65702933e-01 -5.08951247e-01 9.69739497e-01 7.31311679e-01 5.44488490e-01 6.04798079e-01 -1.22738171e+00 -3.93282473e-01 3.65154386e-01 -3.34161758e-01 3.34190100e-01 9.71787199e-02 7.37551332e-01 9.11464095e-01 2.15973146e-02 5.24755478e-01 1.38979709e+00 3.91936541e-01 1.03173029e+00 -1.47675514e+00 -3.66328627e-01 3.71490657e-01 -6.65530488e-02 -5.56595922e-01 -1.68024242e-01 2.79410034e-01 -1.85819477e-01 9.17954445e-01 -2.61870995e-02 1.01770627e+00 1.22672451e+00 4.09187585e-01 1.05516016e+00 1.60894632e+00 -3.26106995e-01 8.31580818e-01 -1.05980277e-01 -1.63551494e-01 6.04831576e-01 1.31069226e-02 6.84487402e-01 -3.73623431e-01 -1.36192720e-02 1.15114260e+00 -1.55125782e-01 -2.45276049e-01 -8.19993377e-01 -8.68957520e-01 9.10218418e-01 2.19026640e-01 6.59189280e-03 -4.48121727e-01 5.37989557e-01 2.58942693e-01 7.99732804e-01 2.83200964e-02 8.02117646e-01 -4.29141521e-01 -5.45485914e-01 -3.84281665e-01 8.11022878e-01 1.03742087e+00 7.07192004e-01 5.87501168e-01 1.79268658e-01 -8.51358771e-02 6.93606317e-01 6.39242828e-02 5.56826055e-01 6.54488325e-01 -1.42243540e+00 3.71429205e-01 -2.49538422e-02 4.84370768e-01 -2.69084543e-01 -6.98257983e-01 -3.86337280e-01 -5.79436183e-01 7.93594301e-01 7.35310495e-01 -6.63905263e-01 -7.87744105e-01 2.04371715e+00 2.64681280e-01 8.33842978e-02 2.51773655e-01 1.09819782e+00 -2.43939102e-01 6.47791743e-01 -2.88809203e-02 -3.51941735e-01 8.52844179e-01 -6.29271448e-01 -4.97581095e-01 -4.82734531e-01 7.94501781e-01 -1.24989942e-01 1.38937783e+00 4.33705896e-01 -1.47476137e+00 -1.23589702e-01 -9.49899137e-01 2.81340867e-01 -2.17597872e-01 -5.81078529e-01 5.03749609e-01 5.68426669e-01 -1.27080166e+00 1.02854729e+00 -9.25920844e-01 -3.72107744e-01 1.92918584e-01 6.20944440e-01 2.03102827e-01 1.86560135e-02 -1.18164241e+00 1.09872723e+00 1.94195852e-01 4.74754311e-02 -1.24039114e+00 -6.99833751e-01 -4.99111801e-01 4.93937060e-02 6.57517970e-01 -5.76066017e-01 1.90601707e+00 -9.63234842e-01 -2.11446524e+00 4.95171309e-01 4.92312729e-01 -6.34842217e-01 5.43694139e-01 -1.79503709e-01 -1.70763247e-02 -1.45840302e-01 -2.16281399e-01 6.48512542e-01 6.82045281e-01 -1.10034502e+00 -6.60901487e-01 -4.44592237e-01 4.19076920e-01 9.08376038e-01 -3.11859269e-02 -3.62045646e-01 1.47860602e-01 -1.55132279e-01 -3.51734579e-01 -1.32716513e+00 -7.66697049e-01 -1.39976844e-01 1.92255080e-01 -7.62964115e-02 5.05789697e-01 3.75899635e-02 8.09060931e-01 -1.97362483e+00 3.93652320e-01 5.48057258e-02 -8.29896033e-02 1.65008500e-01 -4.33628350e-01 4.78563666e-01 1.79710269e-01 -2.06904560e-01 -1.51437998e-01 -6.79151295e-03 4.69079971e-01 7.12592125e-01 -4.02339727e-01 5.82939625e-01 1.53728917e-01 9.01716173e-01 -1.21370745e+00 -1.98517770e-01 -1.76236294e-02 7.30784461e-02 -7.12393403e-01 2.43013814e-01 -5.85327387e-01 4.40233320e-01 -6.81127250e-01 4.36867997e-02 8.76140073e-02 1.11699495e-02 2.90781707e-01 7.54489362e-01 -2.23697692e-01 2.36031055e-01 -1.21889019e+00 1.79074383e+00 -4.71547544e-01 5.42051971e-01 4.56629932e-01 -1.12442887e+00 5.32797456e-01 4.06340808e-02 5.66010892e-01 -9.95576978e-01 2.06035882e-01 -2.60182377e-03 2.64496028e-01 -5.57173789e-01 5.43268681e-01 -2.28446499e-01 -1.46433800e-01 7.86847174e-01 2.81373058e-02 -6.27959371e-01 2.35925555e-01 1.40607695e-03 1.43449688e+00 3.65802526e-01 -6.33955821e-02 -4.16627318e-01 -6.81554228e-02 2.37693354e-01 2.91409850e-01 1.12158477e+00 -4.05695230e-01 3.48156653e-02 9.36895549e-01 -2.68811136e-01 -1.05015349e+00 -9.68644857e-01 6.16843551e-02 1.25984752e+00 1.52070686e-01 1.28390128e-02 -9.24834490e-01 -2.42406309e-01 7.75529370e-02 6.10037446e-01 -7.98244417e-01 -3.66474032e-01 -6.22342825e-01 -8.06469679e-01 4.09208119e-01 1.83540121e-01 3.78968865e-01 -1.38234317e+00 -1.11326146e+00 3.59952539e-01 4.77464974e-01 -7.68459141e-01 -2.60520726e-01 6.88154995e-01 -1.03467810e+00 -1.00785077e+00 -8.30652535e-01 -5.37099659e-01 3.17733854e-01 6.31372631e-02 1.16783738e+00 -2.95226663e-01 -2.36682713e-01 8.04034531e-01 9.01388470e-03 -3.94971520e-01 -4.16068375e-01 6.51475564e-02 3.47876221e-01 -5.02889454e-01 -2.07405947e-02 -5.56302726e-01 -7.62044072e-01 2.10225090e-01 -9.93423998e-01 -1.39436036e-01 7.26960599e-01 9.35522974e-01 5.01035333e-01 2.05250531e-02 5.19195735e-01 -5.65233707e-01 1.26669884e+00 -5.21605909e-01 -1.03754497e+00 7.21541792e-02 -7.74633408e-01 6.61833465e-01 6.97373748e-01 -7.81385243e-01 -9.94782567e-01 1.05690099e-01 1.26970083e-01 -3.12048525e-01 -1.40872538e-01 1.10439010e-01 2.14627400e-01 -7.86778927e-02 8.25784206e-01 3.22906882e-01 3.99493724e-01 -1.55363321e-01 5.43432772e-01 2.58562267e-01 3.46141249e-01 -1.19768262e+00 5.49193978e-01 5.88107333e-02 8.48775953e-02 -5.76740324e-01 -7.14775503e-01 -8.64300132e-03 -2.51602113e-01 -3.34167808e-01 6.58430338e-01 -6.72635674e-01 -1.20197964e+00 3.87426883e-01 -5.16963303e-01 -1.38535726e+00 -8.68167818e-01 4.56605941e-01 -1.46982431e+00 -1.82788789e-01 -7.74809539e-01 -1.18610513e+00 1.87610731e-01 -1.19178832e+00 7.33709395e-01 6.03206754e-01 2.80266583e-01 -9.52679038e-01 6.69804037e-01 -3.36368352e-01 4.97610748e-01 1.04096495e-01 8.57705593e-01 -1.44676715e-01 -5.13120472e-01 3.95168662e-01 1.98397398e-01 1.13044918e-01 -4.45147634e-01 -4.02927905e-01 -6.10154331e-01 -5.41630387e-01 4.99863643e-03 -7.68968761e-01 5.59489787e-01 6.73576117e-01 9.07764077e-01 -2.92270303e-01 -2.29418576e-02 3.88986439e-01 1.56627500e+00 4.40146804e-01 3.65069062e-01 5.95205784e-01 1.42077163e-01 4.23794478e-01 5.66149592e-01 5.92461467e-01 1.64123699e-01 4.75453407e-01 7.30089605e-01 9.48008671e-02 4.35756117e-01 -2.54289657e-01 6.90502405e-01 3.23108822e-01 4.03726939e-03 -7.01398216e-03 -8.04530561e-01 2.91771770e-01 -2.13165069e+00 -1.15007460e+00 3.85475963e-01 2.32127976e+00 9.62047458e-01 2.60201901e-01 6.24970138e-01 -9.53796953e-02 4.05850589e-01 7.60012120e-02 -1.27402377e+00 -7.87763059e-01 2.20074356e-02 2.82746226e-01 8.54476869e-01 4.18467075e-01 -5.90821743e-01 9.36658919e-01 7.71897888e+00 5.36013246e-01 -9.61881697e-01 -1.06215812e-01 5.36630511e-01 -5.53006768e-01 -2.96677346e-03 -1.79257423e-01 -7.10803628e-01 2.74043351e-01 1.21887052e+00 -2.81659514e-01 1.17120254e+00 7.70631254e-01 3.57296348e-01 -4.36355591e-01 -1.06495368e+00 7.18293250e-01 -4.77769136e-01 -1.14029872e+00 -7.71179616e-01 4.66295928e-01 9.50566173e-01 3.03692847e-01 4.20276403e-01 8.34216475e-01 1.34972334e+00 -9.14869666e-01 5.05660772e-01 3.17842454e-01 6.86716855e-01 -8.81941795e-01 9.99425724e-02 7.23468304e-01 -6.81676030e-01 -6.71242476e-01 -4.33263570e-01 -4.25622940e-01 -1.68476149e-01 -1.01589337e-02 -4.64054257e-01 -7.24283978e-02 5.89867473e-01 4.24471498e-01 -1.03881881e-01 9.98570263e-01 -8.08003731e-03 3.74407679e-01 -3.98423433e-01 -4.68967259e-01 8.84212255e-01 -4.85944211e-01 2.50979900e-01 8.68972778e-01 1.34010717e-01 4.44805443e-01 1.95020009e-02 6.43793225e-01 2.07840711e-01 -2.04433993e-01 -7.36125171e-01 -1.05356060e-01 1.62189737e-01 1.02340436e+00 -6.28484190e-01 1.57393906e-02 -6.27697557e-02 7.15157092e-01 6.66710258e-01 6.36238873e-01 -7.70528138e-01 -3.39764841e-02 1.20215774e+00 -4.42870893e-02 3.02343637e-01 -4.45023090e-01 9.60415378e-02 -9.75773454e-01 -3.74211490e-01 -9.65443075e-01 2.12563559e-01 -5.90058625e-01 -1.05791080e+00 1.27134308e-01 -1.88596558e-03 -9.89554703e-01 -5.77120185e-01 -7.32061386e-01 -4.00593132e-01 5.55527031e-01 -1.38993204e+00 -1.17197810e-02 3.17142069e-01 7.81907082e-01 5.22593617e-01 -3.85936759e-02 7.14646578e-01 -1.68825850e-01 -7.82368958e-01 2.25512162e-01 8.23238254e-01 -2.49203235e-01 3.24857533e-01 -1.58735454e+00 2.13600442e-01 4.15997088e-01 -9.19505358e-02 2.31606469e-01 9.24887121e-01 -1.26821741e-01 -1.96577716e+00 -6.44177258e-01 -2.87252486e-01 -2.74145633e-01 8.85755599e-01 -3.57015550e-01 -6.23558760e-01 5.51223934e-01 1.97505534e-01 2.30428241e-02 8.03065673e-02 2.04084352e-01 -6.16005957e-02 6.18785657e-02 -1.05878198e+00 9.23711300e-01 1.21639025e+00 -4.18862790e-01 -2.67249912e-01 3.70115399e-01 4.66920912e-01 -7.37921953e-01 -6.46226048e-01 -1.49928421e-01 5.56509376e-01 -9.43754077e-01 7.85156727e-01 -1.03435075e+00 4.20390308e-01 2.43587315e-01 1.11023717e-01 -1.88368535e+00 -2.72521138e-01 -1.10005176e+00 -3.16437483e-01 4.34984207e-01 1.78925321e-01 -5.32810688e-01 9.22449172e-01 6.61420226e-01 4.67102081e-02 -1.02663064e+00 -9.43104565e-01 -9.66235399e-01 5.73552966e-01 -3.22660744e-01 2.79547304e-01 5.96745908e-01 1.56844974e-01 1.87034637e-01 -2.43577197e-01 -9.27718654e-02 6.33942783e-01 -9.51176211e-02 6.21149004e-01 -9.21901166e-01 -6.83673978e-01 -8.19741607e-01 9.77226906e-03 -1.42592371e+00 3.86762708e-01 -4.74294305e-01 4.47408676e-01 -1.28081572e+00 -1.73054785e-01 -7.61276901e-01 -4.38094556e-01 2.93166190e-01 1.11888118e-01 -5.25348902e-01 3.54551136e-01 1.23212174e-01 -8.17941904e-01 5.90928316e-01 1.51035666e+00 2.12800592e-01 -5.23736477e-01 1.30609825e-01 -5.09319484e-01 3.56617421e-01 1.00931001e+00 -5.36446631e-01 -8.73525083e-01 -4.52276021e-01 4.33401614e-01 5.63719630e-01 1.69543475e-01 -1.00324321e+00 2.09079340e-01 -7.65530765e-01 5.62977232e-02 4.15376946e-02 3.97045404e-01 -6.64098263e-01 -2.54993439e-01 7.40391195e-01 -8.94356191e-01 3.57368529e-01 1.49442315e-01 8.52147818e-01 3.92715216e-01 -1.86510727e-01 9.01217043e-01 -3.05568874e-01 -5.18255115e-01 3.50370944e-01 -8.91811788e-01 6.13816619e-01 1.14685929e+00 -5.76190092e-02 -4.26395714e-01 -5.22626758e-01 -7.21888483e-01 5.38341761e-01 4.44261223e-01 2.72160411e-01 2.30493352e-01 -1.08692801e+00 -3.23461950e-01 1.07675031e-01 -3.90756488e-01 -3.39048170e-02 6.27686009e-02 6.55430615e-01 -1.32240564e-01 1.67955935e-01 -6.25157952e-01 -3.79222214e-01 -6.18266940e-01 4.28227752e-01 7.81120658e-01 -6.17920995e-01 -5.30521572e-01 6.13937438e-01 3.93023752e-02 -3.82624000e-01 4.68843967e-01 -3.82909864e-01 1.06823862e-01 -1.09299645e-01 3.29927534e-01 1.74657747e-01 -3.31728488e-01 5.41183613e-02 1.45332709e-01 2.46378273e-01 7.73354396e-02 -6.95481896e-01 1.44285834e+00 -9.01476946e-03 5.61039805e-01 6.18703723e-01 7.11997747e-01 -8.62514734e-01 -2.17016101e+00 -2.95831650e-01 -7.41538480e-02 -1.51445150e-01 1.38306573e-01 -7.26062238e-01 -9.92243767e-01 8.63981009e-01 7.32547283e-01 5.37536740e-01 9.46540236e-01 -2.12120861e-01 4.78845239e-01 7.82708585e-01 4.78770882e-01 -1.62674284e+00 2.42163196e-01 7.61383176e-01 6.18488312e-01 -9.41185236e-01 -2.88957506e-01 6.30309045e-01 -7.68083870e-01 9.21599030e-01 5.67423761e-01 -5.41388631e-01 4.41677392e-01 5.89181781e-01 -8.51802900e-02 -9.72804241e-03 -1.25686514e+00 -4.60284650e-01 -4.46340859e-01 7.86596596e-01 -3.93589772e-02 -3.85452174e-02 -1.06187694e-01 1.40292242e-01 -2.43954122e-01 -5.56010716e-02 6.44494057e-01 1.16903448e+00 -6.82242930e-01 -1.10968721e+00 -1.84299514e-01 3.95364970e-01 -2.30018362e-01 2.66852766e-01 -7.90628046e-02 1.00669670e+00 -3.69556963e-01 6.79087937e-01 2.11924344e-01 5.34598250e-03 3.40315461e-01 1.17746722e-02 9.64532197e-01 -4.27352041e-01 -7.53450394e-01 -9.50844064e-02 -2.22073212e-01 -9.17207062e-01 -2.30287746e-01 -8.74653220e-01 -1.38805163e+00 -5.02211928e-01 -2.63887167e-04 1.19549341e-01 8.23374987e-01 1.02269638e+00 2.63837546e-01 4.20136005e-01 6.44887865e-01 -1.06934702e+00 -1.22977102e+00 -3.54341537e-01 -8.81409347e-01 1.07883789e-01 6.03491664e-01 -6.57573164e-01 -3.43228430e-01 -4.52253729e-01]	[4.095468044281006, 1.8568180799484253]
32d76955-3cb1-4d18-a620-7c01abc2d620	robust-multi-image-based-blind-face	null	null	http://openaccess.thecvf.com/content_cvpr_2015/html/Jin_Robust_Multi-Image_Based_2015_CVPR_paper.html	http://openaccess.thecvf.com/content_cvpr_2015/papers/Jin_Robust_Multi-Image_Based_2015_CVPR_paper.pdf	Robust Multi-Image Based Blind Face Hallucination	This paper proposes a robust multi-image based blind face hallucination framework to super-resolve LR faces. The proposed framework first estimates both blurring kernel and transformations of multiple LR faces by robust deblurring and registration in PCA subspace. A patch-wise mixture of probabilistic PCA prior is then incorporated for face super-resolution. Previous work on face SR using PCA prior can be viewed as special cases of the framework. Experimental results in both simulated and real LR sequences demonstrate very promising performance of the proposed method.	['Christos-Savvas Bouganis', 'Yonggang Jin']	2015-06-01	null	null	null	cvpr-2015-6	['face-hallucination']	['computer-vision']	[ 3.02141011e-01 -4.14000630e-01 3.25990617e-01 -3.89824122e-01 -8.66925001e-01 -4.35035765e-01 6.77155852e-01 -1.26011205e+00 7.87111968e-02 7.46724427e-01 6.87727094e-01 3.72664779e-01 -2.83823639e-01 -8.43872577e-02 -4.22179371e-01 -8.72632563e-01 2.12087169e-01 1.65499851e-01 -2.98483551e-01 1.71488393e-02 3.23015183e-01 9.73725080e-01 -1.58384085e+00 2.78104037e-01 7.35987306e-01 3.83848727e-01 3.18647414e-01 6.24700665e-01 3.32066983e-01 4.87561882e-01 -2.97510743e-01 -7.98333064e-02 6.16759658e-01 -2.33083278e-01 -6.37169540e-01 5.41957736e-01 9.75802660e-01 -6.13531351e-01 -5.65417469e-01 1.21269429e+00 7.39535570e-01 2.89509028e-01 5.48209131e-01 -6.69630349e-01 -1.28791797e+00 1.41086672e-02 -1.29534650e+00 6.88644409e-01 8.56392741e-01 -2.92625844e-01 9.08524171e-02 -1.45446038e+00 4.67130959e-01 1.78918695e+00 6.07242167e-01 6.24339938e-01 -1.20497262e+00 -7.05073893e-01 -6.64209783e-01 3.76801848e-01 -1.73935235e+00 -1.25920427e+00 8.29013407e-01 -9.18798074e-02 6.66022837e-01 4.83239472e-01 -1.57489851e-01 7.48007536e-01 1.72099352e-01 2.14330211e-01 1.91504085e+00 -3.96024764e-01 -1.80809870e-01 2.11133182e-01 1.03461318e-01 4.11783576e-01 2.64719158e-01 1.79753885e-01 -6.23821616e-01 -5.75576365e-01 1.35874927e+00 -8.02504867e-02 -6.65409684e-01 -1.51260942e-01 -8.97766531e-01 2.34113291e-01 -1.91203151e-02 4.06824052e-01 -5.66340029e-01 -2.25896120e-01 -1.81390315e-01 1.70216650e-01 5.45026541e-01 -1.07070968e-01 9.76759568e-02 5.07137299e-01 -1.31224966e+00 1.04445949e-01 3.38032573e-01 9.93180037e-01 4.37734157e-01 2.23922819e-01 -3.29631269e-01 1.35395455e+00 5.69227219e-01 8.24399233e-01 5.33729136e-01 -1.36152196e+00 -1.47862941e-01 -4.94809657e-01 4.40968394e-01 -8.14845622e-01 4.03302848e-01 -4.68326733e-02 -7.86990702e-01 2.35157028e-01 6.47125542e-02 2.53933609e-01 -9.40587103e-01 1.35548902e+00 5.13223350e-01 9.75271463e-01 2.70467639e-01 1.11691308e+00 8.30780566e-01 4.99420494e-01 -3.73575866e-01 -8.52613747e-01 1.45349145e+00 -8.00916016e-01 -1.22665942e+00 -7.69570321e-02 -1.04843032e+00 -1.32645822e+00 2.96310365e-01 3.18591624e-01 -1.48423982e+00 -8.95181298e-01 -7.60466993e-01 -2.85325274e-02 4.70797569e-01 3.06129426e-01 3.25312912e-01 9.47793663e-01 -1.74157989e+00 3.80173534e-01 -4.59920824e-01 -5.19095302e-01 6.22318983e-01 4.61966813e-01 -6.42406881e-01 -5.50295949e-01 -6.23291552e-01 1.16931200e+00 -2.41290867e-01 4.59188491e-01 -1.12410247e+00 -5.06955326e-01 -7.30367780e-01 -2.60176033e-01 -2.04493374e-01 -7.11897194e-01 8.08154762e-01 -7.34815836e-01 -1.58792639e+00 9.02285337e-01 -1.07589483e+00 3.18871588e-02 2.77734309e-01 -5.49413741e-01 -8.06839705e-01 4.20931160e-01 4.05390337e-02 2.38856733e-01 1.77487421e+00 -1.76316047e+00 2.30895057e-02 -6.77522361e-01 -6.21001184e-01 5.67686439e-01 2.23389175e-02 8.43894243e-01 -2.80971497e-01 -6.66632295e-01 3.22518468e-01 -5.19168615e-01 1.15626939e-01 -3.24435711e-01 1.06081136e-01 2.13385612e-01 1.28860068e+00 -1.28293490e+00 6.45637810e-01 -2.02772856e+00 2.66666949e-01 -2.19097078e-01 1.19592264e-01 1.89040408e-01 -2.64186561e-01 -4.12604883e-02 -5.88519990e-01 -3.33833396e-01 -1.72821626e-01 -5.45904875e-01 -6.61724389e-01 -4.70853597e-02 -5.78905642e-01 1.20796943e+00 5.17749712e-02 4.08484966e-01 -4.06510621e-01 -2.79305160e-01 2.74540901e-01 1.32210219e+00 -5.65377213e-02 3.15362632e-01 7.55478323e-01 8.46502185e-01 5.37290843e-03 7.19323814e-01 1.66477096e+00 2.11737409e-01 -1.85876518e-01 -6.23701036e-01 -1.12678045e-02 -5.51985979e-01 -1.30248702e+00 1.49097824e+00 -2.08484143e-01 5.02249122e-01 7.70245612e-01 -4.43043351e-01 9.48061109e-01 5.82108557e-01 4.10323799e-01 2.18020782e-01 -7.21455887e-02 3.55471410e-02 -4.52269763e-01 -5.23089468e-01 5.46398282e-01 -4.09128398e-01 7.46753395e-01 4.00419414e-01 2.27961078e-01 -5.36831059e-02 -4.62460726e-01 -1.31442785e-01 6.77617610e-01 4.63460803e-01 4.37729090e-01 -3.97363514e-01 1.17205298e+00 -6.46299422e-01 4.52488869e-01 4.96914208e-01 -4.14382428e-01 1.02017367e+00 -6.96450830e-01 -1.26854271e-01 -1.07069480e+00 -1.36326218e+00 -5.57727456e-01 5.65034032e-01 1.23331867e-01 2.51504272e-01 -7.75166750e-01 -1.72248289e-01 -1.85980067e-01 5.16152680e-01 -3.83246481e-01 3.16672295e-01 -6.37403727e-01 -1.06683242e+00 4.82734174e-01 8.74577910e-02 7.07223475e-01 -7.29080081e-01 4.82084826e-02 -2.09209844e-01 -2.87863225e-01 -1.23675334e+00 -5.82528710e-01 -8.15907896e-01 -8.25685620e-01 -8.95787239e-01 -1.11473739e+00 -1.04530978e+00 9.39076066e-01 1.20914567e+00 4.14001465e-01 -2.70180792e-01 -4.05600011e-01 7.96156228e-01 1.38524128e-02 2.16738120e-01 -4.45415050e-01 -1.37229264e+00 7.16638565e-01 5.16412973e-01 3.99076521e-01 -7.63411880e-01 -4.06985492e-01 4.20672715e-01 -6.16584837e-01 -4.48334992e-01 5.00537574e-01 7.39729583e-01 4.47963417e-01 3.43706489e-01 5.43340325e-01 -3.24222237e-01 8.31703603e-01 -4.12609845e-01 -3.97110105e-01 3.68159354e-01 -3.87649328e-01 -1.68231025e-01 -2.55902410e-02 -5.10952771e-01 -2.04446340e+00 1.43072426e-01 4.70252573e-01 -9.55561280e-01 -5.50981998e-01 -2.03763083e-01 -3.10272068e-01 -6.84391379e-01 5.21207929e-01 5.83693802e-01 3.05165410e-01 -7.86628723e-01 4.15574133e-01 1.00330329e+00 1.08213973e+00 -3.53157341e-01 1.10080469e+00 8.32178056e-01 -1.03083618e-01 -1.23230958e+00 -2.60167331e-01 -6.99418426e-01 -8.14851463e-01 -3.61096561e-01 6.97231710e-01 -1.38713503e+00 -5.84182799e-01 7.10361600e-01 -1.18842328e+00 3.85456234e-01 2.69312680e-01 4.77739185e-01 -6.11932516e-01 1.02115166e+00 -7.37154961e-01 -1.06657076e+00 -4.02566612e-01 -1.04559624e+00 1.06622946e+00 5.19632936e-01 1.80800587e-01 -7.61337280e-01 9.23890695e-02 8.93601477e-01 8.14199328e-01 -1.81410253e-01 -1.18088080e-02 -4.52764332e-03 -3.81097853e-01 -5.48389591e-02 -4.97675747e-01 3.41617644e-01 6.42733634e-01 -2.89542973e-01 -1.50564981e+00 -7.41630971e-01 9.76931632e-01 1.59455627e-01 7.66940415e-01 7.15494037e-01 7.19058275e-01 -3.13391238e-01 -3.48437637e-01 6.22657776e-01 1.69060087e+00 -1.00273803e-01 9.01127577e-01 -1.63942710e-01 7.54815638e-01 5.18586278e-01 5.20707726e-01 2.98317879e-01 2.13264853e-01 7.40928054e-01 -1.02371290e-01 2.74896204e-01 -6.21965706e-01 3.81985784e-01 7.41262853e-01 5.03071845e-01 -5.17675281e-01 3.32770497e-01 -3.41524929e-01 4.57343549e-01 -1.41295242e+00 -1.38707995e+00 -1.55149832e-01 2.18652320e+00 7.43691504e-01 -1.01695740e+00 -2.57815063e-01 -1.87886581e-01 1.33202672e+00 2.48427644e-01 -2.61883706e-01 -3.05455015e-03 -4.20991629e-01 3.14686358e-01 4.21142042e-01 8.27628076e-01 -1.05034935e+00 9.36247468e-01 7.21467495e+00 6.86188936e-01 -6.28445029e-01 5.85033298e-01 2.71473557e-01 5.22382632e-02 -1.72092803e-02 -5.89828752e-02 -8.43488336e-01 -4.80959229e-02 7.47065425e-01 -2.12940067e-01 1.00297117e+00 3.90405029e-01 3.86506736e-01 -1.62527025e-01 -6.02889895e-01 1.46758485e+00 8.68491709e-01 -8.69108737e-01 -9.17889252e-02 7.24164397e-02 8.09042513e-01 -2.13629663e-01 3.01042497e-01 -4.99825120e-01 3.01169664e-01 -1.17177010e+00 3.41080308e-01 9.71069217e-01 1.01466227e+00 -4.69840795e-01 3.71008277e-01 -7.68279508e-02 -1.03590417e+00 -5.35599850e-02 -8.02935660e-01 3.21380138e-01 2.92130291e-01 3.99181068e-01 -7.20797539e-01 7.31433749e-01 9.01140809e-01 8.89258444e-01 -5.51937759e-01 1.03878105e+00 6.09869435e-02 2.49743909e-01 3.09534892e-02 1.03498447e+00 -8.97132337e-01 -5.59711516e-01 1.15100646e+00 1.03131402e+00 6.06836677e-01 5.47587395e-01 -3.40928733e-01 1.00194287e+00 2.61504918e-01 -2.41866216e-01 -6.14816248e-01 4.19134796e-01 5.60019732e-01 1.61859655e+00 -3.57126266e-01 -9.49945077e-02 -4.36776221e-01 1.59500384e+00 -1.20114818e-01 6.94461405e-01 -6.42398298e-01 2.15472117e-01 7.01372504e-01 -1.93140879e-01 5.42615294e-01 -2.19085753e-01 -2.00264379e-01 -1.35576177e+00 -1.77657738e-01 -7.78864324e-01 1.05784051e-01 -1.20095539e+00 -1.40593517e+00 6.52821541e-01 1.48346037e-01 -1.11874449e+00 7.29252994e-02 -1.79327458e-01 -4.82098639e-01 1.52333426e+00 -1.52661574e+00 -1.56897593e+00 -3.51346970e-01 9.55977142e-01 6.58673167e-01 -5.15518427e-01 7.42615044e-01 1.81208208e-01 -5.70032477e-01 3.45551431e-01 1.90731287e-01 -4.64408576e-01 1.17800701e+00 -7.93037415e-01 1.56568423e-01 1.32157910e+00 -1.37527630e-01 1.06057370e+00 1.08366919e+00 -9.65173423e-01 -1.70029855e+00 -9.56180453e-01 4.31118816e-01 -5.94869733e-01 1.32072642e-01 1.24839827e-01 -1.13719535e+00 7.19786763e-01 5.86848378e-01 2.45519787e-01 5.12887537e-01 -4.08753037e-01 -4.49828088e-01 -1.53635025e-01 -1.82522523e+00 1.77776903e-01 7.24454820e-01 -6.94631875e-01 -9.53973651e-01 2.84587741e-01 1.28829390e-01 -2.60719478e-01 -1.05372393e+00 3.13628346e-01 5.61490119e-01 -9.03432131e-01 1.55871022e+00 1.47096008e-01 -1.19418077e-01 -7.14902222e-01 -2.68972427e-01 -1.13176322e+00 -7.05072403e-01 -8.08298826e-01 -2.48038039e-01 1.53849936e+00 -4.89622265e-01 -5.12164056e-01 2.16370955e-01 3.29143465e-01 1.39555782e-01 3.05207372e-01 -9.04779315e-01 -5.63540518e-01 -4.66268271e-01 3.35780919e-01 3.41601819e-01 1.04227149e+00 -3.51574779e-01 3.41861658e-02 -8.65405142e-01 8.50613832e-01 1.56287825e+00 -5.04072160e-02 4.90755022e-01 -1.08915079e+00 -2.31699795e-01 1.64698571e-01 -2.39634544e-01 -5.10467470e-01 3.86669606e-01 -5.56342781e-01 5.65141588e-02 -1.16517878e+00 6.92054510e-01 2.87321389e-01 -4.22680937e-02 -5.34156375e-02 -2.74187535e-01 5.21929204e-01 -2.41014853e-01 6.81992769e-01 -9.65583846e-02 3.45942438e-01 1.11679351e+00 3.88530791e-01 2.02022213e-02 -1.47225350e-01 -7.15326726e-01 5.55360198e-01 5.29959440e-01 -9.76762250e-02 -3.29296261e-01 -3.25091809e-01 -7.18859136e-01 4.36296731e-01 6.26084208e-01 -9.91593122e-01 3.05114537e-01 -2.79880106e-01 7.76568472e-01 -4.37179714e-01 8.33834767e-01 -7.32892394e-01 7.25259781e-01 -2.46717827e-03 6.05317801e-02 -2.15731546e-01 2.43220106e-01 8.26595068e-01 -1.59887344e-01 8.84521455e-02 1.28465414e+00 -2.40394592e-01 -4.96341765e-01 1.00952514e-01 -1.63324222e-01 -8.05860519e-01 9.00636792e-01 -4.67173517e-01 -4.00598049e-01 -4.30728465e-01 -8.19303215e-01 -4.59919125e-01 5.86169600e-01 4.94704247e-01 1.17317593e+00 -1.35743773e+00 -1.09532475e+00 6.09250724e-01 -4.95027989e-01 -5.79049468e-01 6.01047814e-01 9.42515671e-01 -2.62543261e-01 3.09192538e-01 -6.54660761e-01 -2.75497854e-01 -1.89982116e+00 7.09802568e-01 3.30229014e-01 5.32936156e-01 -5.27670562e-01 9.99587953e-01 2.34028213e-02 1.58972908e-02 -2.32505977e-01 6.49182081e-01 -6.24526024e-01 -2.67413259e-01 1.19642389e+00 7.80002475e-01 -3.13978136e-01 -1.57964385e+00 -4.72864896e-01 9.27944779e-01 -2.35643178e-01 -4.46359485e-01 1.57350838e+00 -9.71388400e-01 -8.97272527e-01 -2.48086266e-02 8.75473082e-01 2.87899643e-01 -1.19287407e+00 -3.41805756e-01 -2.27954239e-01 -1.14989662e+00 3.50895911e-01 -5.41666389e-01 -9.24204588e-01 4.57201451e-01 1.06153178e+00 -6.11888409e-01 1.50333226e+00 -2.54841913e-02 2.40862474e-01 -3.19472313e-01 4.46741611e-01 -5.02255201e-01 -1.16068654e-01 -5.52644171e-02 1.45743859e+00 -1.10230339e+00 4.53618258e-01 -7.87646353e-01 -4.52170879e-01 1.09484506e+00 4.42090839e-01 -4.02108073e-01 6.49118721e-01 1.80992827e-01 -1.57158360e-01 -6.68096766e-02 -4.55110103e-01 1.31554365e-01 4.42927152e-01 8.65062118e-01 3.69529873e-01 -3.13678324e-01 -2.86250859e-01 3.08352977e-01 2.46232048e-01 2.36608416e-01 9.04654860e-01 5.63674212e-01 -5.82682073e-01 -7.84535170e-01 -1.41121495e+00 7.65496725e-03 -7.23245978e-01 -3.97691056e-02 -9.59364697e-02 -5.32763498e-03 -3.35182607e-01 1.31749725e+00 -1.84902176e-01 -1.58139005e-01 -1.00565642e-01 9.03455019e-02 1.00614345e+00 -3.68369162e-01 -8.73752162e-02 6.17196321e-01 -2.35091373e-01 -5.71383238e-01 -9.93690073e-01 -1.11437631e+00 -6.87470376e-01 -1.82144389e-01 -3.55435431e-01 -1.28155649e-01 4.19087768e-01 6.00273728e-01 3.82260948e-01 -8.22818130e-02 7.78476298e-01 -1.17999125e+00 -5.75169981e-01 -1.31218016e+00 -9.38150525e-01 1.32895932e-01 7.18742669e-01 -5.98837197e-01 -5.77247024e-01 4.59999621e-01]	[12.85014533996582, -0.002096820157021284]
a81b2951-b40d-4e18-a4d1-029cf650be3f	textbox-2-0-a-text-generation-library-with	2212.13005	null	https://arxiv.org/abs/2212.13005v1	https://arxiv.org/pdf/2212.13005v1.pdf	TextBox 2.0: A Text Generation Library with Pre-trained Language Models	To facilitate research on text generation, this paper presents a comprehensive and unified library, TextBox 2.0, focusing on the use of pre-trained language models (PLMs). To be comprehensive, our library covers $13$ common text generation tasks and their corresponding $83$ datasets and further incorporates $45$ PLMs covering general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight PLMs. We also implement $4$ efficient training strategies and provide $4$ generation objectives for pre-training new PLMs from scratch. To be unified, we design the interfaces to support the entire research pipeline (from data loading to training and evaluation), ensuring that each step can be fulfilled in a unified way. Despite the rich functionality, it is easy to use our library, either through the friendly Python API or command line. To validate the effectiveness of our library, we conduct extensive experiments and exemplify four types of research scenarios. The project is released at the link: https://github.com/RUCAIBox/TextBox.	['Ji-Rong Wen', 'Jian-Yun Nie', 'Wayne Xin Zhao', 'Yuhao Wang', 'Xiaoxue Cheng', 'Zican Dong', 'Wenxun Dai', 'Zhuohao Yu', 'Yiwen Hu', 'Zhipeng Chen', 'Junyi Li', 'Tianyi Tang']	2022-12-26	null	null	null	null	['dialogue', 'abstractive-text-summarization', 'data-to-text-generation', 'story-generation', 'question-generation', 'task-oriented-dialogue-systems']	['natural-language-processing', 'natural-language-processing', 'natural-language-processing', 'natural-language-processing', 'natural-language-processing', 'natural-language-processing']	[ 3.99576351e-02 4.08508301e-01 -3.17614019e-01 -3.86494905e-01 -1.01607490e+00 -7.79305577e-01 7.90735841e-01 -1.98057920e-01 -2.48339415e-01 9.57199156e-01 1.83494002e-01 -7.95371175e-01 3.19339037e-01 -7.43949354e-01 -5.37293613e-01 -1.67049497e-01 2.12385327e-01 4.90446627e-01 -4.37556326e-01 -3.00822139e-01 3.88292193e-01 1.89358711e-01 -1.27541876e+00 2.99719274e-01 1.08290982e+00 4.17109221e-01 4.61367965e-01 7.26134837e-01 -3.35008979e-01 5.36321044e-01 -8.39179218e-01 -8.54273200e-01 1.45335823e-01 -3.93422872e-01 -1.15295458e+00 -2.45325908e-01 3.49745713e-02 -4.67039287e-01 -7.45239928e-02 8.12802851e-01 9.35205221e-01 1.92576554e-02 3.38824719e-01 -1.26495075e+00 -9.18021381e-01 1.25379562e+00 -1.17052935e-01 -2.07133129e-01 7.43913412e-01 2.90280938e-01 1.07496178e+00 -1.09934199e+00 7.34601438e-01 1.11983383e+00 3.85719806e-01 7.72708416e-01 -9.58758712e-01 -8.85929823e-01 1.83928892e-01 -2.66754568e-01 -1.08459198e+00 -8.11832607e-01 4.60139483e-01 -3.15411508e-01 1.30813777e+00 2.41802573e-01 4.44102854e-01 1.50851166e+00 9.15973336e-02 1.09394252e+00 8.73669744e-01 -5.83616734e-01 -1.81624264e-01 3.49614412e-01 1.34690955e-01 7.27152824e-01 1.74372330e-01 -2.57666022e-01 -5.27703047e-01 -1.49178252e-01 5.31386375e-01 -4.84726012e-01 -1.43589169e-01 3.11014026e-01 -1.51038456e+00 6.27187729e-01 -1.14046194e-01 2.71435082e-01 -7.52840489e-02 7.03100041e-02 3.45114738e-01 4.12192047e-01 4.92521256e-01 5.38376868e-01 -6.04995370e-01 -5.86734831e-01 -7.89936781e-01 4.25253689e-01 1.07094574e+00 1.82266653e+00 6.80801511e-01 2.69097120e-01 -5.32205522e-01 1.00465381e+00 2.30092868e-01 5.60702622e-01 6.95105672e-01 -7.11766720e-01 8.68600011e-01 5.28414488e-01 3.09015781e-01 -3.61922145e-01 -2.58511871e-01 -2.83393174e-01 -8.01868021e-01 -5.64177036e-01 1.97048217e-01 -7.10857570e-01 -6.32869124e-01 1.69343507e+00 5.20055518e-02 -3.73715281e-01 7.98287913e-02 4.36945915e-01 1.15631247e+00 8.29654038e-01 6.96266666e-02 -2.66296327e-01 1.32981372e+00 -1.09992528e+00 -8.34656715e-01 -4.99746680e-01 1.08259153e+00 -1.22581184e+00 1.34399509e+00 1.02752700e-01 -1.52115452e+00 -5.60303986e-01 -6.80473566e-01 -3.61978501e-01 -7.22593427e-01 6.67021096e-01 6.98569179e-01 7.82175958e-01 -1.28619564e+00 5.36114872e-01 -7.42005110e-01 -3.69993180e-01 -3.46033424e-02 1.75371751e-01 1.18260412e-02 5.18703572e-02 -1.38637364e+00 8.35912764e-01 4.21815872e-01 4.44478914e-02 -6.16489351e-01 -5.99226713e-01 -8.86127055e-01 -1.95290312e-01 3.29209641e-02 -8.61959875e-01 1.73469782e+00 -4.11894530e-01 -1.82585180e+00 7.15568841e-01 -3.31369609e-01 -7.70595223e-02 6.07888639e-01 -4.42141861e-01 -1.07513912e-01 -2.87859470e-01 1.77965581e-01 7.37580776e-01 4.37707812e-01 -8.02162707e-01 -4.80224669e-01 1.12827964e-01 2.13720053e-02 3.59984279e-01 -3.90993685e-01 4.73112345e-01 -5.75518310e-01 -9.11765397e-01 -4.72289145e-01 -8.55788291e-01 -1.09330818e-01 -6.70579135e-01 -7.43000567e-01 -5.85849702e-01 3.68643910e-01 -8.05247903e-01 1.64069808e+00 -1.67883754e+00 1.90755688e-02 -3.22884619e-01 -6.19127341e-02 1.48872137e-01 -1.95388660e-01 8.91939342e-01 -1.60170142e-02 5.28404593e-01 -1.85443580e-01 -7.46426702e-01 5.29081583e-01 -1.75500035e-01 -2.66779810e-01 -1.72599033e-01 3.28890741e-01 1.25426102e+00 -8.77609313e-01 -3.76903176e-01 8.98531824e-02 2.35959738e-01 -3.46006721e-01 4.11213309e-01 -3.67560416e-01 1.50658280e-01 -4.78820652e-01 7.16623664e-01 5.60204625e-01 -2.99672663e-01 2.40325257e-01 2.36901522e-01 -4.47146028e-01 7.85865426e-01 -1.05400109e+00 1.95989823e+00 -5.26215911e-01 5.45059264e-01 1.54962182e-01 -6.64999843e-01 1.00126743e+00 6.32080376e-01 1.18295245e-01 -4.61577624e-01 -2.15635542e-02 4.15581793e-01 -3.85619223e-01 -3.14334720e-01 1.00154626e+00 3.13620180e-01 -2.43776172e-01 1.26154089e+00 2.37969115e-01 -2.91929781e-01 8.00661683e-01 2.78271019e-01 8.30962300e-01 3.91406029e-01 1.89945102e-01 -1.46488145e-01 2.95288652e-01 -6.89703077e-02 2.29617566e-01 8.69136751e-01 9.87126604e-02 2.51587421e-01 3.29677522e-01 5.44933230e-03 -1.01434207e+00 -7.63987243e-01 -1.25803677e-02 1.46034598e+00 -3.91132712e-01 -7.79885054e-01 -9.17835772e-01 -6.77635908e-01 -4.52062339e-01 1.06325400e+00 -1.44890025e-01 1.45718932e-01 -6.90420687e-01 -1.03255451e+00 7.19021201e-01 4.66699928e-01 6.01071298e-01 -1.40529108e+00 -2.68910468e-01 1.79772273e-01 -6.23825967e-01 -9.55064595e-01 -5.63870490e-01 -1.29049093e-01 -7.85255969e-01 -5.12727857e-01 -7.58358300e-01 -1.02859306e+00 5.94259679e-01 1.73212543e-01 1.37947989e+00 -1.66195980e-03 -1.25865057e-01 3.36378127e-01 -5.45192540e-01 -5.30882597e-01 -6.37812436e-01 5.96976519e-01 -2.90609658e-01 -6.84648216e-01 2.62678355e-01 -3.07960570e-01 -4.46640491e-01 1.15216598e-01 -6.91089869e-01 5.79485595e-01 6.73107147e-01 7.33531713e-01 1.23351499e-01 -2.84182131e-01 7.52607107e-01 -7.45638788e-01 1.32155609e+00 -3.94936740e-01 -4.30075794e-01 4.24188048e-01 -8.32706928e-01 -4.09365557e-02 6.34733975e-01 -1.13686763e-01 -1.19227397e+00 -1.41324222e-01 -4.99181569e-01 3.29263687e-01 -2.69215018e-01 7.90487289e-01 -1.39566496e-01 4.65232104e-01 4.54236120e-01 4.42118138e-01 -1.52614519e-01 -6.18566394e-01 6.49911523e-01 1.08385825e+00 2.76332907e-02 -8.47505450e-01 6.31738186e-01 -2.40788743e-01 -7.54661739e-01 -6.13183498e-01 -4.89835083e-01 3.81558612e-02 -4.04619724e-01 -1.06918938e-01 4.66053188e-01 -9.77460325e-01 -3.36231202e-01 5.96353471e-01 -1.36109805e+00 -7.46213317e-01 -4.03863937e-02 2.50384450e-01 -5.67559123e-01 2.78163135e-01 -9.87268209e-01 -6.75271749e-01 -1.08827305e+00 -1.29188502e+00 1.07884526e+00 1.77885577e-01 -4.81472284e-01 -1.07549667e+00 -6.32614642e-02 4.43484753e-01 4.84989703e-01 -1.81766912e-01 9.50583696e-01 -5.78396916e-01 -3.11076313e-01 -2.88215607e-01 -1.44858301e-01 2.34019011e-01 9.21800509e-02 4.28027749e-01 -8.55348051e-01 -4.10460681e-01 -3.15260947e-01 -4.93376166e-01 3.49928558e-01 5.58480173e-02 1.14961565e+00 -5.26949823e-01 -3.48465353e-01 4.50402588e-01 9.04974222e-01 1.84261143e-01 6.00955963e-01 2.12615415e-01 4.88356084e-01 6.50986254e-01 5.11266470e-01 5.28119624e-01 7.07310677e-01 4.08079833e-01 -1.21587448e-01 -8.27034935e-02 6.22283891e-02 -3.49135429e-01 7.88861930e-01 1.29730582e+00 -1.71264246e-01 -4.50459301e-01 -8.29123676e-01 3.42285544e-01 -1.69487548e+00 -9.04957056e-01 -1.02735370e-01 2.16207504e+00 1.46387315e+00 -7.91517496e-02 1.77792776e-02 -2.64788091e-01 5.64285040e-01 3.18008885e-02 -2.41464704e-01 -5.91765404e-01 5.27035818e-02 4.92926717e-01 7.44917393e-02 6.54705465e-01 -8.76654327e-01 1.19268715e+00 7.28100014e+00 8.80463183e-01 -1.00829566e+00 5.23285940e-03 5.59262455e-01 -2.75334686e-01 -4.67290342e-01 -1.35995552e-01 -1.06254566e+00 5.14028490e-01 1.19317710e+00 -7.02847600e-01 5.96283495e-01 8.05100441e-01 5.31176209e-01 2.82206774e-01 -1.12636745e+00 7.10160911e-01 -2.10945964e-01 -1.29665554e+00 2.86765009e-01 -1.84941143e-01 5.60986042e-01 9.23910812e-02 3.59410904e-02 7.58653581e-01 7.02618897e-01 -9.44442689e-01 6.78030550e-01 1.75208420e-01 9.14528012e-01 -5.55351734e-01 4.57865983e-01 3.66585016e-01 -9.66741800e-01 1.43521488e-01 -1.99356049e-01 -1.73734650e-01 2.85832286e-01 4.69488800e-01 -9.43144560e-01 8.92036498e-01 4.04522687e-01 7.55677462e-01 -6.17811084e-01 4.43022013e-01 -5.00421643e-01 5.68659544e-01 -9.41348672e-02 -2.06841648e-01 -4.84712310e-02 -2.74284631e-01 1.98866814e-01 1.68006170e+00 6.18255913e-01 -1.10928230e-01 -3.90321463e-02 9.43981826e-01 -3.20652843e-01 4.66253370e-01 -4.80123550e-01 -4.36497688e-01 6.00193739e-01 1.39041698e+00 -3.22343707e-01 -5.36014974e-01 -4.37911928e-01 9.95142102e-01 3.79269063e-01 4.77865905e-01 -7.86931396e-01 -8.54164958e-01 4.90234017e-01 -1.55525312e-01 -2.20149904e-01 -4.19585139e-01 -2.93425202e-01 -1.39414907e+00 1.40956998e-01 -1.15979505e+00 1.76184759e-01 -9.17246819e-01 -1.12026703e+00 6.74870551e-01 1.65096149e-01 -9.16671813e-01 -6.19454265e-01 -5.67808270e-01 -5.68002224e-01 1.19803309e+00 -1.33637714e+00 -1.03825963e+00 -3.14139932e-01 3.69771123e-01 8.00893903e-01 -2.02277880e-02 1.12061775e+00 4.56420094e-01 -1.15836322e+00 8.63600791e-01 -4.52854335e-02 3.77250075e-01 1.01781642e+00 -1.28928900e+00 9.79040146e-01 8.14842701e-01 -1.93607569e-01 1.14432776e+00 4.92040098e-01 -6.73807085e-01 -1.55793095e+00 -1.21678388e+00 1.43599343e+00 -5.86504340e-01 7.38542557e-01 -6.19120896e-01 -4.40867156e-01 1.04683244e+00 6.41190588e-01 -8.43613148e-01 8.21611226e-01 1.07582800e-01 1.92887057e-02 1.79808289e-01 -6.84468448e-01 9.54758883e-01 1.09211433e+00 -3.71762246e-01 -3.64763975e-01 6.68676198e-01 9.01955009e-01 -6.29091263e-01 -1.06736255e+00 2.13600397e-01 4.58364069e-01 -5.50207138e-01 5.95299900e-01 -5.40523469e-01 7.34530091e-01 4.03988771e-02 2.17152104e-01 -1.47358644e+00 -1.68301210e-01 -1.24859893e+00 -1.43548712e-01 1.43226421e+00 1.00828695e+00 -8.68274331e-01 4.73179340e-01 8.36075306e-01 -4.58288521e-01 -6.69215262e-01 -3.66292626e-01 -4.95782197e-01 3.22036326e-01 -6.15406692e-01 8.36337447e-01 9.41206992e-01 5.25097787e-01 6.22794509e-01 -3.82506847e-01 -3.52527946e-01 2.03426316e-01 2.21010447e-01 1.01048422e+00 -6.76323116e-01 -3.21318477e-01 -7.38755703e-01 5.94936967e-01 -1.52923524e+00 3.59005779e-02 -1.20251763e+00 -4.56608459e-02 -1.90592766e+00 1.07235380e-01 -5.54652989e-01 1.24416508e-01 7.00405300e-01 -5.08002043e-01 4.65914533e-02 2.51747847e-01 1.19729817e-01 -3.74856532e-01 5.40959775e-01 1.28124976e+00 6.61353320e-02 -3.58024627e-01 1.42063230e-01 -1.11264002e+00 2.34268993e-01 1.20760763e+00 -1.52335480e-01 -3.78730476e-01 -1.00142992e+00 2.91976362e-01 -7.92658553e-02 -6.44224361e-02 -4.85221237e-01 6.71224818e-02 -1.66497484e-01 9.20629352e-02 -5.02528667e-01 1.37777939e-01 -6.37179986e-02 8.58459473e-02 1.67414919e-01 -5.40937126e-01 3.72262269e-01 3.53689969e-01 -2.31005535e-01 4.72720526e-02 -3.75775367e-01 2.49371782e-01 -3.84041250e-01 -2.21704215e-01 3.06622565e-01 -5.68365753e-01 7.40374252e-02 6.86890423e-01 1.88041613e-01 -6.94006622e-01 -5.46431243e-01 -4.90396261e-01 4.45323050e-01 3.17303509e-01 5.28968990e-01 3.59402835e-01 -1.09867954e+00 -9.02288795e-01 1.71118721e-01 1.36917785e-01 4.27042246e-02 -9.90298018e-03 5.60166895e-01 -4.72471595e-01 7.64195144e-01 8.95422027e-02 -5.61067685e-02 -9.21104610e-01 1.42586559e-01 1.79633364e-01 -3.84698361e-01 -2.76419997e-01 6.98307753e-01 -3.52179617e-01 -7.65193284e-01 1.99299768e-01 -4.40921813e-01 9.96717438e-03 -1.16694592e-01 6.15259528e-01 4.77215409e-01 1.71848834e-01 -1.26136839e-01 7.48767629e-02 1.25818864e-01 -1.48879349e-01 -3.00660849e-01 1.09936488e+00 -1.06049687e-01 -3.53788167e-01 3.03077400e-01 8.63133729e-01 1.05845174e-02 -7.46717870e-01 -1.02953099e-01 -1.07954472e-01 -1.57573540e-02 -3.24582547e-01 -1.06241155e+00 -7.74890304e-01 7.25571692e-01 -2.17609834e-02 2.91047841e-01 9.64521706e-01 -2.41678312e-01 7.72300005e-01 4.41915721e-01 2.50037193e-01 -1.33794010e+00 -1.13084972e-01 7.12020099e-01 1.01397824e+00 -9.62609351e-01 -3.48874442e-02 -3.32007468e-01 -5.97691178e-01 1.00408781e+00 6.53317750e-01 5.31928003e-01 3.95062745e-01 3.93595427e-01 8.44515637e-02 1.31782174e-01 -1.12014544e+00 9.35859308e-02 -2.56800409e-02 4.92650777e-01 1.25745642e+00 1.63150489e-01 -6.65378749e-01 7.45362163e-01 -8.83762836e-01 1.23513050e-01 5.35491884e-01 1.12897491e+00 -1.35287821e-01 -1.61793411e+00 -1.32821560e-01 4.88885790e-01 -5.34264982e-01 -5.90866983e-01 -5.60115874e-01 7.10904896e-01 -3.12532514e-01 1.26605451e+00 -1.25226989e-01 -2.25906163e-01 3.03210467e-01 5.15957355e-01 2.87588209e-01 -9.26086545e-01 -8.14690650e-01 -3.99538921e-03 4.49989080e-01 -3.79527301e-01 1.18186213e-02 -4.68586028e-01 -1.00701237e+00 -6.22800589e-01 -1.60219476e-01 2.65879303e-01 7.09747732e-01 6.19575620e-01 7.17025161e-01 2.32331946e-01 4.80864525e-01 -7.58563936e-01 -5.62537789e-01 -1.52323794e+00 -6.92241192e-02 9.91601571e-02 -2.28993461e-01 -1.53866827e-01 -2.09438175e-01 3.40479821e-01]	[11.478611946105957, 9.12226676940918]
95715e21-d2ad-4aed-bdaf-d2bc4533384b	deeper-profiles-and-cascaded-recurrent-and	null	null	https://doi.org/10.1038/s41598-019-48786-x	https://www.nature.com/articles/s41598-019-48786-x.pdf	Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction	Protein Secondary Structure prediction has been a central topic of research in Bioinformatics for decades. In spite of this, even the most sophisticated ab initio SS predictors are not able to reach the theoretical limit of three-state prediction accuracy (88–90%), while only a few predict more than the 3 traditional Helix, Strand and Coil classes. In this study we present tests on different models trained both on single sequence and evolutionary profile-based inputs and develop a new state-of-the-art system with Porter 5. Porter 5 is composed of ensembles of cascaded Bidirectional Recurrent Neural Networks and Convolutional Neural Networks, incorporates new input encoding techniques and is trained on a large set of protein structures. Porter 5 achieves 84% accuracy (81% SOV) when tested on 3 classes and 73% accuracy (70% SOV) on 8 classes on a large independent set. In our tests Porter 5 is 2% more accurate than its previous version and outperforms or matches the most recent predictors of secondary structure we tested. When Porter 5 is retrained on SCOPe based sets that eliminate homology between training/testing samples we obtain similar results. Porter is available as a web server and standalone program at http://distilldeep.ucd.ie/porter/ alongside all the datasets and alignments.	['Mirko Torrisi', 'Gianluca Pollastri', 'Manaz Kaleel']	2019-10-12	null	null	null	scientific-reports-2019-10	['protein-secondary-structure-prediction']	['medical']	[ 3.98081630e-01 8.08743536e-02 -1.89748362e-01 -2.64118642e-01 -7.68554449e-01 -4.13594097e-01 3.96074951e-01 4.00494635e-01 -7.04514086e-01 1.23641670e+00 -1.24833230e-02 -9.24246728e-01 1.40945047e-01 -3.80826950e-01 -8.84968579e-01 -9.80903268e-01 -5.35638444e-02 7.73863733e-01 5.40745676e-01 -5.63350379e-01 2.47544616e-01 5.90777159e-01 -1.37342691e+00 6.61129713e-01 8.33207726e-01 5.97521842e-01 4.61561203e-01 9.07888234e-01 -4.54798266e-02 6.87754452e-01 -4.42686051e-01 -3.21688831e-01 -7.41803721e-02 -5.61901152e-01 -1.08512378e+00 -5.30867577e-01 2.94708014e-01 2.12828502e-01 9.98557806e-02 4.30395395e-01 8.07130456e-01 -3.72802436e-01 5.90467095e-01 -5.11544168e-01 -5.51788926e-01 4.53493387e-01 -2.02781141e-01 2.97445416e-01 4.57214415e-01 2.53913194e-01 9.40231621e-01 -8.95687282e-01 9.97629344e-01 6.87617123e-01 9.83413875e-01 4.70447332e-01 -1.71046448e+00 -4.04027373e-01 -3.51287961e-01 4.92956877e-01 -9.76455748e-01 -2.51272351e-01 2.64495224e-01 -2.37846851e-01 1.92143023e+00 1.91919178e-01 6.58031583e-01 1.31635642e+00 6.95057034e-01 6.75208688e-01 1.24259114e+00 -5.90316951e-01 1.76227883e-01 5.87174408e-02 4.24642742e-01 6.39539063e-01 -5.50001524e-02 6.62278906e-02 -2.98719496e-01 -4.88477975e-01 2.86478430e-01 -1.57042295e-01 -3.38269740e-01 -3.65436822e-01 -1.15342486e+00 8.16940486e-01 3.76398444e-01 5.12493551e-01 -5.66385865e-01 -5.01327753e-01 4.85624045e-01 5.55472016e-01 3.09809208e-01 5.21406829e-01 -1.11742747e+00 -1.82819530e-01 -8.21413696e-01 2.93492913e-01 1.02401483e+00 3.75994176e-01 5.80413401e-01 -6.58734962e-02 3.10458064e-01 8.34564030e-01 -1.46646887e-01 2.35376760e-01 9.16462541e-01 -2.74752051e-01 -1.11461161e-02 6.39204443e-01 9.19447318e-02 -4.04052734e-01 -8.82241368e-01 -5.32016397e-01 -7.32030809e-01 2.91223764e-01 5.32616615e-01 -4.05766293e-02 -1.02866077e+00 1.49775791e+00 1.50290191e-01 -2.11482346e-01 3.36866230e-01 6.41429305e-01 9.38751996e-01 7.30572104e-01 1.19478963e-01 -4.38489318e-01 1.10317826e+00 -7.03847408e-01 -2.06418440e-01 6.52670562e-02 8.93636107e-01 -9.45308328e-01 5.96644521e-01 6.07080281e-01 -9.67494369e-01 -4.95817870e-01 -1.22815084e+00 -1.29338279e-01 -5.85504770e-01 6.73897704e-03 3.59855622e-01 5.00265598e-01 -1.23596799e+00 9.83493149e-01 -9.23955142e-01 -7.57250607e-01 -3.08217779e-02 6.07646525e-01 -6.40579998e-01 3.45546126e-01 -1.26088929e+00 1.40144205e+00 5.43919802e-01 -1.63832799e-01 -6.01216316e-01 -4.92994100e-01 -3.44767511e-01 -1.04082279e-01 -7.02528059e-02 -5.85688412e-01 1.19875991e+00 -9.96141911e-01 -1.53729594e+00 1.06943762e+00 -3.88553023e-01 -9.64971066e-01 4.62198943e-01 -1.86179966e-01 -2.50425816e-01 1.51937921e-02 -2.08347455e-01 5.05946159e-01 1.15508243e-01 -7.57847071e-01 -4.47972029e-01 -3.58839363e-01 -3.87757689e-01 -3.46489847e-02 2.95109659e-01 1.31020382e-01 2.39144161e-01 -2.60340124e-01 2.38673249e-03 -1.06295466e+00 -3.91680777e-01 -4.31282938e-01 -2.27399513e-01 -2.13942736e-01 6.19645119e-01 -9.13064420e-01 9.13306653e-01 -1.43200207e+00 3.79302680e-01 9.72938687e-02 1.93935484e-02 8.50029409e-01 -1.59213439e-01 9.43386018e-01 -8.24881911e-01 -2.00635180e-01 -3.70370746e-01 3.03885639e-01 -3.97363484e-01 1.22754149e-01 -1.62129954e-01 5.01770139e-01 2.30288044e-01 7.33813167e-01 -6.57530904e-01 -9.39240009e-02 2.63776839e-01 7.18822718e-01 -3.53023946e-01 -3.85482796e-02 -2.64010668e-01 3.02561492e-01 -1.89711764e-01 4.29811150e-01 5.31513810e-01 -6.11509800e-01 6.14482522e-01 -5.65713383e-02 -2.22080752e-01 6.03846610e-01 -6.81412578e-01 1.47149515e+00 -6.75682351e-02 3.84254068e-01 -4.31370407e-01 -1.35668087e+00 1.16718078e+00 3.83221924e-01 4.87883419e-01 -5.34328222e-01 5.32652587e-02 4.18084979e-01 6.47172272e-01 -2.20311597e-01 1.42782554e-01 -9.95351002e-02 4.47190374e-01 3.45449001e-01 3.88096422e-01 3.97368759e-01 1.61139518e-01 1.55875042e-01 1.35085237e+00 5.11372864e-01 6.51870668e-01 -4.19731677e-01 6.89342320e-01 2.59234935e-01 5.78422546e-01 3.39157760e-01 -2.49968261e-01 4.61528748e-01 5.86408615e-01 -8.72540832e-01 -1.55233586e+00 -7.80591190e-01 -4.53919232e-01 1.23091733e+00 -3.54647279e-01 -5.77681899e-01 -7.55884051e-01 -6.19036555e-01 -1.49547860e-01 6.12521946e-01 -5.64055741e-01 -7.57525414e-02 -5.59972525e-01 -1.33103418e+00 4.19828206e-01 2.01306105e-01 1.30331099e-01 -1.40574205e+00 -5.55415154e-01 5.84672928e-01 -1.84336938e-02 -4.70008999e-01 2.40763932e-01 9.37873065e-01 -8.55985701e-01 -1.31090069e+00 -7.25553334e-01 -9.07097757e-01 9.30880830e-02 -1.27802521e-01 1.26096904e+00 1.34305567e-01 -2.90737063e-01 -5.76478124e-01 -4.58008528e-01 -4.62008685e-01 -7.75401115e-01 4.64669377e-01 6.28058985e-02 -4.55546528e-01 8.28624964e-01 -8.21135283e-01 -5.20902991e-01 4.40271497e-01 -5.48211634e-01 1.53813541e-01 8.30205202e-01 1.39450371e+00 5.38424551e-01 -8.06204915e-01 6.19744420e-01 -1.01537263e+00 3.37805927e-01 -3.79254580e-01 -4.47079092e-01 2.82263637e-01 -7.72481263e-01 2.94695973e-01 8.44144642e-01 -2.35711008e-01 -7.35806406e-01 4.13945824e-01 -7.38819540e-01 1.90933887e-02 -3.27821732e-01 4.60663557e-01 1.43572822e-01 -6.32430427e-04 1.05142319e+00 6.27299786e-01 2.24328786e-01 -6.21142864e-01 -1.03761233e-01 7.14901686e-01 1.76563680e-01 -2.54650235e-01 2.06487477e-01 -8.82456545e-03 -5.29937483e-02 -9.44387436e-01 -4.87460434e-01 -5.03699660e-01 -8.95728946e-01 2.04526395e-01 6.96394742e-01 -5.16062737e-01 -8.20205152e-01 5.20728886e-01 -9.83227849e-01 -2.50833094e-01 1.92184478e-01 3.52670312e-01 -7.25501597e-01 5.64826846e-01 -9.61549580e-01 -4.84369576e-01 -7.70340800e-01 -1.29547441e+00 8.40965450e-01 -9.47577804e-02 -3.72779340e-01 -6.12118363e-01 4.19784963e-01 1.96192235e-01 2.56311983e-01 2.33227730e-01 1.11426294e+00 -1.09819555e+00 -1.14162453e-01 -1.84862111e-02 1.07375979e-01 1.72401577e-01 -1.67879567e-04 3.08723956e-01 -8.40514779e-01 -3.51979405e-01 -3.35886657e-01 -4.42494929e-01 1.14842701e+00 3.56792957e-01 6.55223250e-01 -2.60726660e-02 -5.73498666e-01 5.04524529e-01 1.38400757e+00 4.84082639e-01 7.72060096e-01 7.49955058e-01 1.60861984e-01 3.86478454e-01 3.92531842e-01 8.70489776e-02 -1.87249765e-01 6.17804170e-01 2.65231967e-01 -2.05466360e-01 2.95873195e-01 2.60612704e-02 3.88774127e-01 6.85716748e-01 -5.14869690e-01 -9.21876580e-02 -1.24270332e+00 2.03027844e-01 -1.78997946e+00 -1.23092377e+00 -2.91887760e-01 2.08647919e+00 1.07744145e+00 3.14031094e-01 4.81118709e-01 1.13806926e-01 5.97509801e-01 -2.76502699e-01 -8.34067881e-01 -8.84496808e-01 -4.21951890e-01 5.45703351e-01 5.19846737e-01 3.84815156e-01 -1.07353020e+00 1.00379419e+00 7.14294004e+00 7.42859364e-01 -1.25738549e+00 -2.42017657e-01 8.06887805e-01 5.68996975e-03 1.77611977e-01 -1.17991097e-01 -9.36084270e-01 4.84707981e-01 1.70351994e+00 -7.67443106e-02 5.55631332e-02 9.32582200e-01 9.91722643e-02 1.22231469e-02 -8.59242499e-01 4.97340769e-01 -2.27807775e-01 -1.68515313e+00 -7.95187652e-02 1.99100837e-01 3.79305899e-01 7.64950991e-01 -1.56126410e-01 2.41023317e-01 4.84471112e-01 -1.21129489e+00 1.93296447e-01 4.22908336e-01 5.77933490e-01 -9.26770687e-01 1.02863860e+00 5.36803365e-01 -7.29704916e-01 2.48452321e-01 -5.59969068e-01 -1.46539491e-02 -1.60958581e-02 4.27904487e-01 -1.15340579e+00 6.19388878e-01 7.46718228e-01 6.87624872e-01 -5.90442419e-01 7.58658469e-01 2.63422169e-02 7.66885340e-01 -3.88023078e-01 -4.02349174e-01 3.89600426e-01 -3.91485065e-01 3.05849493e-01 1.44072533e+00 -8.93472135e-02 7.79531524e-02 2.48507969e-02 2.17594251e-01 2.57441759e-01 5.01705229e-01 -3.79503369e-01 9.98643264e-02 1.97845735e-02 9.92393732e-01 -5.40354192e-01 -4.54782188e-01 -3.75316978e-01 8.51043820e-01 7.40960479e-01 2.29071021e-01 -7.37258732e-01 -5.73542476e-01 7.80226111e-01 -8.22229385e-02 4.86900121e-01 9.77903232e-02 2.95123458e-01 -1.10596466e+00 -3.24903935e-01 -1.25042653e+00 4.32740301e-01 -8.05965245e-01 -1.18763864e+00 9.17530119e-01 -4.95048434e-01 -8.18533361e-01 -4.87468004e-01 -1.10706091e+00 -3.40283394e-01 1.07837307e+00 -1.11352718e+00 -9.91468191e-01 3.57115775e-01 1.25924915e-01 3.22671562e-01 -3.10660988e-01 1.32826853e+00 -7.59657333e-03 -5.62810302e-01 4.55602556e-01 8.70887756e-01 -8.67713764e-02 9.04890060e-01 -1.33980143e+00 6.41869962e-01 3.30629677e-01 -1.92685518e-02 7.46917009e-01 1.00454843e+00 -5.89349747e-01 -1.06491148e+00 -7.46356010e-01 1.20480311e+00 -4.48724836e-01 6.86527610e-01 -1.77398577e-01 -1.44965458e+00 7.82198906e-01 3.50631833e-01 -4.08946365e-01 1.07921207e+00 1.84051245e-01 -2.97685951e-01 3.09979200e-01 -9.93829727e-01 4.10677671e-01 1.03002012e+00 -2.37978652e-01 -8.69463801e-01 4.96269137e-01 5.14575481e-01 -3.21511120e-01 -1.08358824e+00 6.11983597e-01 8.59061956e-01 -1.47299969e+00 9.41075027e-01 -1.12467146e+00 4.67250109e-01 -1.41202733e-01 -3.29967178e-02 -1.11995983e+00 -4.77947593e-01 -3.81322443e-01 1.48514315e-01 4.65172768e-01 8.65787566e-01 -7.77205169e-01 1.17721808e+00 -3.58392373e-02 -1.43779367e-01 -1.25915408e+00 -8.34930122e-01 -5.69983721e-01 4.37609911e-01 1.82313994e-02 1.94255531e-01 7.45073855e-01 3.27999473e-01 7.60664761e-01 -3.29245090e-01 -3.57211828e-01 1.69661894e-01 3.72846812e-01 6.70246124e-01 -1.08935428e+00 -3.93065542e-01 -4.62490141e-01 -5.84717453e-01 -7.71108866e-01 1.51770905e-01 -1.06354475e+00 -3.46125752e-01 -1.32117319e+00 3.72299135e-01 8.48586112e-02 -5.94397664e-01 6.57508135e-01 -1.50614334e-02 2.93726712e-01 -2.52623081e-01 2.04875201e-01 -1.95726961e-01 3.42420429e-01 6.45572960e-01 -5.52495010e-02 -5.58045832e-03 1.83378588e-02 -2.58245468e-01 5.05400479e-01 9.75250661e-01 -2.21086293e-01 9.66962799e-02 3.70552659e-01 1.90171808e-01 -5.05688749e-02 3.74550209e-03 -9.56028283e-01 -2.41491631e-01 9.45697650e-02 8.28617930e-01 -9.59917307e-01 2.93033808e-01 -4.13219005e-01 3.97919416e-01 1.07539344e+00 -3.66527796e-01 2.59436429e-01 2.78124988e-01 2.86564887e-01 4.12801020e-02 -3.72042842e-02 9.36975718e-01 -1.57868803e-01 -5.38967073e-01 6.65260851e-02 -8.24039042e-01 -6.04972064e-01 8.42474401e-01 -3.16054523e-01 -2.37522945e-01 -1.15595661e-01 -9.97443080e-01 -7.32428282e-02 7.20648110e-01 1.13036834e-01 3.74277622e-01 -6.12397373e-01 -8.32944334e-01 2.03554437e-01 1.48284733e-01 -7.08908260e-01 7.88550079e-02 8.17014873e-01 -9.73395467e-01 9.51448619e-01 -5.99975348e-01 -8.00580680e-01 -1.80304754e+00 7.39271522e-01 5.26298761e-01 -4.50704753e-01 -5.04288912e-01 5.53853929e-01 -1.35262251e-01 -6.82299733e-01 -1.02350935e-01 -6.43068254e-02 -3.96155387e-01 -9.23196599e-02 4.16020364e-01 9.69190970e-02 4.29385126e-01 -7.66631484e-01 -3.79200548e-01 4.06635046e-01 -5.48368037e-01 3.49545121e-01 1.63953674e+00 3.89905781e-01 -7.61369839e-02 5.33330977e-01 1.21649659e+00 -4.15534407e-01 -7.47575998e-01 -1.21142725e-02 3.16509157e-01 1.41081303e-01 -3.69207799e-01 -1.19029617e+00 -4.31388766e-01 8.26506317e-01 7.80257404e-01 -6.03268156e-03 8.47454786e-01 -1.87217504e-01 7.64619291e-01 8.89334857e-01 2.89497048e-01 -7.05854118e-01 -5.28078854e-01 7.59327829e-01 6.68041527e-01 -1.22214830e+00 -1.31914355e-02 -4.74729240e-02 -4.23031986e-01 1.16356301e+00 3.79537702e-01 -1.78502083e-01 3.52251083e-01 1.83991447e-01 2.73187011e-01 1.59283727e-02 -1.32151401e+00 -1.04353011e-01 1.38572557e-02 5.41387260e-01 1.10028529e+00 -1.01318695e-01 -8.15946937e-01 8.29752907e-02 -2.84253299e-01 8.14143196e-02 3.33464354e-01 1.06204021e+00 -6.59451425e-01 -1.47261322e+00 -6.63321018e-02 5.20959020e-01 -7.88453341e-01 -2.58716106e-01 -7.65675604e-01 8.13262582e-01 -2.01897517e-01 5.44017851e-01 -2.86231726e-01 -4.81280923e-01 6.98722154e-02 5.36807358e-01 4.26561534e-01 -2.60125071e-01 -1.03261459e+00 6.75908988e-03 4.00613606e-01 -5.45658410e-01 -5.30590415e-01 -7.06012964e-01 -1.21245635e+00 -5.16163766e-01 -4.20926750e-01 6.73469305e-01 6.42139554e-01 7.73300588e-01 6.01548374e-01 2.47154728e-01 2.75524646e-01 -8.44834268e-01 -5.90448499e-01 -1.35943973e+00 -3.71584713e-01 3.51114541e-01 2.67782688e-01 -4.04459834e-01 -1.03207193e-01 1.21750832e-01]	[4.717804908752441, 5.562806129455566]
57bdbc61-518b-436a-a663-2edcfff9db0e	balancing-novelty-and-salience-adaptive	1701.03947	null	http://arxiv.org/abs/1701.03947v1	http://arxiv.org/pdf/1701.03947v1.pdf	Balancing Novelty and Salience: Adaptive Learning to Rank Entities for Timeline Summarization of High-impact Events	Long-running, high-impact events such as the Boston Marathon bombing often develop through many stages and involve a large number of entities in their unfolding. Timeline summarization of an event by key sentences eases story digestion, but does not distinguish between what a user remembers and what she might want to re-check. In this work, we present a novel approach for timeline summarization of high-impact events, which uses entities instead of sentences for summarizing the event at each individual point in time. Such entity summaries can serve as both (1) important memory cues in a retrospective event consideration and (2) pointers for personalized event exploration. In order to automatically create such summaries, it is crucial to identify the "right" entities for inclusion. We propose to learn a ranking function for entities, with a dynamically adapted trade-off between the in-document salience of entities and the informativeness of entities across documents, i.e., the level of new information associated with an entity for a time point under consideration. Furthermore, for capturing collective attention for an entity we use an innovative soft labeling approach based on Wikipedia. Our experiments on a real large news datasets confirm the effectiveness of the proposed methods.	['Claudia Niederée', 'Nattiya Kanhabua', 'Avishek Anand', 'Ujwal Gadiraju', 'Tuan Tran']	2017-01-14	null	null	null	null	['timeline-summarization']	['natural-language-processing']	[-2.27157772e-02 2.29824841e-01 -2.85112023e-01 -3.77254605e-01 -9.61146951e-01 -5.58417737e-01 8.28876317e-01 1.46658874e+00 -6.58828855e-01 9.21820223e-01 1.28339958e+00 1.90569982e-01 -3.44294608e-01 -9.04303253e-01 -7.23159671e-01 -3.84823412e-01 -3.15660268e-01 5.55886328e-01 4.41904098e-01 -9.42635611e-02 5.33227563e-01 1.87560886e-01 -1.31541657e+00 4.46079314e-01 8.92164171e-01 5.10774672e-01 3.65061671e-01 4.48295116e-01 -2.46534497e-01 9.80741441e-01 -9.27055418e-01 -3.57651025e-01 -3.04716319e-01 -2.63194621e-01 -8.32456648e-01 -3.77696753e-02 1.78067684e-01 -1.87721616e-03 -2.93680608e-01 8.80179703e-01 4.58327293e-01 6.78734601e-01 5.81096947e-01 -7.08713412e-01 -7.54980743e-02 1.44382393e+00 -4.83330578e-01 8.65527332e-01 4.87374425e-01 -2.02490464e-01 1.32921863e+00 -5.96450806e-01 8.85021031e-01 8.77853811e-01 5.42146087e-01 -8.94035921e-02 -7.74572551e-01 -1.19488724e-01 5.68082869e-01 2.07217693e-01 -1.02977538e+00 -4.86710340e-01 8.06760728e-01 -4.84972805e-01 8.41518342e-01 4.96393681e-01 7.91784883e-01 8.75756204e-01 1.23027995e-01 8.40640008e-01 2.69784600e-01 -2.96084702e-01 3.71865332e-01 -6.91087097e-02 5.44300139e-01 3.03443193e-01 3.21921647e-01 -7.52729714e-01 -9.75086689e-01 -4.51081157e-01 5.94980270e-02 -7.91253075e-02 -3.61828893e-01 2.36435398e-01 -1.41924059e+00 6.54557705e-01 3.07195157e-01 5.26289940e-01 -8.80758107e-01 2.38875914e-02 6.84940457e-01 -1.09703667e-01 7.34691143e-01 7.03060746e-01 -1.43281370e-01 -3.35677534e-01 -1.01503837e+00 4.94051039e-01 7.28161037e-01 5.16814172e-01 4.94801760e-01 -3.99372488e-01 -8.69384646e-01 6.95214629e-01 -1.51838169e-01 -1.03594266e-01 4.99983668e-01 -3.92716587e-01 7.79433787e-01 7.61472106e-01 2.79123276e-01 -1.33532262e+00 -5.68581164e-01 -6.32639647e-01 -6.59989595e-01 -4.70677555e-01 3.54513489e-02 -2.18837336e-01 -3.75039339e-01 1.86011374e+00 4.85127002e-01 2.09885225e-01 -7.56392702e-02 5.82230031e-01 8.72492075e-01 9.12834048e-01 2.59783417e-01 -5.82152188e-01 1.64039803e+00 -7.18761742e-01 -8.61148834e-01 -3.56372178e-01 4.97875333e-01 -5.24633527e-01 7.17890441e-01 -7.89680518e-03 -1.17456865e+00 -2.03225225e-01 -8.60512674e-01 -5.72655862e-03 -2.00607628e-01 1.50559852e-02 3.55438590e-01 -1.82944536e-02 -4.31479543e-01 7.42463648e-01 -5.37643611e-01 -4.60888952e-01 9.59220752e-02 -2.00289682e-01 -1.36582196e-01 4.24262106e-01 -1.42534530e+00 8.13897371e-01 9.02483165e-01 -1.62920296e-01 -5.95085025e-01 -6.60512865e-01 -7.69356787e-01 3.80342305e-01 7.60589242e-01 -6.19704425e-01 1.09942007e+00 -4.72493529e-01 -7.43839562e-01 5.68234324e-01 -2.82983452e-01 -6.80037558e-01 2.76986748e-01 -5.23104548e-01 -3.22143763e-01 2.74729759e-01 4.52055573e-01 2.42509872e-01 4.23988879e-01 -8.27077448e-01 -9.63222027e-01 -1.61810458e-01 2.41319597e-01 7.14859068e-01 -4.52533633e-01 1.32538855e-01 -4.83117342e-01 -8.90065551e-01 1.21744700e-01 -4.30869728e-01 -2.70235509e-01 -7.94216812e-01 -5.68092406e-01 -3.34128290e-01 4.35202926e-01 -7.07890987e-01 1.98397171e+00 -1.84551859e+00 2.44891703e-01 3.40885930e-02 2.48563334e-01 -5.45432381e-02 3.62562597e-01 8.16085279e-01 2.04405561e-01 1.82212144e-02 -1.36891171e-01 -2.76944607e-01 -1.18128732e-01 -2.46716991e-01 -5.84325671e-01 1.83998480e-01 -1.06739216e-01 6.20949566e-01 -1.30299556e+00 -5.13838410e-01 -3.06844711e-01 9.70385373e-02 -3.69023085e-01 3.65149789e-02 -3.94049197e-01 3.97263616e-01 -6.77896500e-01 2.85762757e-01 1.75959300e-02 -3.42836022e-01 -6.63618892e-02 -4.23365742e-01 -4.81004834e-01 6.09261453e-01 -9.93028581e-01 1.40754926e+00 -9.57794040e-02 5.67873180e-01 -3.66004288e-01 -7.28548110e-01 6.48835838e-01 1.74263224e-01 4.56452429e-01 -5.21120131e-01 -6.34047575e-03 -8.33767503e-02 -5.43227732e-01 -5.78524232e-01 1.33887386e+00 9.35795438e-03 -6.18187189e-01 7.61137784e-01 -1.41225845e-01 5.29963076e-01 7.48164475e-01 6.99325025e-01 1.16556919e+00 -3.94659549e-01 7.19406307e-01 -1.10223502e-01 3.39686334e-01 3.57894488e-02 6.09337389e-01 8.82894516e-01 2.72389650e-01 5.56926966e-01 6.97720647e-01 -3.90896440e-01 -8.21317852e-01 -5.30856788e-01 1.82572842e-01 1.19439757e+00 2.80778408e-01 -7.81190813e-01 -5.66549420e-01 -6.21408165e-01 -1.92885637e-01 1.23698127e+00 -5.77498972e-01 -2.09505767e-01 -8.84955168e-01 -8.75306070e-01 4.18330461e-01 2.87539095e-01 2.61324823e-01 -1.16982698e+00 -8.64380121e-01 5.38450062e-01 -9.79706287e-01 -8.55999291e-01 -8.57303739e-01 1.34740174e-01 -5.28426349e-01 -8.20197105e-01 -5.67113221e-01 -4.43940520e-01 7.21379578e-01 9.46746841e-02 1.08351099e+00 -2.05808446e-01 2.20752388e-01 3.00063729e-01 -6.32142007e-01 -3.43338996e-01 -2.42255598e-01 3.54779691e-01 1.29073877e-02 3.79835069e-01 -7.06674010e-02 -4.34739560e-01 -5.89457154e-01 -3.90587933e-02 -1.00246513e+00 2.33394131e-01 2.93735772e-01 6.42969787e-01 5.78104258e-01 2.03843400e-01 8.02717447e-01 -1.08384764e+00 1.01454294e+00 -9.69482303e-01 -5.69629157e-03 5.06037235e-01 -3.23738784e-01 1.90257624e-01 4.11393255e-01 -3.79772753e-01 -1.26448107e+00 -4.64462459e-01 -7.24887289e-03 2.76423156e-01 2.76623130e-01 1.07669163e+00 1.39149904e-01 8.19614232e-01 6.44842505e-01 1.79890022e-01 -9.09139514e-01 -4.81393516e-01 3.39052737e-01 3.61930966e-01 5.24317324e-01 -5.73577762e-01 3.88485193e-01 4.01281863e-01 -3.95685911e-01 -6.64067209e-01 -1.21589518e+00 -8.29868674e-01 -4.29422945e-01 -5.70106566e-01 6.36032045e-01 -8.91373336e-01 -4.95565444e-01 2.43019566e-01 -1.13483429e+00 1.19889185e-01 -6.93162978e-01 4.05539811e-01 -1.68197379e-01 4.28027689e-01 -2.96095401e-01 -6.43577754e-01 -4.97538984e-01 -4.75393206e-01 7.96356082e-01 5.31008065e-01 -6.23107135e-01 -9.15005445e-01 4.04578030e-01 9.11764354e-02 1.88397989e-01 5.52394509e-01 8.71628463e-01 -1.07528746e+00 -5.35996020e-01 -4.15378392e-01 2.72392668e-02 -4.60973263e-01 1.17216878e-01 -2.46217638e-01 -5.26938260e-01 -2.48707280e-01 -5.89504279e-02 7.69975036e-03 1.12735677e+00 4.80519712e-01 7.84979939e-01 -7.73826003e-01 -5.80080450e-01 6.54090494e-02 9.48236763e-01 8.87368154e-03 3.71987462e-01 4.77522790e-01 5.75201094e-01 6.01621449e-01 9.22803581e-01 9.74938750e-01 7.19526529e-01 6.30078137e-01 1.82052270e-01 2.78263360e-01 1.22862749e-01 -4.94978368e-01 3.96008790e-01 9.13457274e-01 1.92111395e-02 -6.94708705e-01 -7.90459573e-01 8.25797737e-01 -2.12691689e+00 -1.46489215e+00 1.54257314e-02 2.40755892e+00 9.15734529e-01 3.84345621e-01 4.99987341e-02 -1.25033975e-01 9.93919790e-01 7.11816192e-01 -3.93396378e-01 -2.37400625e-02 -3.35760027e-01 -4.87325996e-01 2.22026765e-01 5.06803453e-01 -1.11694622e+00 6.45588458e-01 4.95862150e+00 8.70702326e-01 -7.34236538e-01 1.77743733e-01 6.06869817e-01 -3.72589111e-01 -5.81025124e-01 1.75041780e-01 -9.82610643e-01 6.43153250e-01 7.58277416e-01 -7.98799634e-01 -1.71747804e-01 5.40954113e-01 3.09010297e-01 -5.23867965e-01 -8.59572828e-01 4.81753230e-01 2.67313182e-01 -1.65686405e+00 1.11445606e-01 -3.44377220e-01 4.93142039e-01 -1.83140725e-01 -4.09106612e-01 2.95355380e-01 1.85322743e-02 -2.30280906e-01 1.10070276e+00 7.51224160e-01 2.57842720e-01 -7.97168970e-01 5.88092446e-01 6.83001578e-01 -1.28180981e+00 -8.69669095e-02 -5.21292016e-02 1.67058244e-01 6.85428739e-01 9.47948158e-01 -9.29352582e-01 5.98875880e-01 4.49954212e-01 6.63289785e-01 -4.97171432e-01 1.25971401e+00 -2.51087457e-01 5.93768954e-01 -3.38443249e-01 -1.61558583e-01 1.69038147e-01 1.50486469e-01 1.19983494e+00 1.56180394e+00 4.73074615e-01 4.04992849e-01 2.63198763e-01 3.82101446e-01 -3.28237832e-01 3.35530847e-01 -3.14730704e-01 -8.00207257e-02 6.44789100e-01 1.21702468e+00 -1.11323524e+00 -5.18507361e-01 1.97638124e-01 7.05371559e-01 5.39317727e-01 -4.06073667e-02 -7.84469247e-01 -4.28468823e-01 1.74549252e-01 2.96868742e-01 2.34262437e-01 8.85859132e-03 -7.38627985e-02 -1.26510823e+00 1.73709884e-01 -2.56665736e-01 8.06173861e-01 -6.59414053e-01 -9.02491510e-01 6.38364613e-01 1.98588908e-01 -1.18371558e+00 -1.26610875e-01 5.69471121e-01 -1.09817994e+00 3.82797182e-01 -1.17993391e+00 -6.72204018e-01 -2.10359290e-01 -6.13542385e-02 7.24769652e-01 1.31656662e-01 3.20057243e-01 2.22007275e-01 -4.94769335e-01 2.29519054e-01 -1.94384456e-02 -6.36246055e-02 6.43204987e-01 -1.17137182e+00 4.60527897e-01 1.12193739e+00 2.19049796e-01 4.42475468e-01 1.05643332e+00 -1.20699942e+00 -8.52615178e-01 -1.04492116e+00 1.47022450e+00 -2.10785314e-01 5.16489804e-01 2.95323357e-02 -1.01312220e+00 6.33855522e-01 2.93671519e-01 -8.44151616e-01 7.17599750e-01 3.68130207e-01 7.29590058e-02 4.21572812e-02 -9.08940017e-01 6.71771467e-01 8.64088058e-01 -8.93596411e-02 -9.04820621e-01 5.25852144e-01 9.22473967e-01 -5.09741306e-01 -5.27898967e-01 2.41265193e-01 2.01679900e-01 -6.69678450e-01 8.61245930e-01 -5.12801945e-01 4.01496619e-01 -3.76611680e-01 2.24008024e-01 -1.42523372e+00 -5.24372220e-01 -6.87894106e-01 -3.43387246e-01 1.56865931e+00 3.51207018e-01 -2.80106395e-01 3.83959621e-01 4.38785285e-01 -3.47638905e-01 -6.20206535e-01 -7.53175974e-01 -4.80704680e-02 -7.54250705e-01 -2.98202336e-01 4.81014162e-01 9.20586348e-01 4.17375684e-01 5.79326451e-01 -4.56765860e-01 2.92950153e-01 5.06721079e-01 2.18267411e-01 3.86609763e-01 -1.20795512e+00 -9.85015482e-02 -4.91009474e-01 -2.25611050e-02 -9.31882381e-01 -1.64852217e-01 -8.38409781e-01 7.38643855e-02 -1.78547037e+00 5.58886349e-01 -3.06772828e-01 -3.91249865e-01 2.62289077e-01 -6.17879033e-01 -3.61387610e-01 1.39165232e-02 3.28991055e-01 -1.15414691e+00 4.68250066e-01 7.17718840e-01 -6.96556494e-02 -4.84311998e-01 1.85415015e-01 -8.73604596e-01 8.23881984e-01 5.89475214e-01 -7.42985725e-01 -2.39802465e-01 -2.60965675e-01 8.08520734e-01 4.21585083e-01 8.09956118e-02 -8.48470688e-01 8.15778613e-01 -2.03414142e-01 7.12969378e-02 -1.05509567e+00 1.18367217e-01 -2.56218702e-01 3.73812854e-01 1.33472160e-01 -7.83389628e-01 1.23430185e-01 5.50776944e-02 9.46252227e-01 -3.66371065e-01 -5.54280162e-01 3.12865198e-01 -1.85416237e-01 -7.68396080e-01 1.76072523e-01 -4.74954635e-01 3.61304611e-01 9.93349254e-01 -3.78332175e-02 -4.71318573e-01 -4.24943238e-01 -7.33431637e-01 5.39787710e-01 1.78657666e-01 3.47285211e-01 4.91264910e-01 -1.28223813e+00 -9.85493958e-01 -4.31057572e-01 2.31358886e-01 1.05238013e-01 6.54005408e-01 7.90076375e-01 -3.74192208e-01 2.09096119e-01 -4.73836698e-02 -1.45364970e-01 -1.28331077e+00 1.76109716e-01 -2.55077034e-01 -7.55550146e-01 -8.57552707e-01 8.53373110e-01 1.34319559e-01 2.90762901e-01 3.02845329e-01 -1.92564443e-01 -8.67835879e-01 1.01571107e+00 9.81042981e-01 4.31792468e-01 6.08622059e-02 -7.18561411e-01 -1.01934530e-01 1.09435044e-01 -3.54379147e-01 -1.30183473e-01 1.51431966e+00 -4.72701162e-01 -1.26631513e-01 7.38607109e-01 6.39171839e-01 3.70789587e-01 -9.27927732e-01 -4.44208294e-01 3.86914462e-01 -2.86970496e-01 -1.45728048e-02 -5.81461906e-01 -6.00914657e-01 1.98081821e-01 -2.93089747e-01 5.74312806e-01 9.71646309e-01 3.52278143e-01 9.50857937e-01 4.19449091e-01 2.71699369e-01 -1.13387334e+00 1.00181468e-01 5.81248999e-01 1.00565171e+00 -8.21184933e-01 4.02365476e-01 -8.34786892e-02 -1.02376056e+00 1.00983858e+00 2.96495289e-01 2.33520627e-01 4.00513142e-01 -2.56882831e-02 -4.74905908e-01 -5.03845155e-01 -9.10322905e-01 -2.02599093e-01 4.07575548e-01 -1.73249066e-01 2.48807132e-01 1.25087544e-01 -6.26234293e-01 7.71272004e-01 -1.37891442e-01 -3.97126794e-01 7.87251472e-01 9.38284814e-01 -9.61432815e-01 -5.81821322e-01 -3.02770078e-01 5.73557019e-01 -5.16133428e-01 1.02818616e-01 -1.78877383e-01 1.26370400e-01 -9.95129719e-02 6.47157133e-01 1.61094487e-01 -1.67647049e-01 4.67224717e-01 2.03535229e-01 4.36600260e-02 -6.88039184e-01 -8.99509490e-01 -1.03965454e-01 4.90186572e-01 -1.44525215e-01 -3.10499191e-01 -1.06748295e+00 -1.34395766e+00 -1.32139072e-01 -3.16580385e-01 4.52903390e-01 4.10533398e-01 9.23483789e-01 4.25460130e-01 7.98914254e-01 5.06548882e-01 -7.93119848e-01 -7.34534562e-02 -9.61706102e-01 -2.82707930e-01 4.56588030e-01 2.42605507e-01 -5.49805582e-01 -1.36506319e-01 -1.63477734e-02]	[12.56828498840332, 9.517938613891602]
4afdbae4-5a64-49ab-8c7a-0b47a404f499	speech-modeling-with-a-hierarchical	2303.09404	null	https://arxiv.org/abs/2303.09404v2	https://arxiv.org/pdf/2303.09404v2.pdf	Speech Modeling with a Hierarchical Transformer Dynamical VAE	The dynamical variational autoencoders (DVAEs) are a family of latent-variable deep generative models that extends the VAE to model a sequence of observed data and a corresponding sequence of latent vectors. In almost all the DVAEs of the literature, the temporal dependencies within each sequence and across the two sequences are modeled with recurrent neural networks. In this paper, we propose to model speech signals with the Hierarchical Transformer DVAE (HiT-DVAE), which is a DVAE with two levels of latent variable (sequence-wise and frame-wise) and in which the temporal dependencies are implemented with the Transformer architecture. We show that HiT-DVAE outperforms several other DVAEs for speech spectrogram modeling, while enabling a simpler training procedure, revealing its high potential for downstream low-level speech processing tasks such as speech enhancement.	['Xavier Alameda-Pineda', 'Laurent Girin', 'Simon Leglaive', 'Xiaoyu Bie', 'Xiaoyu Lin']	2023-03-07	null	null	null	null	['speech-enhancement']	['speech']	[ 5.99104576e-02 2.04239637e-01 3.53254601e-02 -1.54689690e-02 -3.43927205e-01 -5.41529357e-01 9.54603910e-01 -6.25466645e-01 9.07943100e-02 3.60835522e-01 5.72818577e-01 -5.04166901e-01 1.21657522e-02 -6.98004246e-01 -5.84468007e-01 -1.09268844e+00 3.24823111e-02 9.38593969e-02 -1.02821738e-01 -1.23660736e-01 -4.77690548e-01 2.32093379e-01 -1.56868303e+00 2.18000457e-01 4.03532088e-01 7.20763266e-01 6.40720904e-01 1.00472915e+00 -6.66493699e-02 9.94053185e-01 -5.12347519e-01 -4.37467426e-01 -1.44925296e-01 -8.31476331e-01 -4.68368888e-01 8.01385492e-02 -2.59286880e-01 -4.19749320e-01 -6.53061688e-01 7.81724811e-01 3.11814129e-01 3.97220880e-01 8.30365658e-01 -1.23222744e+00 -1.04335892e+00 9.30816650e-01 -1.53934836e-01 3.97179753e-01 -1.66087896e-01 -6.02479652e-03 1.24821270e+00 -9.59719718e-01 6.33194804e-01 1.41028452e+00 5.57547450e-01 8.25122118e-01 -1.53141749e+00 -2.48415589e-01 2.00608701e-01 4.10305381e-01 -1.01552820e+00 -6.62708819e-01 9.86006320e-01 -7.11049378e-01 1.48068237e+00 1.74836323e-01 6.83733284e-01 1.86561477e+00 4.37239319e-01 8.98234844e-01 6.34105027e-01 -3.25936556e-01 3.13308597e-01 -2.33860090e-01 4.40531224e-02 3.42420638e-01 -5.84126711e-01 4.11202371e-01 -7.11486340e-01 -2.40072116e-01 9.68907475e-01 -2.96256337e-02 -2.13160560e-01 -3.02771062e-01 -9.39154506e-01 1.05735540e+00 -4.28730920e-02 4.34894919e-01 -8.50270689e-01 3.84729654e-01 4.34002787e-01 3.80530208e-01 6.98186100e-01 -1.13973163e-01 -3.15610915e-01 -2.58699924e-01 -1.10093367e+00 5.40978983e-02 5.63904285e-01 7.34291732e-01 3.88661206e-01 1.10227525e+00 -5.12554288e-01 8.20923209e-01 5.65644026e-01 2.58726150e-01 7.68567383e-01 -9.54776049e-01 1.07009560e-01 -1.71080187e-01 -2.02917010e-01 -5.25108695e-01 7.37194195e-02 -5.23472190e-01 -9.00284350e-01 1.06182486e-01 -1.44103974e-01 -1.37371019e-01 -1.08942413e+00 2.22795033e+00 1.40510290e-03 6.57262623e-01 4.21304524e-01 5.18170655e-01 7.63285697e-01 1.27707493e+00 2.47836560e-01 -8.24816585e-01 9.80933070e-01 -9.14132595e-01 -1.39582193e+00 -6.14079870e-02 4.23020236e-02 -5.54680943e-01 7.60892332e-01 2.64741480e-01 -1.44275284e+00 -9.12282288e-01 -8.31960142e-01 -3.41617137e-01 -5.94553761e-02 3.68395261e-02 3.66652697e-01 4.30802405e-01 -1.63925576e+00 6.26727939e-01 -1.33901274e+00 2.14130789e-01 -1.57493085e-01 8.02472457e-02 9.43484232e-02 5.89547932e-01 -1.50563145e+00 4.59669828e-01 2.03846712e-02 1.61512658e-01 -1.56131196e+00 -8.13355565e-01 -1.09626400e+00 4.98222113e-01 -1.38986617e-01 -7.89361238e-01 1.55820489e+00 -8.94438088e-01 -2.07959890e+00 3.44415873e-01 -7.52324581e-01 -6.94359720e-01 2.62733817e-01 -1.89250782e-01 -5.24881840e-01 -1.34474412e-01 -3.33370447e-01 5.04982352e-01 1.51192379e+00 -1.06283545e+00 -1.40065357e-01 1.52932862e-02 -2.86699444e-01 2.20873803e-02 -3.45019341e-01 1.10524043e-01 -1.53998807e-01 -9.39791262e-01 -1.92768231e-01 -8.15954864e-01 -1.38570532e-01 -4.05237645e-01 -1.93242431e-01 -6.13578320e-01 1.08850050e+00 -8.83448660e-01 1.53956747e+00 -2.31724215e+00 1.03142297e+00 -3.40875775e-01 4.07810926e-01 2.84374177e-01 -1.33143663e-01 6.54314876e-01 -4.46756095e-01 -2.23374330e-02 -3.27954531e-01 -1.03347743e+00 1.74981937e-01 6.56216741e-01 -9.63939667e-01 1.53404459e-01 3.08305144e-01 1.14843237e+00 -7.60559738e-01 3.44327092e-03 3.12498659e-01 1.16138113e+00 -5.31821907e-01 4.53237861e-01 -4.23046917e-01 4.40863550e-01 -5.94525412e-02 -6.81786388e-02 2.63381094e-01 -1.87954396e-01 2.17840672e-01 4.94019873e-02 -3.60521525e-01 5.64091265e-01 -7.48204887e-01 1.59171319e+00 -4.58088458e-01 1.15905750e+00 1.32674918e-01 -7.79532313e-01 5.32819450e-01 1.18239534e+00 4.55594748e-01 -3.37036908e-01 2.32617378e-01 -1.36041433e-01 2.44409945e-02 -3.69513869e-01 5.99732995e-01 -3.57077450e-01 1.09031290e-01 3.96640241e-01 5.80505669e-01 1.37990355e-01 4.65800129e-02 3.34353179e-01 8.65237355e-01 2.04383254e-01 1.81720093e-01 -4.98320162e-02 3.19359511e-01 -7.05603123e-01 6.51010871e-01 5.45529485e-01 -2.29343250e-01 3.95879745e-01 5.03330648e-01 -2.01672148e-02 -1.41419220e+00 -1.51517129e+00 -5.71204200e-02 1.03939724e+00 -4.72790539e-01 -5.71867347e-01 -8.43212426e-01 2.24386990e-01 -3.08128446e-01 1.01944709e+00 -6.76320076e-01 -1.57584772e-01 -5.56366563e-01 -4.14633244e-01 4.90190685e-01 7.97192633e-01 -6.08257055e-02 -1.20679069e+00 -4.73546356e-01 5.83048403e-01 -2.95387685e-01 -1.03294885e+00 -3.55546534e-01 3.95602822e-01 -6.41354442e-01 -1.45474613e-01 -9.54260886e-01 -6.92475200e-01 1.01552166e-01 -4.04892527e-02 1.14569879e+00 -5.10059655e-01 8.07057396e-02 4.10397112e-01 -3.93652827e-01 -2.57895380e-01 -1.04507184e+00 -2.83760339e-01 4.35214102e-01 1.29449546e-01 1.89116411e-02 -1.06375599e+00 -3.62552732e-01 -2.15436712e-01 -9.60783482e-01 1.45184994e-01 1.63846523e-01 9.74787414e-01 7.43397593e-01 -1.36632890e-01 2.30589464e-01 -4.95628625e-01 7.65160859e-01 -5.81783414e-01 -5.39635777e-01 2.14093700e-02 -2.66717643e-01 2.00797528e-01 6.50183976e-01 -7.88688362e-01 -1.29418170e+00 -2.94048071e-01 -5.10231674e-01 -1.11453032e+00 6.02058275e-03 5.52234411e-01 -3.55338976e-02 7.31094182e-01 3.03131521e-01 5.63876569e-01 -8.55737552e-02 -5.25435865e-01 6.26218140e-01 4.42054749e-01 6.25482082e-01 -7.54500553e-02 7.76618779e-01 2.07752794e-01 -2.06244677e-01 -1.01696515e+00 -5.30664086e-01 -1.23387858e-01 -6.55768871e-01 -9.71744657e-02 1.35229552e+00 -1.01281857e+00 -4.66280520e-01 5.94011605e-01 -1.45173013e+00 -6.14389956e-01 -5.56274712e-01 4.87613916e-01 -7.56283343e-01 2.21805662e-01 -1.17833388e+00 -1.18420696e+00 -2.24992663e-01 -1.21631861e+00 1.02089322e+00 -2.07626875e-02 -3.02220643e-01 -1.28476739e+00 2.71567076e-01 -2.44434476e-01 5.14292598e-01 -6.32662773e-02 1.02791047e+00 -1.66949719e-01 -4.32429910e-01 3.81528765e-01 6.34173572e-01 5.78582168e-01 1.92287847e-01 4.27861810e-01 -1.25526524e+00 -3.42313707e-01 4.91352618e-01 1.80072680e-01 8.54070365e-01 1.05443084e+00 9.53037620e-01 -2.98503697e-01 -1.40466481e-01 7.44437516e-01 1.02557623e+00 5.54874539e-01 5.65979123e-01 -2.63882130e-01 5.64741492e-01 3.61586630e-01 -2.74200916e-01 4.08925295e-01 1.05801903e-01 5.90371132e-01 2.77760863e-01 -1.27468914e-01 -2.42999986e-01 -3.37224483e-01 8.29782784e-01 1.80466938e+00 -5.18399663e-02 -7.59715378e-01 -5.45438468e-01 7.83525646e-01 -1.74781835e+00 -1.39806747e+00 -1.58837020e-01 1.54677939e+00 6.12786889e-01 -2.25269273e-01 -1.17847146e-02 2.56805241e-01 7.19320953e-01 5.98216116e-01 -6.92926764e-01 -7.22007275e-01 -2.44957477e-01 4.62231576e-01 -1.93294436e-01 6.76107109e-01 -8.51757050e-01 9.47011113e-01 7.32467365e+00 6.97339296e-01 -1.07861245e+00 4.98781800e-01 2.04599515e-01 -2.09309876e-01 -6.52460992e-01 -1.19499035e-01 -7.12163746e-01 3.68297070e-01 1.58807123e+00 -1.22585312e-01 5.40512800e-01 6.74446285e-01 5.32563686e-01 7.57451296e-01 -1.01111555e+00 7.04325974e-01 -2.08738551e-01 -1.38809144e+00 2.18014494e-01 1.99017167e-01 6.59094751e-01 2.95933932e-02 6.70210242e-01 3.91179532e-01 6.06202722e-01 -9.83103454e-01 9.65247750e-01 3.86524916e-01 7.14274526e-01 -5.96516013e-01 8.29835311e-02 4.47695047e-01 -1.33492708e+00 -1.22187577e-01 -3.24265033e-01 -1.32478457e-02 8.24412048e-01 2.49903366e-01 -3.45684469e-01 3.65306139e-01 5.86040378e-01 8.69066894e-01 2.37600505e-01 2.45043397e-01 -4.80384916e-01 1.16499281e+00 1.94860250e-01 2.63385922e-01 3.43609184e-01 -3.20872039e-01 9.93494034e-01 1.14757192e+00 5.08840084e-01 2.52720118e-02 -4.79254395e-01 1.27418303e+00 1.63844794e-01 -3.81258190e-01 -4.50920284e-01 -3.68960261e-01 4.68465030e-01 8.66894841e-01 -2.18459055e-01 -2.87088543e-01 -3.42164397e-01 1.27382541e+00 2.10093543e-01 8.42390537e-01 -1.01899576e+00 9.06878859e-02 1.19763589e+00 -2.82824159e-01 8.75489354e-01 -5.06425679e-01 1.67660072e-01 -1.24352551e+00 -3.09193194e-01 -6.14366353e-01 8.91980454e-02 -1.03894782e+00 -1.17420268e+00 1.10866487e+00 -1.98382456e-02 -1.06199336e+00 -1.06524599e+00 -5.46675444e-01 -6.00789785e-01 1.16140330e+00 -1.24099326e+00 -1.05696571e+00 3.68701041e-01 6.90075755e-01 9.68323767e-01 -1.86844990e-01 1.00584149e+00 7.00519457e-02 -6.76745236e-01 4.69823658e-01 4.01841104e-01 -7.83868283e-02 -1.01487897e-01 -1.19942772e+00 1.00077081e+00 1.25586832e+00 5.92583001e-01 9.10706639e-01 1.14521253e+00 -5.13977408e-01 -1.02634799e+00 -8.84325683e-01 1.03840578e+00 -4.04282838e-01 7.01567829e-01 -6.73868001e-01 -1.17464602e+00 1.08009470e+00 6.58439517e-01 -2.91099072e-01 7.31654108e-01 3.20503376e-02 -2.46467084e-01 4.10006016e-01 -4.31685537e-01 6.10786796e-01 1.08035648e+00 -1.10678816e+00 -7.04563618e-01 -1.21248707e-01 1.38280046e+00 -4.29740191e-01 -7.61974156e-01 1.45025879e-01 3.54957730e-01 -8.70495200e-01 9.92559552e-01 -7.19547391e-01 6.50586605e-01 -1.05386622e-01 -3.42051446e-01 -1.62889719e+00 -7.80995488e-01 -9.76598442e-01 -8.35975826e-01 1.42714417e+00 2.83938408e-01 -3.25575888e-01 2.96338141e-01 2.42288187e-01 -5.45088649e-01 -4.59518760e-01 -1.25137985e+00 -7.57465661e-01 1.86977357e-01 -6.84707940e-01 5.83304107e-01 9.29676592e-01 -3.28299671e-01 3.95110220e-01 -7.99612701e-01 3.65243107e-01 3.26252162e-01 -9.18115601e-02 1.33591428e-01 -1.04828811e+00 -7.74140775e-01 -6.10606432e-01 -1.49419919e-01 -1.33790863e+00 4.60388809e-01 -8.44036281e-01 7.41200820e-02 -1.39076519e+00 -5.17412983e-02 3.11324805e-01 -3.71739984e-01 1.32408351e-01 -9.97685567e-02 -2.72918135e-01 -6.34898990e-02 1.32037371e-01 1.06376261e-01 1.23972607e+00 9.07108665e-01 1.15656532e-01 -3.77472222e-01 4.50990833e-02 -9.41991881e-02 4.72691208e-01 3.37059170e-01 -3.94061238e-01 -8.18106532e-01 -6.30035102e-01 -5.45237362e-02 5.86847186e-01 3.82687032e-01 -5.06815970e-01 9.96350870e-02 5.28949313e-02 1.21865161e-01 -5.90474010e-01 7.35460937e-01 -3.29056054e-01 6.45002544e-01 2.98739016e-01 -5.54687202e-01 3.13368469e-01 6.92740083e-02 6.19590461e-01 -5.17790616e-01 1.47735670e-01 6.20837390e-01 1.43670827e-01 -6.16116643e-01 4.60071206e-01 -1.14700377e+00 -3.82650375e-01 7.07327962e-01 -6.76395744e-02 -2.22477634e-02 -6.35549009e-01 -1.15487814e+00 -3.56284261e-01 -1.27540737e-01 6.09896183e-01 6.06781304e-01 -1.42140102e+00 -6.74032331e-01 4.21973825e-01 -3.07065427e-01 -2.93222576e-01 5.65189600e-01 4.98756856e-01 2.01774463e-01 5.58619261e-01 -3.78520712e-02 -6.95829511e-01 -1.18926227e+00 7.60598183e-01 4.50173318e-01 -2.98413903e-01 -8.74664664e-01 1.33255792e+00 6.29294515e-01 -9.66974869e-02 1.41650230e-01 -3.41818899e-01 -3.14007699e-01 1.71624795e-01 4.15314436e-01 1.70979455e-01 -2.71393478e-01 -1.03426933e+00 3.82106118e-02 1.89778022e-02 1.91877484e-01 -5.66714823e-01 1.61348510e+00 -3.59661996e-01 3.69591415e-02 9.85110343e-01 1.16164446e+00 -1.83618739e-01 -1.70509267e+00 -4.25567448e-01 -2.91310489e-01 1.16633877e-01 4.12939340e-01 -2.17428431e-01 -9.20018494e-01 1.35240912e+00 5.14472485e-01 4.85968739e-01 1.04636610e+00 8.10577199e-02 8.52297187e-01 -4.84149039e-01 4.09677764e-03 -7.54252374e-01 1.14917949e-01 6.84188366e-01 8.93140078e-01 -4.12766606e-01 -6.73075259e-01 -6.31080121e-02 -7.08711505e-01 8.23131561e-01 -3.35990242e-03 -3.02334111e-02 8.44025552e-01 5.14364541e-01 5.05128205e-02 1.35080414e-02 -1.34558821e+00 -2.16942474e-01 4.85021859e-01 6.56134546e-01 6.19533539e-01 1.38279036e-01 -7.70046338e-02 7.81525552e-01 -4.88669991e-01 -3.46159846e-01 3.70238066e-01 5.19243121e-01 -1.13593400e-01 -1.33545053e+00 -4.06606942e-02 5.52716143e-02 -4.43794191e-01 -4.31229740e-01 -1.64185558e-02 4.36881393e-01 -1.37029618e-01 1.03735840e+00 4.62800175e-01 -3.73532772e-01 2.89359968e-02 4.25263345e-01 2.87356883e-01 -4.40042317e-01 -4.88001138e-01 6.07276261e-01 -3.13542694e-01 -3.58272642e-01 -4.14639413e-01 -9.16922092e-01 -1.01838553e+00 -1.20416678e-01 -6.70586452e-02 7.49716014e-02 4.94038075e-01 1.00854635e+00 2.87676811e-01 1.18079698e+00 5.77079833e-01 -7.83043206e-01 -4.91936624e-01 -1.11202037e+00 -6.86087668e-01 2.58353919e-01 9.01258349e-01 -5.97955763e-01 -5.41830420e-01 4.90269333e-01]	[15.080416679382324, 6.312829971313477]
f87eb258-d059-40d9-b39e-c72ca38b73d6	non-rigid-point-cloud-registration-for-middle	2304.13618	null	https://arxiv.org/abs/2304.13618v1	https://arxiv.org/pdf/2304.13618v1.pdf	Non-rigid Point Cloud Registration for Middle Ear Diagnostics with Endoscopic Optical Coherence Tomography	Purpose: Middle ear infection is the most prevalent inflammatory disease, especially among the pediatric population. Current diagnostic methods are subjective and depend on visual cues from an otoscope, which is limited for otologists to identify pathology. To address this shortcoming, endoscopic optical coherence tomography (OCT) provides both morphological and functional in-vivo measurements of the middle ear. However, due to the shadow of prior structures, interpretation of OCT images is challenging and time-consuming. To facilitate fast diagnosis and measurement, improvement in the readability of OCT data is achieved by merging morphological knowledge from ex-vivo middle ear models with OCT volumetric data, so that OCT applications can be further promoted in daily clinical settings. Methods: We propose C2P-Net: a two-staged non-rigid registration pipeline for complete to partial point clouds, which are sampled from ex-vivo and in-vivo OCT models, respectively. To overcome the lack of labeled training data, a fast and effective generation pipeline in Blender3D is designed to simulate middle ear shapes and extract in-vivo noisy and partial point clouds. Results: We evaluate the performance of C2P-Net through experiments on both synthetic and real OCT datasets. The results demonstrate that C2P-Net is generalized to unseen middle ear point clouds and capable of handling realistic noise and incompleteness in synthetic and real OCT data. Conclusion: In this work, we aim to enable diagnosis of middle ear structures with the assistance of OCT images. We propose C2P-Net: a two-staged non-rigid registration pipeline for point clouds to support the interpretation of in-vivo noisy and partial OCT images for the first time. Code is available at: https://gitlab.com/nct\_tso\_public/c2p-net.	['Stefanie Speidel', 'Marcus Neudert', 'Edmund Koch', 'Zhaoyu Chen', 'Yujia Hu', 'Chenpan Li', 'Sebastian Bodenstedt', 'Joseph Morgenstern', 'Jonas Golde', 'Peng Liu']	2023-04-26	null	null	null	null	['point-cloud-registration']	['computer-vision']	[-2.91088581e-01 -2.25779742e-01 3.42744797e-01 -4.67600627e-03 -9.15633678e-01 -5.44052780e-01 -3.21742445e-01 1.36176303e-01 -3.00240695e-01 3.72219592e-01 5.00957556e-02 -1.25194564e-01 -3.11814286e-02 -5.31041265e-01 -4.70351934e-01 -4.94322002e-01 5.38944919e-03 9.79884267e-01 3.74745339e-01 1.30267441e-01 -1.37394726e-01 6.05550528e-01 -1.66128314e+00 1.22553267e-01 1.06895661e+00 8.20164084e-01 2.88556397e-01 4.83053118e-01 1.13887992e-02 -4.11840349e-01 -8.76946896e-02 -1.87068522e-01 3.13594311e-01 1.80886224e-01 -6.32808745e-01 -1.14985285e-02 5.43099225e-01 -4.28005040e-01 1.67750686e-01 1.07947922e+00 1.15135205e+00 -3.60948235e-01 3.29513967e-01 -7.28779674e-01 -1.63109094e-01 -9.70596541e-03 -4.47150230e-01 1.84082091e-01 4.83383268e-01 5.95523179e-01 3.76553863e-01 -1.02413821e+00 7.29969084e-01 7.68428624e-01 7.15155721e-01 5.11200607e-01 -1.49222910e+00 -8.46509337e-01 -1.98037535e-01 -1.88223377e-01 -1.26915205e+00 -1.05732672e-01 3.14856112e-01 -7.03161418e-01 7.50284135e-01 3.71243685e-01 1.56210828e+00 6.49310052e-01 8.45179856e-02 5.55031776e-01 1.42167103e+00 -5.67567311e-02 7.26715475e-02 -2.99700588e-01 -3.95466499e-02 5.71881473e-01 5.20754874e-01 4.86404866e-01 -3.52057904e-01 -5.07391095e-01 9.72700596e-01 -1.78991303e-01 -8.24663103e-01 -2.96829611e-01 -1.23221278e+00 2.09364802e-01 4.25126851e-01 1.56945288e-01 -6.76360071e-01 -6.73074052e-02 5.04879467e-02 4.48911414e-02 6.32669806e-01 4.31761950e-01 -3.09263468e-01 -3.07668686e-01 -9.09718573e-01 8.08790997e-02 4.89296347e-01 6.77857697e-01 3.47050786e-01 -2.68750638e-01 3.12798917e-01 8.73436451e-01 5.86323678e-01 6.68940842e-01 7.51462698e-01 -6.93492711e-01 -1.23010222e-02 5.36796212e-01 -1.14582852e-01 -2.71921545e-01 -4.60563660e-01 -6.32415354e-01 -4.85618025e-01 3.83050501e-01 1.66374415e-01 6.92241043e-02 -1.45120108e+00 1.25051188e+00 8.03145885e-01 7.22587109e-01 -5.46612859e-01 1.25394022e+00 1.10637820e+00 -2.05251575e-01 -1.01790883e-01 -1.68370903e-01 1.54604948e+00 -3.64444196e-01 -3.55699420e-01 -1.27625316e-01 6.30926728e-01 -1.31497955e+00 1.03255200e+00 5.00997186e-01 -1.35291135e+00 -1.07885569e-01 -5.51455259e-01 9.36534479e-02 1.28549561e-01 1.20195366e-01 3.27347934e-01 2.82290906e-01 -1.19301796e+00 3.44368577e-01 -1.44665790e+00 -2.83091724e-01 5.23665547e-01 7.81857669e-01 -6.26094520e-01 -2.47305334e-01 -4.74266469e-01 7.86214352e-01 8.57784897e-02 3.85099173e-01 -1.76807716e-01 -1.12595046e+00 -6.07418835e-01 -4.46377426e-01 -1.40362412e-01 -1.33099484e+00 1.25099099e+00 -1.92647621e-01 -1.28341293e+00 1.20149350e+00 -3.02153975e-01 -6.85209930e-02 5.60867071e-01 -2.41823480e-01 -2.12210655e-01 3.27932358e-01 1.36435598e-01 6.37783229e-01 7.45960593e-01 -1.27991748e+00 -2.50320137e-01 -8.30017447e-01 -5.76431632e-01 -2.19646026e-03 3.83830458e-01 7.78084341e-03 -6.02217317e-01 -4.53936964e-01 9.74974036e-01 -1.38793409e+00 -3.63376617e-01 3.77498955e-01 -4.51807201e-01 3.16128314e-01 5.95153213e-01 -9.13681269e-01 9.91006076e-01 -2.14475489e+00 -4.49473590e-01 3.26507777e-01 6.84806049e-01 5.68867385e-01 -3.83093506e-02 -2.73896128e-01 -4.38869894e-01 9.20362175e-02 -3.55354249e-02 -4.39380974e-01 -3.48182917e-01 -9.54356790e-03 3.94717138e-03 5.77254295e-01 -2.18575969e-01 9.34387386e-01 -8.23771358e-01 -5.57305753e-01 3.79056156e-01 8.37634385e-01 -7.34169483e-01 5.33360802e-02 -1.46813512e-01 1.23623145e+00 -5.09873807e-01 1.10459173e+00 1.01941371e+00 -3.47736180e-01 -8.98145288e-02 -3.79468590e-01 -2.09219396e-01 4.73541558e-01 -1.29893041e+00 1.79621124e+00 -5.14044166e-01 1.67136908e-01 3.10986876e-01 -8.35067183e-02 3.75392824e-01 7.95433044e-01 7.15553522e-01 -4.46864367e-01 4.22180682e-01 9.93247330e-01 3.69432271e-01 -6.75470412e-01 3.05520948e-02 -2.99610913e-01 6.27617657e-01 4.17108715e-01 -2.94282168e-01 -7.13459373e-01 -1.71891928e-01 -3.08700383e-01 6.58660173e-01 1.04745142e-01 1.21874809e-01 2.07793355e-01 1.23261876e-01 -6.75876765e-03 5.72235644e-01 1.58845589e-01 -1.51795700e-01 1.12215734e+00 -8.28270316e-02 -2.91524321e-01 -8.54013026e-01 -1.32784295e+00 -8.10571253e-01 -1.60400048e-01 -1.06214741e-02 -1.82913870e-01 -5.72512984e-01 -8.17421451e-02 1.38971418e-01 1.38582036e-01 -3.18773925e-01 2.58287191e-01 -4.78732973e-01 -7.69782186e-01 1.75655276e-01 3.43584985e-01 1.02826163e-01 -6.37263894e-01 -3.95587891e-01 5.08618534e-01 -3.54619414e-01 -1.34462953e+00 -3.76664370e-01 -3.83530498e-01 -1.38874400e+00 -1.16620433e+00 -8.20412815e-01 -7.87397981e-01 8.92574131e-01 6.30283579e-02 8.25161040e-01 2.07490221e-01 -5.80623209e-01 4.70995903e-01 -5.11909872e-02 -6.95167363e-01 -1.93712488e-01 -2.30084613e-01 1.77993894e-01 -1.66287422e-01 3.10431510e-01 -1.14635503e+00 -1.22414494e+00 4.55910802e-01 -7.71974504e-01 -7.22987577e-02 5.69927275e-01 6.78043127e-01 1.27065706e+00 -5.28903782e-01 -2.01010108e-01 -3.67731661e-01 4.86591429e-01 -5.21410480e-02 -8.12866211e-01 -1.14785209e-02 -3.83643329e-01 -2.05046549e-01 -7.40081519e-02 -5.13983548e-01 -5.72629213e-01 -2.04517087e-03 -4.32478666e-01 -6.65053546e-01 -1.62127823e-01 5.59145987e-01 3.40473652e-01 -4.50788289e-01 5.17208099e-01 9.64451954e-02 3.77563179e-01 -6.29124463e-01 -1.09892800e-01 6.55228436e-01 3.69550049e-01 -5.54267704e-01 5.89373350e-01 9.68330026e-01 1.01296045e-01 -6.62904501e-01 -4.58987683e-01 -7.74898350e-01 -6.00549042e-01 -7.07237870e-02 6.76044464e-01 -8.16605270e-01 -7.83661723e-01 6.91886783e-01 -1.03338802e+00 -5.79042658e-02 -2.43182555e-01 1.28305018e+00 -4.38012779e-01 4.00924444e-01 -6.77786708e-01 -2.73832500e-01 -7.80976832e-01 -1.76084006e+00 1.34495389e+00 7.73138460e-03 -1.66131780e-01 -8.05911779e-01 4.31437373e-01 5.23633361e-01 1.76019579e-01 2.18959317e-01 5.81704617e-01 -3.20322871e-01 -9.20155406e-01 -2.45040134e-01 -4.04219888e-02 3.35344255e-01 1.37048945e-01 1.93717733e-01 -1.10101151e+00 -3.31779599e-01 1.37229143e-02 -4.24560681e-02 5.07541299e-01 9.36377466e-01 9.93490636e-01 2.05942437e-01 -3.91656131e-01 1.11330473e+00 1.44014156e+00 -4.44719158e-02 6.62573218e-01 1.68909967e-01 5.28230429e-01 5.65670252e-01 6.91573083e-01 2.66960114e-01 3.05833727e-01 7.65901625e-01 6.11725748e-01 -2.42955461e-01 -3.70316386e-01 -1.66071057e-01 -3.96236032e-01 1.09250438e+00 -4.66524005e-01 4.57690358e-01 -1.19779551e+00 7.43570924e-01 -1.27357948e+00 -2.75570631e-01 -2.80933678e-01 2.45429969e+00 8.70984972e-01 -1.51303649e-01 -1.12193078e-01 -8.52556452e-02 6.39531851e-01 -5.59301555e-01 -3.55114698e-01 1.81933194e-01 1.59961417e-01 9.56720948e-01 2.28227943e-01 4.25009847e-01 -6.96968913e-01 6.34512305e-01 5.22217798e+00 4.57201838e-01 -1.86980319e+00 1.98305607e-01 -6.57963455e-02 -3.39869112e-01 -3.21232617e-01 1.06650122e-01 -5.85483909e-01 4.56332207e-01 4.47135478e-01 6.63276762e-02 -2.06765421e-02 3.37655604e-01 4.90560979e-01 -2.03057438e-01 -8.08254719e-01 1.11037433e+00 -4.98165965e-01 -1.20199764e+00 -6.37760609e-02 4.94975656e-01 5.45093179e-01 7.28872538e-01 2.63203800e-01 -3.29465657e-01 -3.10693830e-02 -8.52730274e-01 6.57687411e-02 5.17022729e-01 1.19742227e+00 -9.37568024e-02 6.44852638e-01 -1.88619215e-02 -1.22364736e+00 3.47793341e-01 -2.31712647e-02 6.45405829e-01 4.08753067e-01 9.66080368e-01 -1.45080996e+00 4.29859281e-01 7.97675312e-01 4.92765933e-01 -2.10779279e-01 1.95919335e+00 -2.88184732e-01 4.96224791e-01 -7.15418458e-01 5.61472118e-01 -1.73628226e-01 -2.97928512e-01 1.05647540e+00 5.46731353e-01 7.86605775e-01 3.23313296e-01 -1.05207379e-03 9.21443582e-01 3.15707445e-01 2.62178600e-01 -3.02757770e-01 2.02183038e-01 4.77086365e-01 1.24274433e+00 -5.17134368e-01 3.23725305e-03 -3.26456815e-01 3.77785802e-01 -2.71212250e-01 3.11195701e-01 -4.50343966e-01 2.09083572e-01 8.14114928e-01 9.43794310e-01 -3.81681211e-02 -2.06541732e-01 -2.88275272e-01 -1.39122736e+00 2.94155926e-01 -7.61204362e-01 1.76816955e-01 -1.27114511e+00 -1.03281796e+00 7.16259658e-01 -3.21390271e-01 -1.83001482e+00 -8.69771987e-02 -5.68717897e-01 -4.80222791e-01 1.10924625e+00 -1.78333080e+00 -1.51209652e+00 -5.99156737e-01 5.22777796e-01 -4.52729836e-02 4.39009756e-01 8.84629846e-01 4.45212245e-01 -2.42655873e-01 3.58605683e-01 -1.36976287e-01 5.14865071e-02 8.75205159e-01 -1.16761911e+00 3.02208871e-01 4.32836354e-01 -2.41146311e-01 9.84502852e-01 5.45563877e-01 -9.07544851e-01 -8.84316802e-01 -7.83319652e-01 5.54264963e-01 -3.12567592e-01 6.58645630e-01 2.55204499e-01 -9.67173874e-01 7.46654510e-01 -4.98885125e-01 5.14802575e-01 9.40108418e-01 -2.44410828e-01 -5.10050021e-02 1.53384909e-01 -1.32713544e+00 4.24008936e-01 7.58140981e-01 -5.15514314e-01 -5.88516593e-01 2.46099100e-01 5.74917078e-01 -1.19620883e+00 -1.27903187e+00 7.22599685e-01 7.59257138e-01 -8.25206339e-01 1.00254285e+00 -1.41240969e-01 -8.19747522e-02 -3.97095472e-01 2.52844155e-01 -1.36903560e+00 3.68454486e-01 -6.45916164e-01 2.81492144e-01 4.95941341e-01 2.23525196e-01 -1.28443110e+00 9.22527969e-01 5.44276834e-01 -5.51706374e-01 -7.64695704e-01 -1.21199477e+00 -4.78615373e-01 -1.03019074e-01 -7.87500322e-01 5.42487025e-01 7.43477643e-01 -2.73231626e-01 -4.28750128e-01 6.65822625e-01 6.77987635e-01 7.74621904e-01 1.66775793e-01 6.95896924e-01 -1.61637115e+00 -3.15902323e-01 -4.16091233e-02 -7.93196976e-01 -8.59879673e-01 -1.73192695e-01 -9.04571712e-01 -3.07592213e-01 -1.57877481e+00 -1.24214604e-01 -7.97797143e-01 4.07849140e-02 2.58720100e-01 2.88531724e-02 5.80616653e-01 -2.43413553e-01 5.38897514e-01 3.47638011e-01 1.55227333e-01 2.26609302e+00 2.53857911e-01 -4.14423317e-01 5.14893174e-01 -1.95006043e-01 9.47066605e-01 4.65871572e-01 -4.26898211e-01 -3.18504721e-01 -4.66793150e-01 1.93367109e-01 1.90958172e-01 8.82932246e-01 -9.77483332e-01 2.39964321e-01 2.99180150e-01 -4.35066111e-02 -9.46689188e-01 6.71586335e-01 -8.22744429e-01 3.45613152e-01 6.06592357e-01 6.33767307e-01 -1.43764600e-01 3.92749369e-01 1.11455910e-01 -5.12983263e-01 1.11777976e-01 8.61543059e-01 -2.73257345e-01 -2.13020109e-02 8.28361869e-01 1.35315299e-01 8.86536092e-02 6.31759405e-01 -6.68828487e-01 -2.59905189e-01 -1.71995267e-01 -1.48592639e+00 1.55266941e-01 7.05203593e-01 -2.29110360e-01 1.05829656e+00 -8.77916694e-01 -8.04487407e-01 4.71029252e-01 2.21816897e-01 8.21174383e-01 6.78314865e-01 1.71424651e+00 -9.08831537e-01 3.65092069e-01 3.40408571e-02 -1.17235827e+00 -1.51330090e+00 -4.10326496e-02 8.44901621e-01 -2.23078877e-01 -6.75981343e-01 8.62692297e-01 1.41858086e-01 -6.12416208e-01 -2.04509720e-01 -9.08199728e-01 1.25395447e-01 -2.16758370e-01 2.15623602e-01 9.45946351e-02 6.89859331e-01 -5.61379790e-01 -1.97613865e-01 1.17457831e+00 -1.85869008e-01 -1.07891455e-01 1.36868286e+00 -4.39720266e-02 -3.23712021e-01 -1.48587987e-01 9.59946334e-01 3.00995141e-01 -7.28770077e-01 -2.67042637e-01 -5.31358659e-01 -5.87835014e-01 3.14887047e-01 -8.17169666e-01 -1.15620208e+00 9.95185196e-01 1.01279163e+00 -4.17835802e-01 1.20890093e+00 5.39059117e-02 1.30736828e+00 -3.64660084e-01 6.54576123e-01 -5.82692206e-01 -2.34640658e-01 1.29312715e-02 8.63230526e-01 -9.21619773e-01 3.27143930e-02 -1.00294185e+00 -9.09371600e-02 9.01516140e-01 4.06874269e-01 6.19031489e-02 1.04312623e+00 4.30622429e-01 5.45355558e-01 -5.33708930e-01 -3.83434296e-01 -4.25429642e-01 5.78224361e-01 6.71789765e-01 3.82619441e-01 3.98024172e-02 -3.27108890e-01 1.45203650e-01 -5.52892327e-01 3.91990036e-01 4.05683517e-01 1.01604176e+00 -1.13735363e-01 -1.36953580e+00 -6.52292848e-01 4.23962772e-01 -6.00328505e-01 -3.82835388e-01 1.08964965e-01 7.83630013e-01 3.25723976e-01 4.40926164e-01 6.10832870e-02 -1.39889315e-01 4.57051694e-01 -3.97310257e-01 6.95865691e-01 -1.04883730e+00 -6.40824199e-01 7.51086712e-01 -7.80888349e-02 -6.03718817e-01 -4.23731148e-01 -7.04925716e-01 -1.38136303e+00 -7.43221666e-04 -5.88172019e-01 -1.51937798e-01 1.10694706e+00 5.15752435e-01 5.07277131e-01 2.77861178e-01 3.28757852e-01 -7.54097164e-01 -3.48201752e-01 -8.10070038e-01 -6.59071386e-01 1.69366449e-01 4.37062800e-01 -7.68537045e-01 -6.14879966e-01 -1.97440341e-01]	[13.881196022033691, -2.9506514072418213]
722a7e8c-14f0-4af0-8ecd-513e1e1c2c51	information-gain-sampling-for-active-learning	2208.00974	null	https://arxiv.org/abs/2208.00974v1	https://arxiv.org/pdf/2208.00974v1.pdf	Information Gain Sampling for Active Learning in Medical Image Classification	Large, annotated datasets are not widely available in medical image analysis due to the prohibitive time, costs, and challenges associated with labelling large datasets. Unlabelled datasets are easier to obtain, and in many contexts, it would be feasible for an expert to provide labels for a small subset of images. This work presents an information-theoretic active learning framework that guides the optimal selection of images from the unlabelled pool to be labeled based on maximizing the expected information gain (EIG) on an evaluation dataset. Experiments are performed on two different medical image classification datasets: multi-class diabetic retinopathy disease scale classification and multi-class skin lesion classification. Results indicate that by adapting EIG to account for class-imbalances, our proposed Adapted Expected Information Gain (AEIG) outperforms several popular baselines including the diversity based CoreSet and uncertainty based maximum entropy sampling. Specifically, AEIG achieves ~95% of overall performance with only 19% of the training data, while other active learning approaches require around 25%. We show that, by careful design choices, our model can be integrated into existing deep learning classifiers.	['Tal Arbel', 'Brennan Nichyporuk', 'Changjian Shui', 'Raghav Mehta']	2022-08-01	null	null	null	null	['skin-lesion-classification']	['medical']	[ 8.32314014e-01 6.50751352e-01 -7.44177520e-01 -8.29147756e-01 -1.26222682e+00 -2.31615067e-01 2.27518708e-01 6.77306771e-01 -8.56802940e-01 9.53901410e-01 -2.01136805e-02 -3.12518589e-02 -4.25619841e-01 -5.65226495e-01 -3.54972929e-01 -1.05167210e+00 1.30864695e-01 7.41001606e-01 3.37822014e-03 6.69053912e-01 1.73176438e-01 2.53044277e-01 -1.49638760e+00 3.21972668e-01 1.15255630e+00 1.28847277e+00 7.48956576e-02 3.49180371e-01 6.26174137e-02 9.92246926e-01 -5.14398217e-01 -3.57346982e-01 2.26931036e-01 -4.14616227e-01 -1.00923419e+00 4.90132630e-01 3.55533361e-01 -4.05212820e-01 2.84306705e-01 8.65500808e-01 8.60427022e-01 1.46700904e-01 9.79301572e-01 -1.09572041e+00 -2.97500521e-01 6.19702578e-01 -5.20025015e-01 2.39899293e-01 -2.07999632e-01 1.44694388e-01 1.06386220e+00 -4.41849023e-01 6.80385232e-01 8.23931873e-01 4.34092343e-01 5.26594937e-01 -1.30414855e+00 -4.97118205e-01 1.27111197e-01 2.51548439e-01 -1.29827297e+00 -6.12534583e-01 4.90148783e-01 -3.59595001e-01 6.58533394e-01 3.80801141e-01 5.51649332e-01 7.94247150e-01 6.75709322e-02 1.10458899e+00 1.09025419e+00 -8.16392183e-01 7.03066051e-01 3.20499897e-01 2.16199175e-01 7.00516164e-01 4.32680577e-01 6.80451021e-02 -3.63627136e-01 -5.12528837e-01 3.49356622e-01 -1.40447587e-01 -2.07332850e-01 -6.07367873e-01 -9.41308677e-01 9.91383076e-01 4.08443838e-01 -2.19122067e-01 -4.11856562e-01 -1.44483685e-01 4.41864371e-01 9.39741544e-03 7.41107583e-01 6.21710539e-01 -5.65328777e-01 2.85351574e-02 -9.07799542e-01 -2.31730156e-02 6.52851105e-01 7.09608614e-01 6.13116026e-01 -5.66280186e-01 -3.24204326e-01 9.62976754e-01 3.73317450e-01 4.69122529e-02 3.01221818e-01 -1.13536036e+00 5.51023288e-03 8.92348230e-01 -6.14071786e-02 -5.33478379e-01 -4.50352728e-01 -5.58224857e-01 -7.43132710e-01 3.92530024e-01 3.01548153e-01 -2.58014619e-01 -1.17591405e+00 1.35421395e+00 2.33024314e-01 -2.80825973e-01 -2.43626058e-01 6.23811245e-01 8.80671680e-01 5.75517118e-02 3.47635567e-01 -5.77690601e-01 1.01536524e+00 -6.80779755e-01 -6.69557631e-01 -4.13255394e-01 6.60999358e-01 -4.06068951e-01 5.87231159e-01 4.89455968e-01 -8.21225107e-01 -1.13071010e-01 -9.38090801e-01 1.46175086e-01 -2.03598328e-02 3.20026457e-01 6.47945583e-01 7.52920687e-01 -8.05191875e-01 3.88817310e-01 -9.48572040e-01 -9.95040834e-02 1.24706209e+00 5.13351858e-01 -3.04200977e-01 -1.49240345e-01 -8.25483680e-01 8.85016859e-01 6.49069607e-01 -3.80188674e-02 -5.72492957e-01 -7.17211902e-01 -8.06249261e-01 -8.14298317e-02 4.46666688e-01 -4.46313947e-01 1.29145813e+00 -1.18243980e+00 -1.10239398e+00 1.14045715e+00 1.12616517e-01 -6.04827881e-01 6.54758275e-01 1.17771082e-01 1.43187672e-01 2.86924958e-01 -6.47740141e-02 1.19819891e+00 5.87115645e-01 -1.15773249e+00 -6.33681357e-01 -3.48813564e-01 -4.92137745e-02 4.43606764e-01 -3.50532323e-01 -1.06843777e-01 -2.00152487e-01 -3.62106174e-01 -5.62913306e-02 -1.12508810e+00 -6.67703688e-01 4.31625634e-01 -3.79373103e-01 -1.39025033e-01 3.64095658e-01 -3.59527230e-01 1.05980587e+00 -2.04453754e+00 -1.70534343e-01 1.77153796e-01 3.46766949e-01 3.74103040e-01 1.57470733e-01 -1.29636884e-01 3.64473835e-02 1.76927328e-01 -4.69817072e-01 -1.23659894e-01 -1.68047547e-01 2.80132920e-01 2.25993410e-01 3.87199402e-01 3.69816303e-01 6.90061688e-01 -8.78832340e-01 -9.44749057e-01 3.29769820e-01 3.31168830e-01 -6.37182891e-01 -1.53370416e-02 -1.78474545e-01 4.92635697e-01 -2.50007570e-01 7.03419983e-01 4.71173227e-01 -7.98978209e-01 4.02962387e-01 -1.33444235e-01 4.61748421e-01 2.19866350e-01 -9.64829683e-01 1.42915487e+00 -3.10096681e-01 6.75149024e-01 -3.08963001e-01 -1.24404323e+00 6.64991498e-01 3.56713444e-01 7.47938275e-01 -5.55080116e-01 1.70791179e-01 1.44585103e-01 2.64827549e-01 -4.42904651e-01 3.38097624e-02 5.22588454e-02 4.42284383e-02 4.39528644e-01 1.79270938e-01 2.54873127e-01 2.85039127e-01 9.57849175e-02 1.18931699e+00 -2.18058541e-01 8.03589582e-01 -1.29999757e-01 1.25232667e-01 1.39890565e-02 8.40589225e-01 9.07954812e-01 -6.64717674e-01 6.47778988e-01 3.91853899e-01 -4.95338470e-01 -7.96657562e-01 -7.15216994e-01 -6.26248181e-01 8.44519019e-01 -1.16755053e-01 3.79106365e-02 -7.46426105e-01 -1.16184247e+00 -2.36108243e-01 6.09135151e-01 -6.53519928e-01 -1.17884889e-01 -2.83604115e-01 -1.38762784e+00 2.66718626e-01 4.88924950e-01 4.33873415e-01 -1.06045270e+00 -9.58321333e-01 4.13411632e-02 -1.80170625e-01 -7.57194579e-01 -6.25405312e-02 5.85974097e-01 -9.25387859e-01 -1.14837968e+00 -6.11428678e-01 -5.64159513e-01 1.03272510e+00 -3.56509537e-01 1.28551388e+00 -3.80128343e-03 -6.79333091e-01 1.50154069e-01 -5.20927310e-01 -7.69147813e-01 -3.70710403e-01 2.80361325e-01 -4.57849085e-01 -7.65468776e-02 6.14593208e-01 -4.88980673e-02 -8.45651686e-01 2.25621656e-01 -7.59847343e-01 -1.18951802e-03 7.36353934e-01 1.06299365e+00 9.39346790e-01 1.91475764e-01 6.96102321e-01 -1.31833410e+00 1.22323871e-01 -3.13858449e-01 -4.45314556e-01 4.49285895e-01 -9.80208516e-01 1.44144539e-02 1.10465065e-01 -4.41074818e-01 -1.13008940e+00 4.75799620e-01 3.72550599e-02 7.26488084e-02 -2.55719453e-01 3.90069038e-01 -4.58148234e-02 -8.23528022e-02 1.01896322e+00 -3.70453268e-01 7.59928003e-02 -1.27621666e-01 1.27587944e-01 1.07279682e+00 -1.09520545e-02 -2.04958662e-01 -3.10789756e-02 4.45718586e-01 -2.42799938e-01 -3.29989821e-01 -1.25546587e+00 -4.72623169e-01 -7.66535521e-01 -3.18699569e-01 5.96197188e-01 -7.29336321e-01 -3.24662149e-01 3.01370710e-01 -6.49031460e-01 -1.94217831e-01 -5.97314298e-01 7.68478513e-01 -5.66147745e-01 1.60261273e-01 -1.74724400e-01 -8.41501534e-01 -5.43457747e-01 -1.42414522e+00 1.16109264e+00 3.07603836e-01 -5.64824581e-01 -9.98795450e-01 -1.07616372e-01 7.94774950e-01 1.55436426e-01 3.25024277e-01 1.07258117e+00 -1.05688274e+00 -5.37855804e-01 -3.98307800e-01 -1.15851864e-01 5.11608422e-01 3.34840268e-01 -1.21276595e-01 -1.08522880e+00 -3.32446992e-01 -3.21655542e-01 -8.17089856e-01 1.06807482e+00 8.81213546e-01 1.43045318e+00 -2.18933657e-01 -4.29481983e-01 3.52115899e-01 1.31134903e+00 5.75841129e-01 5.50964415e-01 2.41570279e-01 1.77944183e-01 4.96992320e-01 7.25652218e-01 5.49542844e-01 1.03567816e-01 3.68851602e-01 3.95919740e-01 -2.98308760e-01 1.28643564e-03 3.85858834e-01 -2.17671141e-01 3.78032953e-01 1.52833849e-01 -4.16434556e-01 -9.87693489e-01 5.65572262e-01 -1.72824895e+00 -6.70058370e-01 3.26576799e-01 2.51117992e+00 1.23812866e+00 2.68269241e-01 -3.94482650e-02 3.51179063e-01 7.25568414e-01 -1.26963049e-01 -1.01743519e+00 -4.64362726e-02 1.23231076e-01 2.22764403e-01 7.47251987e-01 2.21717805e-01 -1.48351490e+00 1.25512883e-01 6.69300270e+00 8.73246372e-01 -9.46891904e-01 8.31383616e-02 1.27929771e+00 -3.60313356e-01 1.88804716e-02 -6.15781136e-02 -8.31753969e-01 4.68992174e-01 8.30463886e-01 -3.96516779e-03 -8.38435367e-02 7.50852406e-01 -7.70496875e-02 -4.51430827e-01 -1.21124101e+00 9.21639860e-01 4.44254056e-02 -1.27204490e+00 -1.71754941e-01 1.71719521e-01 8.31821084e-01 1.68488070e-01 -8.72431472e-02 -7.31194988e-02 4.88179028e-01 -1.03757703e+00 3.80483031e-01 3.93190861e-01 8.93651247e-01 -7.46830165e-01 9.44463849e-01 5.15562713e-01 -3.86261046e-01 -2.71839082e-01 -2.96074480e-01 2.99357444e-01 -2.13841517e-02 9.75793064e-01 -1.09693336e+00 3.40629786e-01 5.04281700e-01 3.56690496e-01 -6.31518781e-01 1.46259546e+00 1.26908869e-01 7.45169640e-01 -1.84152007e-01 7.76781840e-03 1.10207982e-02 1.34175807e-01 1.42818451e-01 8.79405797e-01 -3.86501476e-02 -3.05619347e-03 3.05944026e-01 4.52263653e-01 -2.28607520e-01 1.62983671e-01 -2.20911011e-01 -1.72862381e-01 5.53312421e-01 1.21537113e+00 -1.08922291e+00 -2.17472985e-01 -1.58442959e-01 5.48187375e-01 2.62450159e-01 1.17243119e-02 -5.86449564e-01 -3.86735976e-01 4.29792888e-02 -1.62032217e-01 5.12959994e-02 6.04877353e-01 -4.22289789e-01 -7.70633996e-01 -1.67613119e-01 -7.95753598e-01 8.14580858e-01 -5.31430602e-01 -1.33936107e+00 4.55341727e-01 1.42345741e-01 -1.30490053e+00 -3.03176314e-01 -4.97922421e-01 2.93300692e-02 6.23135746e-01 -1.32662523e+00 -7.21444845e-01 -2.78044969e-01 -5.94082400e-02 4.42768574e-01 -2.70664662e-01 1.04135072e+00 4.51462448e-01 -5.74165404e-01 7.44317889e-01 1.83079213e-01 2.50247926e-01 7.16267765e-01 -1.22909510e+00 -1.12229839e-01 3.87087017e-01 3.09072882e-02 1.93613514e-01 3.19708943e-01 -4.25752193e-01 -6.33294821e-01 -1.13567829e+00 7.52583146e-01 -2.90468216e-01 -1.20679446e-01 -2.85834018e-02 -7.35010505e-01 7.11985230e-01 8.13676119e-02 3.98325622e-01 1.20321584e+00 2.77697165e-02 9.42551997e-03 -1.94423035e-01 -1.57329440e+00 1.58492640e-01 8.38797390e-01 -2.29674414e-01 -2.20165253e-01 6.17170453e-01 3.09164286e-01 -4.90746230e-01 -9.25037563e-01 8.31489265e-01 4.75982189e-01 -7.60988951e-01 7.26038218e-01 -5.12941897e-01 3.37699741e-01 1.03546366e-01 -2.60864999e-02 -1.21772993e+00 -4.10186857e-01 -2.30199203e-01 4.29396369e-02 9.99275267e-01 7.02460766e-01 -5.43026328e-01 9.37506676e-01 8.80585492e-01 2.12835237e-01 -1.15040863e+00 -9.30513978e-01 -3.78073782e-01 -1.10893004e-01 -1.96831614e-01 2.14340702e-01 9.02676821e-01 -1.59853324e-01 2.55714774e-01 -3.33601348e-02 -1.03084862e-01 8.70214283e-01 -1.61375776e-02 1.36131674e-01 -1.47569895e+00 -2.14903593e-01 -1.20518684e-01 -6.05731487e-01 -4.40182149e-01 2.49209236e-02 -9.19663727e-01 2.24944890e-01 -1.66219044e+00 6.73313022e-01 -9.10735488e-01 -5.62578797e-01 7.51048326e-01 -3.14740121e-01 4.23532993e-01 -2.31432244e-01 1.37316361e-01 -7.54112840e-01 2.05958515e-01 9.89267945e-01 -3.60404611e-01 -9.61427018e-02 1.89396992e-01 -8.90443683e-01 8.46959174e-01 6.97588265e-01 -6.24584019e-01 -7.37147510e-01 -1.60646334e-01 3.06706160e-01 1.71862952e-02 9.42147225e-02 -7.21234500e-01 7.13858381e-02 -1.87133402e-01 6.46298170e-01 -5.10630250e-01 1.24531902e-01 -7.27686465e-01 9.03005153e-02 3.46363842e-01 -1.02284014e+00 -6.65708661e-01 -1.01338085e-02 5.83640337e-01 -1.06518179e-01 -5.43759584e-01 1.25154865e+00 -2.82803565e-01 -5.77918231e-01 3.56832087e-01 -2.33450770e-01 2.99543530e-01 1.20842373e+00 -2.22312093e-01 -3.77463818e-01 -1.06753439e-01 -7.91615725e-01 6.49182349e-02 3.26748788e-01 2.41617654e-02 3.60176563e-01 -1.07481635e+00 -6.98171318e-01 1.27093103e-02 3.82332951e-01 3.94840807e-01 2.50636965e-01 8.86411369e-01 -5.13253331e-01 3.08014125e-01 -7.05070868e-02 -8.21241558e-01 -1.44783664e+00 1.57747194e-01 4.19052631e-01 -4.46681559e-01 -5.03202558e-01 1.05026281e+00 1.27557844e-01 -5.02868116e-01 4.62150216e-01 -9.13055167e-02 -2.83775032e-01 4.04378414e-01 5.24210036e-01 4.52923089e-01 5.62636733e-01 -2.39665389e-01 -3.74054313e-01 2.70051677e-02 -5.11984587e-01 1.57536697e-02 1.24505770e+00 -7.28432694e-03 2.66073123e-02 3.15143734e-01 1.11722481e+00 -5.32506347e-01 -1.27862561e+00 -4.44972634e-01 4.30971235e-02 -4.65757340e-01 5.90195954e-01 -1.20984662e+00 -1.13388240e+00 6.18303239e-01 1.02893519e+00 7.28775710e-02 1.41389275e+00 -8.47180858e-02 2.90807337e-01 4.42207098e-01 4.08478051e-01 -1.19121587e+00 -1.91541359e-01 -2.02423558e-01 4.22604650e-01 -1.57328618e+00 4.94447410e-01 -4.24114853e-01 -9.05949950e-01 7.55038023e-01 4.46285456e-01 2.73745507e-01 7.07729638e-01 3.15712631e-01 2.98689723e-01 -2.00362906e-01 -1.07378960e+00 -1.98746435e-02 2.85572946e-01 5.63949108e-01 5.18281341e-01 7.05905035e-02 -4.61801708e-01 4.86730151e-02 3.07268113e-01 3.01988989e-01 3.46322775e-01 1.14959490e+00 -3.62639576e-01 -1.10206258e+00 -5.40774688e-02 1.21153843e+00 -6.69864237e-01 1.34650031e-02 -3.65365058e-01 3.87406439e-01 3.06606323e-01 9.11774218e-01 3.38013679e-01 7.54369050e-02 -1.97267115e-01 7.15419874e-02 6.40137434e-01 -8.24256003e-01 -2.73753285e-01 -1.46287950e-02 3.40699077e-01 -1.82664692e-01 -9.41384673e-01 -6.94415033e-01 -1.17872703e+00 2.82829195e-01 -8.11284959e-01 -1.19908430e-01 3.92634511e-01 1.01142561e+00 4.90511119e-01 4.41660285e-01 6.16044044e-01 -4.46296245e-01 -6.64738595e-01 -8.68706167e-01 -4.87545222e-01 2.23180592e-01 2.31179655e-01 -8.10087562e-01 -3.53699833e-01 2.49788627e-01]	[14.921767234802246, -2.3250699043273926]
3705d603-2871-4657-8e9f-08d3b7d814ab	rfc-net-learning-high-resolution-global	2302.06134	null	https://arxiv.org/abs/2302.06134v1	https://arxiv.org/pdf/2302.06134v1.pdf	RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget	Learning High-Resolution representations is essential for semantic segmentation. Convolutional neural network (CNN)architectures with downstream and upstream propagation flow are popular for segmentation in medical diagnosis. However, due to performing spatial downsampling and upsampling in multiple stages, information loss is inexorable. On the contrary, connecting layers densely on high spatial resolution is computationally expensive. In this work, we devise a Loose Dense Connection Strategy to connect neurons in subsequent layers with reduced parameters. On top of that, using a m-way Tree structure for feature propagation we propose Receptive Field Chain Network (RFC-Net) that learns high resolution global features on a compressed computational space. Our experiments demonstrates that RFC-Net achieves state-of-the-art performance on Kvasir and CVC-ClinicDB benchmarks for Polyp segmentation.	['David Chapman', 'Tim Oates', 'Md Osman Gani', 'Shaswati Saha', 'Sourajit Saha']	2023-02-13	null	null	null	null	['medical-diagnosis']	['medical']	[ 2.29501322e-01 3.27788085e-01 -3.51778269e-01 -4.32788938e-01 -7.45172381e-01 1.64882187e-02 1.23531818e-01 1.55959144e-01 -4.35631394e-01 6.55438423e-01 2.15021372e-01 -2.17789814e-01 -2.65802592e-01 -1.01868224e+00 -7.23759532e-01 -4.81149673e-01 -1.07509859e-01 1.53052464e-01 4.78842586e-01 -7.78555870e-02 -9.92940962e-02 5.60622215e-01 -9.13130403e-01 8.27452481e-01 7.61816978e-01 9.42327559e-01 2.41607293e-01 6.32182956e-01 -1.66722417e-01 8.07867348e-01 -1.20632134e-01 -2.35927626e-01 6.06481433e-02 -4.09481525e-01 -1.39985883e+00 -1.88226700e-01 1.47904366e-01 -2.39333868e-01 -3.49641651e-01 9.01927650e-01 3.15747708e-01 -4.15709428e-02 5.56140125e-01 -3.37951660e-01 -5.65712452e-01 8.99032295e-01 -6.68730378e-01 3.91402453e-01 -1.46978512e-01 1.40812807e-02 7.62137234e-01 -6.73359573e-01 7.32490897e-01 9.51437294e-01 1.10402918e+00 6.88454390e-01 -1.27793348e+00 -2.90847600e-01 1.85852960e-01 -1.95952863e-01 -1.34570348e+00 6.25410378e-02 5.24030626e-01 -1.94013670e-01 1.15708935e+00 1.59053117e-01 9.13163841e-01 1.04839230e+00 2.97831059e-01 7.09426880e-01 6.06911480e-01 -1.58539593e-01 9.93201360e-02 -9.57842693e-02 2.35030577e-01 8.99617732e-01 3.18823934e-01 -2.54506711e-02 -4.26734418e-01 1.21890418e-01 1.35521340e+00 3.38760257e-01 -4.38634783e-01 1.27136372e-02 -1.09389186e+00 1.03930104e+00 1.47505927e+00 5.85427880e-01 -5.14670312e-01 3.91321868e-01 4.68509674e-01 1.65391907e-01 3.86695176e-01 6.05048418e-01 -4.16361451e-01 2.10171670e-01 -1.15297258e+00 -1.00887947e-01 5.05030870e-01 7.50922859e-01 4.05643374e-01 -2.23179117e-01 -2.49405190e-01 7.36700773e-01 -4.26585451e-02 -2.18095660e-01 7.25260794e-01 -9.35384452e-01 3.74705106e-01 6.24061584e-01 -4.54506338e-01 -7.99736500e-01 -7.84821868e-01 -9.78382587e-01 -1.52304053e+00 1.07132658e-01 3.51395816e-01 -8.94762278e-02 -1.16012883e+00 1.24634087e+00 2.00879097e-01 3.58240396e-01 1.81116641e-01 1.00159848e+00 1.16826725e+00 5.92400253e-01 8.33991691e-02 1.57384634e-01 1.49073160e+00 -1.21144235e+00 -3.89004201e-01 -1.50560886e-01 7.26182282e-01 -5.17779112e-01 7.47935772e-01 2.20314726e-01 -1.24609399e+00 -5.73630750e-01 -1.01765215e+00 -4.87006575e-01 -2.80762762e-01 3.82364076e-03 9.05356228e-01 3.47318798e-01 -1.13940823e+00 1.04677057e+00 -1.26329434e+00 -1.57859892e-01 1.14684761e+00 4.32773739e-01 -2.29099616e-01 -2.13185638e-01 -9.99926388e-01 5.10640204e-01 2.99783349e-01 5.51924519e-02 -7.13399351e-01 -1.20838988e+00 -8.39894176e-01 1.56333148e-01 -7.01142699e-02 -1.15495908e+00 9.92441893e-01 -7.34033287e-01 -1.44341576e+00 7.39326179e-01 2.30749249e-01 -8.74472082e-01 5.87876379e-01 -1.83562830e-01 -2.76566539e-02 5.20022452e-01 -8.67064595e-02 1.20521712e+00 7.01027095e-01 -6.14872813e-01 -5.42679727e-01 -3.01176041e-01 -1.70405880e-01 1.91393316e-01 -1.96588859e-01 -3.66131365e-01 -5.31877995e-01 -7.59311199e-01 4.97554868e-01 -4.18862641e-01 -9.53956425e-01 2.75735587e-01 -5.13418555e-01 5.01378104e-02 5.51933587e-01 -6.10352039e-01 9.82972383e-01 -2.28329420e+00 9.61601436e-02 2.14800119e-01 5.21062136e-01 2.20077306e-01 2.69843042e-02 -2.32683092e-01 6.38612509e-02 1.54907018e-01 -3.86463910e-01 -1.99151486e-01 -6.81458890e-01 1.74706832e-01 1.03398174e-01 4.44776297e-01 5.15329719e-01 1.15692735e+00 -8.08118880e-01 -6.89358711e-01 1.67083606e-01 1.05841923e+00 -1.07315230e+00 -1.93121359e-01 2.47356687e-02 6.71761572e-01 -7.92294502e-01 5.75420022e-01 6.47507012e-01 -9.76359844e-01 -5.96152171e-02 -2.23507881e-01 -1.74563862e-02 3.95321310e-01 -6.43621504e-01 2.34824347e+00 -5.99036455e-01 2.99727738e-01 1.14617653e-01 -1.18597114e+00 6.47988856e-01 3.07594299e-01 4.80037332e-01 -5.68713486e-01 1.86018169e-01 2.67827928e-01 -2.06613585e-01 -1.22799940e-01 2.53203273e-01 6.90516690e-03 3.60935554e-02 -2.40872592e-01 1.61970615e-01 4.21338156e-02 -5.10103367e-02 1.79468130e-03 1.17243338e+00 -7.33263642e-02 2.98720479e-01 -2.95582235e-01 4.66661364e-01 1.67042702e-01 5.96195281e-01 6.94530964e-01 1.02507204e-01 1.08906317e+00 5.16858935e-01 -7.54102767e-01 -8.49312961e-01 -8.71752679e-01 -5.06799757e-01 6.06274486e-01 -2.86669470e-02 -3.26990396e-01 -8.24978352e-01 -5.85172772e-01 -3.38454932e-01 9.87077653e-02 -7.26221800e-01 -3.89336646e-02 -9.05415893e-01 -6.76522017e-01 6.44805908e-01 8.17792952e-01 7.03209221e-01 -1.10938394e+00 -1.03881037e+00 4.98199373e-01 4.73769195e-02 -9.13786709e-01 -3.05453092e-01 4.54324067e-01 -1.38674402e+00 -9.98808682e-01 -1.18141961e+00 -1.15199769e+00 8.75087738e-01 3.52811627e-02 1.32422829e+00 9.91242006e-02 -8.01171660e-01 -2.88817555e-01 -3.03507656e-01 1.24553002e-01 -1.32634088e-01 5.29055417e-01 -7.73979604e-01 -4.48624671e-01 9.79774371e-02 -5.94989717e-01 -1.20950377e+00 -5.69167733e-02 -7.14154184e-01 4.37713355e-01 8.66956413e-01 1.06986105e+00 1.11669791e+00 -4.21432517e-02 2.79097497e-01 -1.34612381e+00 1.92826852e-01 -3.89611453e-01 -6.04651153e-01 2.17301007e-02 -3.69706154e-01 2.94385646e-02 8.20163071e-01 -1.28308937e-01 -9.39673185e-01 3.67018491e-01 -5.77770770e-01 -4.91707593e-01 -1.48131311e-01 3.11207503e-01 4.98377919e-01 2.15921234e-02 7.76932478e-01 4.96338755e-02 2.88047623e-02 -5.65396070e-01 4.14165020e-01 1.94825351e-01 6.17337883e-01 -1.81205839e-01 2.03320056e-01 6.98298693e-01 2.36722618e-01 -6.14769101e-01 -9.75175261e-01 -3.55462760e-01 -5.71828902e-01 3.50066066e-01 1.41451454e+00 -9.98883009e-01 -5.97782671e-01 1.87047929e-01 -9.70407426e-01 -2.74938822e-01 -7.29103923e-01 6.61612511e-01 -4.97745454e-01 -1.34149134e-01 -1.23123443e+00 1.01064667e-01 -7.16418862e-01 -1.30378246e+00 9.14825737e-01 4.17780608e-01 -1.56753495e-01 -9.86617327e-01 -1.22092478e-01 6.05285764e-02 7.30711401e-01 3.77086788e-01 8.73950243e-01 -3.11585635e-01 -7.40653038e-01 -4.71228734e-02 -5.58458924e-01 1.46541342e-01 -4.46001850e-02 -4.57029849e-01 -8.82099628e-01 -2.50560641e-01 -9.30856168e-02 -3.33766460e-01 1.53981924e+00 1.12692368e+00 1.73252130e+00 -2.17745170e-01 -6.06961370e-01 1.35900390e+00 1.63074052e+00 -4.17108029e-01 6.51625574e-01 1.50173321e-01 7.61277258e-01 4.04809624e-01 5.02512567e-02 1.64086998e-01 -3.24312821e-02 1.51440114e-01 3.07276845e-01 -6.25001788e-01 -5.41840494e-01 -1.08093590e-01 -3.30748111e-01 5.92727661e-01 -1.32928565e-01 1.31738946e-01 -6.34101450e-01 4.50346917e-01 -1.64692950e+00 -6.02686882e-01 -1.30156547e-01 1.76637864e+00 9.03695762e-01 1.93958238e-01 -1.97142899e-01 -1.19414680e-01 5.36696017e-01 1.22157425e-01 -4.78408456e-01 -2.52443671e-01 1.12958923e-01 6.65919721e-01 7.28888273e-01 2.71071583e-01 -1.15215874e+00 7.86485374e-01 6.14527512e+00 9.36321139e-01 -1.03423929e+00 2.68946260e-01 1.21685481e+00 -1.41425163e-01 -1.01514004e-01 -4.62289870e-01 -8.24880302e-01 8.38273689e-02 7.22720981e-01 6.44892216e-01 1.10263288e-01 8.22410047e-01 -2.40450978e-01 2.01917231e-01 -9.14113045e-01 1.08222592e+00 -4.72427189e-01 -2.09803271e+00 1.25734359e-01 -3.04588117e-02 8.54674995e-01 3.60689193e-01 2.86336809e-01 1.95059642e-01 2.59367168e-01 -1.41162515e+00 2.54107863e-02 3.28220516e-01 1.01776361e+00 -9.00028706e-01 7.66737103e-01 1.33716622e-02 -1.09504640e+00 1.46966070e-01 -6.78634524e-01 4.13939506e-01 7.39926472e-02 8.30194354e-01 -5.92871070e-01 5.01989245e-01 8.46359372e-01 9.49719667e-01 -3.32240909e-01 9.89597797e-01 -5.79032814e-03 5.84869146e-01 -3.13076049e-01 3.11295241e-01 6.08396828e-01 1.76943570e-01 1.02586269e-01 1.42045701e+00 3.63768250e-01 1.33223832e-01 9.12312865e-02 9.87734377e-01 -4.19461221e-01 -9.80692580e-02 -3.78162235e-01 2.72685468e-01 7.61005208e-02 1.32771707e+00 -1.03436983e+00 -1.44949973e-01 -4.95158076e-01 1.04484129e+00 5.29593468e-01 1.45104557e-01 -5.63200057e-01 -4.04211551e-01 5.09451568e-01 2.40464374e-01 5.78332186e-01 2.75616348e-01 -6.41551673e-01 -8.35980773e-01 -2.22206578e-01 -3.67074966e-01 6.65878236e-01 -1.44762993e-01 -1.22499037e+00 8.31675470e-01 -4.72186208e-01 -1.24848163e+00 -1.85424499e-02 -5.72320640e-01 -4.34999526e-01 9.31132257e-01 -1.94882572e+00 -1.05613303e+00 -1.79666385e-01 7.32812762e-01 7.28900731e-01 2.71187406e-02 9.63380873e-01 2.00099736e-01 -2.62519240e-01 6.22293413e-01 -1.47798777e-01 3.80916536e-01 1.03898510e-01 -1.12186468e+00 4.70694661e-01 4.48993772e-01 -1.48658141e-01 4.69970524e-01 1.79161131e-02 -5.12622714e-01 -8.41086388e-01 -1.55914545e+00 6.44508421e-01 2.00176165e-01 2.68672138e-01 -3.39425020e-02 -1.10056365e+00 4.82959926e-01 1.73666745e-01 7.27388084e-01 6.14886582e-01 1.06045924e-01 -2.95025676e-01 4.53298166e-02 -1.40623868e+00 2.35851660e-01 9.00613725e-01 -2.19428837e-01 -3.46068680e-01 3.04937720e-01 1.06029391e+00 -6.87585056e-01 -1.18459511e+00 4.02991503e-01 2.67755330e-01 -9.30460095e-01 1.34081209e+00 -4.29471046e-01 7.92161167e-01 8.48907791e-03 1.10437289e-01 -1.07076561e+00 -5.68967223e-01 -4.33910936e-01 1.77672729e-01 5.77575564e-01 6.47647083e-01 -4.74823564e-01 1.07505918e+00 -2.34914180e-02 -4.75992441e-01 -1.22576475e+00 -9.13382351e-01 -3.56033772e-01 4.61271286e-01 -1.15236513e-01 3.19715679e-01 7.33771563e-01 -1.93000063e-01 2.53412426e-01 -3.40332389e-02 1.02725819e-01 4.69933450e-01 7.33513683e-02 -1.24377459e-01 -1.10017967e+00 -5.47348320e-01 -5.73633730e-01 -3.26673508e-01 -1.08078241e+00 -3.00500691e-01 -1.16700530e+00 -1.70254350e-01 -1.80597413e+00 3.14751089e-01 -5.50622821e-01 -5.61079323e-01 4.00684178e-01 1.35860210e-02 5.72624683e-01 -1.29948080e-01 1.89221635e-01 -5.89467525e-01 1.51765525e-01 1.67372870e+00 -1.13315791e-01 -3.54341984e-01 1.06595971e-01 -6.06506467e-01 9.12796319e-01 8.88633072e-01 -4.88821447e-01 -3.20158660e-01 -6.30014122e-01 2.01700822e-01 2.59811580e-01 3.75360399e-01 -1.07921469e+00 2.25550771e-01 3.72588009e-01 9.52692449e-01 -7.58127928e-01 3.10345769e-01 -5.66391349e-01 -1.33085012e-01 8.64928484e-01 -6.91294909e-01 -2.76306808e-01 8.42054263e-02 4.39914703e-01 -3.90404582e-01 -1.80657521e-01 1.09515822e+00 -6.42981946e-01 -3.10703635e-01 4.54994112e-01 -2.43770182e-01 8.83479044e-02 6.70379937e-01 -3.86333242e-02 -1.63737059e-01 3.26969713e-01 -9.51798618e-01 2.42688999e-01 5.62029220e-02 -5.44456057e-02 9.44468439e-01 -1.09036446e+00 -7.86956131e-01 3.72757107e-01 -2.06753939e-01 7.53574491e-01 5.18790007e-01 9.84692097e-01 -1.04400396e+00 5.21942496e-01 -1.56919330e-01 -7.82500505e-01 -8.90005350e-01 3.57529193e-01 5.14911354e-01 -8.30082893e-01 -1.49719977e+00 1.36609781e+00 4.51981336e-01 -3.24929774e-01 2.58368075e-01 -6.55840814e-01 -3.56661052e-01 -3.50157261e-01 6.25188231e-01 1.57679722e-01 2.78812051e-01 -1.53918535e-01 -2.73598671e-01 5.25212526e-01 -5.23020864e-01 2.72787988e-01 1.50696254e+00 1.70778885e-01 3.39410529e-02 -9.73273516e-02 1.33804059e+00 -5.76396227e-01 -1.37050211e+00 -2.68923044e-01 -2.81925350e-01 -9.32746306e-02 4.43718433e-01 -6.55524731e-01 -1.48433125e+00 8.97253811e-01 7.58128464e-01 -1.40912518e-01 1.24369919e+00 2.25112662e-01 1.11664379e+00 3.86864066e-01 5.12899831e-02 -8.96920562e-01 -3.44269462e-02 3.38791102e-01 6.18027449e-01 -1.05934083e+00 -5.50998077e-02 -7.07664549e-01 -4.41152513e-01 1.14195800e+00 4.79982883e-01 -5.74072897e-01 8.33458424e-01 4.31379378e-01 -1.68809295e-01 -4.49739218e-01 -6.14737749e-01 -1.31279141e-01 1.60571590e-01 4.93120849e-01 6.88957512e-01 1.92612126e-01 -1.70025781e-01 5.22920132e-01 -1.69269755e-01 1.06786661e-01 1.90010890e-01 8.22524071e-01 -3.75254780e-01 -7.32408762e-01 -4.88345698e-02 6.69633090e-01 -9.12525654e-01 -2.80942649e-01 2.91113317e-01 6.82739139e-01 1.31673098e-01 4.54775006e-01 4.13732618e-01 1.72324508e-01 1.57524407e-01 -3.63159269e-01 4.83979195e-01 -5.68534076e-01 -8.51778924e-01 3.05682838e-01 -2.34134302e-01 -8.51240695e-01 -1.63967818e-01 -2.43675411e-01 -1.75336730e+00 6.29514828e-02 -2.52294019e-02 9.12509300e-03 5.86865127e-01 4.93350178e-01 3.22720498e-01 1.28312242e+00 2.88693190e-01 -5.55381298e-01 -4.45692420e-01 -7.57952511e-01 -5.00015020e-01 2.13428408e-01 4.69201535e-01 -7.11136013e-02 1.09578490e-01 -1.32101983e-01]	[14.53510570526123, -2.592127561569214]
ff912a90-e43d-4f55-9d8c-4749d35ef4e5	why-words-alone-are-not-enough-error-analysis	null	null	https://aclanthology.org/W13-4101	https://aclanthology.org/W13-4101.pdf	Why Words Alone Are Not Enough: Error Analysis of Lexicon-based Polarity Classifier for Czech	null	['Jan Haji{\\v{c}} jr.', "Kate{\\v{r}}ina Veselovsk{\\'a}"]	2013-10-01	null	null	null	ws-2013-10	['fine-grained-opinion-analysis']	['natural-language-processing']	[-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01 -8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01 -2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00 -3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01 -9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01 7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01 7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00 -1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01 3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01 9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01 5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00 -5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01 1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00 7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01 -1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02 -1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01 1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00 1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01 3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01 8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01 9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01 -9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01 -1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01 -2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01 -8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00 1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01 8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00 -6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01 -6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01 3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01 4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02 4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01 1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01 9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01 -1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01 -7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00 -1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02 1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01 -1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01 -1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01 -4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01 -1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01 6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01 -1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00 -7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01 -1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01 3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01 -1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01 1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01 3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00 -2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01 2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01 -1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01 4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01 2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00 1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01 -3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00 7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01 3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01 -2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01 7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01 -2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01 6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00 7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00 -3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01 -6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00 3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01 1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01 -5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01 -5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01 -2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01 -1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01 5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01 -2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01 -4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01 5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01 -6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00 1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01 8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02 -6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01 -1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01 1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01 8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03 3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01 8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01 -1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01 6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01 -9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01 -1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00 -5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02 -5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01 1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01 -4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01 1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01 6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01 5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01 1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01 1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01 1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01 1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00 -8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01 -1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01 6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01 4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00 -1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00 -7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00 2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01 -4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02 1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01 3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01 9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01 7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01 6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01 1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01 -1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00 3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01 9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01 -4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01 4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00 2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01 5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01 2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01 -2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01 -6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01 -1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01 -5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01 -1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00 -6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01 -1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01 1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02 1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01 5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01 -4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01 -1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01 6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01 7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01 1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01 1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01 8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01 8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00 -4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01 -5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02 5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01 -2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00 -3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01 6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01 5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00 3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01 -8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00 -8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01 3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01 -3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05 -1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01 8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02 6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01 5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00 1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01 2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02 -1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01 -4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02 9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01 -8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02 7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01 -3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01 -1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01 -1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01 -2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01 1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03 6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01 -4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01 9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01 8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01 1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01 -1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01 8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01 5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01 9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01 -4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01 1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01 -9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00 5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01 -7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00 -6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01 -5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01 -5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01 4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01 -9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00 -8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00 -5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01 -2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00 -3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02 2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01]	[-7.156679153442383, 3.7958171367645264]
54694759-f82d-4a3a-8750-ba524632f266	optimized-three-deep-learning-models-based	2306.07296	null	https://arxiv.org/abs/2306.07296v1	https://arxiv.org/pdf/2306.07296v1.pdf	Optimized Three Deep Learning Models Based-PSO Hyperparameters for Beijing PM2.5 Prediction	Deep learning is a machine learning approach that produces excellent performance in various applications, including natural language processing, image identification, and forecasting. Deep learning network performance depends on the hyperparameter settings. This research attempts to optimize the deep learning architecture of Long short term memory (LSTM), Convolutional neural network (CNN), and Multilayer perceptron (MLP) for forecasting tasks using Particle swarm optimization (PSO), a swarm intelligence-based metaheuristic optimization methodology: Proposed M-1 (PSO-LSTM), M-2 (PSO-CNN), and M-3 (PSO-MLP). Beijing PM2.5 datasets was analyzed to measure the performance of the proposed models. PM2.5 as a target variable was affected by dew point, pressure, temperature, cumulated wind speed, hours of snow, and hours of rain. The deep learning network inputs consist of three different scenarios: daily, weekly, and monthly. The results show that the proposed M-1 with three hidden layers produces the best results of RMSE and MAPE compared to the proposed M-2, M-3, and all the baselines. A recommendation for air pollution management could be generated by using these optimized models	['Felix Andika Dwiyanto', 'Agung Bella Putra Utama', 'Aji Prasetya Wibawa', 'Yingchi Mao', 'Andri Pranolo']	2023-06-10	null	null	null	null	['metaheuristic-optimization']	['methodology']	[-2.65063733e-01 -6.79832280e-01 3.01476475e-02 4.17226665e-02 6.15744814e-02 6.12174068e-03 4.05728847e-01 1.63325161e-01 -5.64553499e-01 9.31747854e-01 -3.91978398e-02 -5.34257770e-01 -6.18528128e-01 -1.05909157e+00 -4.70412105e-01 -1.12334538e+00 -2.92301774e-01 1.12099908e-01 -9.52733979e-02 -2.45928109e-01 4.00963843e-01 7.19548047e-01 -1.38242614e+00 5.94938211e-02 9.61525321e-01 1.13984227e+00 6.70806289e-01 7.80075014e-01 -2.57447008e-02 4.82673436e-01 -7.80239284e-01 1.19730189e-01 2.88928270e-01 -1.38712646e-02 -3.26021105e-01 -3.79751027e-01 -2.21212447e-01 2.65187770e-01 6.86738044e-02 9.15556371e-01 7.22518623e-01 7.42834449e-01 2.81452090e-01 -1.13776815e+00 -6.86222017e-01 2.78486073e-01 -9.06693116e-02 8.07694793e-01 -4.43429798e-01 1.77253634e-01 2.50794560e-01 -4.03293401e-01 -2.97419012e-01 1.22488070e+00 1.08155990e+00 2.14150921e-01 -4.43456173e-01 -5.29013991e-01 -1.10677078e-01 4.65726703e-01 -1.15713692e+00 2.19167560e-01 3.34628105e-01 -4.64006126e-01 1.54170799e+00 2.90166736e-01 7.52337396e-01 7.34418631e-01 1.18966317e+00 2.05332544e-02 9.32259798e-01 -2.51216859e-01 2.51182258e-01 3.31518948e-01 1.90708056e-01 5.91720641e-01 4.49890763e-01 6.29855156e-01 -4.72711846e-02 -1.46937504e-01 2.22550035e-01 1.91019073e-01 7.51138180e-02 9.00958478e-01 -8.10774326e-01 7.87541866e-01 7.26053894e-01 4.11821693e-01 -9.14471805e-01 3.02376114e-02 2.46607199e-01 3.31597030e-01 5.35338998e-01 9.63188052e-01 -9.88913774e-01 -1.53672203e-01 -7.34309494e-01 6.61304519e-02 7.65037835e-01 1.12158544e-01 3.80513608e-01 6.21520221e-01 -2.94083625e-01 9.05763686e-01 4.98079330e-01 9.29460466e-01 1.04849195e+00 -5.96127748e-01 4.69270915e-01 4.67696637e-01 3.38276416e-01 -1.70134163e+00 -8.51383269e-01 -6.48793340e-01 -1.14013171e+00 -1.10357516e-01 -4.65281844e-01 -8.54356289e-01 -7.47661591e-01 1.07885635e+00 -4.21719626e-02 3.89161974e-01 3.99177045e-01 5.41504502e-01 9.96891618e-01 1.51106381e+00 1.46644443e-01 -1.30776748e-01 1.12503040e+00 -1.53534925e+00 -5.96749544e-01 -2.39006117e-01 3.18140745e-01 -5.84901750e-01 6.12648308e-01 1.39669338e-02 -7.60885239e-01 -9.68237162e-01 -9.93361771e-01 8.13085318e-01 -1.11787617e+00 4.00302052e-01 2.79050767e-01 7.25098968e-01 -9.82187927e-01 1.07694936e+00 -9.52099323e-01 -3.69216800e-01 1.48911148e-01 5.62612355e-01 1.98423937e-01 6.07891500e-01 -1.42339110e+00 1.21152008e+00 6.86348915e-01 6.46051168e-01 -3.50286245e-01 -4.70701218e-01 -5.15442908e-01 4.23880965e-01 -5.64966381e-01 -8.89165401e-01 8.28197658e-01 -8.78291667e-01 -1.62367213e+00 -6.86367750e-02 -1.40553802e-01 -6.03106439e-01 -1.46670505e-01 -8.54922980e-02 -9.35846806e-01 -7.57593438e-02 -1.87281623e-01 4.78905261e-01 5.18025696e-01 -7.76787579e-01 -9.14063990e-01 -2.06419528e-01 -2.24072173e-01 3.02550405e-01 -5.59475005e-01 1.31483376e-01 4.31359500e-01 -5.65562487e-01 -3.23322415e-01 -1.02367246e+00 -5.68205953e-01 -7.46778071e-01 -2.47667432e-01 -1.50488198e-01 7.86023676e-01 -8.11225235e-01 1.25396061e+00 -1.89083731e+00 -2.50323087e-01 3.89046043e-01 -5.03781855e-01 8.98051262e-01 -1.84006199e-01 2.92592853e-01 1.42204657e-01 4.59059596e-01 -5.46543347e-03 -3.27443480e-02 -6.74821809e-02 5.76929927e-01 1.05236910e-01 1.38926178e-01 1.05635025e-01 8.06918383e-01 -7.34069526e-01 -6.46412298e-02 6.08973682e-01 4.89575565e-01 8.24909583e-02 -1.52707370e-02 -3.14053118e-01 2.72717535e-01 -4.35173422e-01 3.89373273e-01 7.32946038e-01 -4.75607723e-01 -4.13376927e-01 -1.46221397e-02 -7.03427196e-01 -1.53155461e-01 -1.11651111e+00 4.73979592e-01 -6.29750192e-01 9.03747082e-01 -3.14705670e-01 -7.99186587e-01 9.91092682e-01 4.51226354e-01 3.72755975e-01 -7.58766055e-01 2.86701173e-01 1.43900245e-01 7.82999769e-02 -1.08720028e+00 4.48008269e-01 2.68716872e-01 5.85976720e-01 7.95234367e-02 -5.15731037e-01 4.10612404e-01 1.02983095e-01 -8.84706378e-01 5.39411008e-01 -5.84351122e-01 -1.19240865e-01 -2.18136594e-01 7.70755708e-01 1.23448549e-02 4.88355726e-01 8.58795524e-01 -3.70308012e-02 1.75619170e-01 6.60333484e-02 -7.44925141e-01 -8.54008496e-01 -3.33290249e-01 -1.89438954e-01 1.01389360e+00 -5.56689426e-02 3.04559827e-01 -4.26759720e-01 2.67217040e-01 -5.53502655e-03 1.01128197e+00 -4.20191288e-01 -2.79224455e-01 -5.06077409e-01 -1.54980922e+00 4.87764955e-01 3.37402165e-01 1.18597865e+00 -1.46918285e+00 -6.80109859e-01 3.66084874e-01 2.18580738e-01 -8.29292655e-01 9.25364122e-02 1.36615083e-01 -9.82278883e-01 -6.58395886e-01 -4.39372212e-01 -8.90513122e-01 4.78291601e-01 8.77502561e-02 8.14981699e-01 1.16662271e-01 2.83178598e-01 -6.69073965e-03 -2.36113325e-01 -8.33018661e-01 -3.27798903e-01 1.73589677e-01 -4.21146490e-03 -2.28661131e-02 2.04774350e-01 -4.81334239e-01 -5.56905210e-01 2.73037255e-01 -5.64220190e-01 -3.26021850e-01 6.80689096e-01 7.22313106e-01 4.11207974e-01 9.09755349e-01 4.27401692e-01 -2.89690673e-01 1.04526079e+00 -7.94562161e-01 -6.89599514e-01 2.45580256e-01 -1.01362062e+00 -2.93175846e-01 9.48087096e-01 -3.15500885e-01 -1.01221156e+00 -5.26967049e-01 -2.61643320e-01 -2.79654860e-01 -2.16207579e-01 1.05388284e+00 2.08472148e-01 -4.47286636e-01 5.08968294e-01 3.79486591e-01 -2.31609941e-01 -6.17487192e-01 -3.69738281e-01 8.54896665e-01 2.78607637e-01 -2.30348930e-02 3.81814152e-01 5.04961535e-02 4.69985828e-02 -1.26944876e+00 -8.29813838e-01 -2.50731051e-01 -2.25445539e-01 -1.12181112e-01 1.07859993e+00 -6.83449864e-01 -7.34535098e-01 8.44190478e-01 -1.20534551e+00 -1.99491397e-01 4.11981456e-02 7.68414855e-01 2.50922412e-01 -2.05100819e-01 -3.68278593e-01 -6.79701447e-01 -8.54509175e-01 -1.10011232e+00 3.82819980e-01 7.88603485e-01 2.42192730e-01 -1.61689341e+00 5.62432408e-02 3.01753730e-01 1.04608655e+00 4.89712954e-01 8.85305226e-01 -6.33871496e-01 1.74488220e-02 -2.71074265e-01 -6.34940937e-02 8.69315803e-01 1.24149710e-01 2.62781888e-01 -6.33152544e-01 -2.06002966e-01 2.27871731e-01 4.19500351e-01 5.38841128e-01 8.39583039e-01 1.37891626e+00 -9.20532584e-01 -1.72368482e-01 8.67339313e-01 1.52150810e+00 8.58365715e-01 5.26499093e-01 1.09623122e+00 5.01096785e-01 -5.79301342e-02 1.51593417e-01 3.96267414e-01 2.90918827e-01 9.15081277e-02 5.18219233e-01 -7.98213333e-02 4.90136713e-01 3.36457253e-01 3.75410616e-01 9.62290943e-01 -2.27626190e-01 -6.54560506e-01 -9.95232284e-01 3.45897704e-01 -1.66345584e+00 -1.17225862e+00 -2.17306092e-01 1.66318965e+00 1.78618908e-01 8.61963108e-02 -2.31108338e-01 9.09683108e-02 7.51681864e-01 2.94258416e-01 -3.76682639e-01 -9.93360400e-01 -2.09983185e-01 5.14208913e-01 8.93047333e-01 2.92930812e-01 -1.23691809e+00 4.48368996e-01 5.48901653e+00 4.08780485e-01 -1.71856415e+00 2.17367738e-01 5.02861202e-01 -7.97792003e-02 2.29121819e-01 -4.99242336e-01 -9.54963446e-01 1.00947750e+00 1.76271963e+00 -8.64772964e-03 5.09776175e-01 5.77227652e-01 1.00437975e+00 -1.05655991e-01 -2.44009823e-01 7.93637097e-01 -2.29268312e-01 -1.50044501e+00 2.00407445e-01 -1.34242281e-01 1.19838095e+00 7.45058060e-01 2.10435748e-01 4.52295482e-01 -1.51718304e-01 -1.15682983e+00 7.45614097e-02 1.03421462e+00 -2.97632396e-01 -9.08079445e-01 1.42518663e+00 5.46840012e-01 -1.02395916e+00 -7.44168282e-01 -7.05948174e-01 -3.18256170e-01 -1.91912502e-01 5.68420887e-01 -3.93399715e-01 4.47039485e-01 9.48059499e-01 6.63548052e-01 -4.99601036e-01 1.35597396e+00 1.37848556e-01 8.98603857e-01 -5.14160633e-01 -6.78934753e-01 6.83381677e-01 -1.42150998e-01 7.01868713e-01 1.19939935e+00 4.46645558e-01 4.95151356e-02 1.86529011e-01 5.22172630e-01 2.23194569e-01 7.72373751e-02 -1.03699811e-01 -2.06820697e-01 6.12560689e-01 1.01913893e+00 -4.93563175e-01 -2.04264358e-01 -1.52594209e-01 2.79366881e-01 -3.62279415e-01 4.31175768e-01 -8.84238482e-01 -5.65110207e-01 6.10129237e-01 -4.47234809e-01 4.93754029e-01 -1.57528281e-01 -4.74721968e-01 -5.12326062e-01 -1.05815724e-01 -6.15018904e-01 2.58163571e-01 -9.00584579e-01 -1.17538643e+00 5.77926517e-01 -6.79606721e-02 -1.02867246e+00 6.64803460e-02 -8.53878319e-01 -1.31108916e+00 1.11117446e+00 -1.79398501e+00 -4.42348748e-01 -5.49217284e-01 2.55948395e-01 3.85830641e-01 -6.88690305e-01 8.70735526e-01 4.16798174e-01 -1.09911919e+00 2.10019305e-01 9.11434114e-01 -9.17157754e-02 -2.09607840e-01 -8.15034628e-01 3.29595476e-01 6.66924357e-01 -4.41770583e-01 4.12395328e-01 5.70962667e-01 -5.49352109e-01 -1.17647135e+00 -1.66775727e+00 9.65991259e-01 3.30128282e-01 4.52595979e-01 5.45105457e-01 -5.31439543e-01 3.74528438e-01 3.21114749e-01 -2.65893996e-01 5.68780184e-01 -3.60806555e-01 8.84464860e-01 -4.91864949e-01 -1.30876112e+00 2.56013781e-01 -1.90459862e-01 1.58458471e-01 -3.27377468e-01 6.99234009e-01 5.42452455e-01 -5.14874816e-01 -1.24365509e+00 4.69799876e-01 5.02121627e-01 -6.85694873e-01 1.00111985e+00 -5.88780105e-01 2.05162525e-01 -9.49202254e-02 -9.23592895e-02 -1.61286104e+00 -4.92944270e-01 -2.13498831e-01 -1.28291205e-01 6.38101518e-01 7.07820714e-01 -1.25497198e+00 5.37898958e-01 4.97210979e-01 -2.42638260e-01 -1.14632225e+00 -9.36550736e-01 -9.17306840e-01 -6.95657879e-02 -7.73736462e-02 9.05218124e-01 8.47229898e-01 -9.22634423e-01 5.48085980e-02 -3.00970852e-01 8.44908297e-01 8.25417787e-03 -8.47521722e-02 4.16096032e-01 -1.31031144e+00 9.75037217e-02 -6.87702000e-01 -3.31203580e-01 -5.15310705e-01 -5.48712946e-02 -4.92465466e-01 -2.18789652e-01 -1.86462855e+00 -4.38965023e-01 -2.05796272e-01 -7.59882689e-01 5.29104173e-01 -1.07646845e-01 -2.85458744e-01 1.59126744e-01 1.76943973e-01 -5.32043576e-02 7.08214104e-01 1.14694107e+00 -1.73563197e-01 -6.70976162e-01 6.96326315e-01 -2.87430108e-01 8.47932696e-01 1.36506319e+00 -6.87745631e-01 -1.38500452e-01 -8.64790082e-01 2.68201798e-01 2.22720727e-02 3.48903179e-01 -1.52836239e+00 4.82007325e-01 -4.10937995e-01 7.75097489e-01 -7.66462445e-01 2.88948923e-01 -8.33903730e-01 3.47598493e-01 8.79118443e-01 -2.11021692e-01 7.30182052e-01 6.26165986e-01 3.48017126e-01 -2.36794621e-01 -4.84468549e-01 7.38437891e-01 -3.10192257e-01 -8.24956119e-01 4.10925746e-01 -6.78007782e-01 -3.92967284e-01 8.12053263e-01 -4.49978322e-01 -4.37595427e-01 9.64564830e-02 -8.00545812e-01 6.37108743e-01 -2.20295846e-01 5.23468792e-01 6.36086345e-01 -1.11530268e+00 -6.16303980e-01 1.79468989e-01 -7.28634596e-01 -2.60021240e-01 2.03956559e-01 8.62610102e-01 -9.85130489e-01 6.64704919e-01 -4.26156759e-01 -4.42640573e-01 -1.02001488e+00 -1.58201098e-01 1.09471273e+00 -3.76021028e-01 -9.12517160e-02 8.20936918e-01 -7.24945307e-01 -7.09707379e-01 2.45144024e-01 -4.99956667e-01 -7.79922843e-01 -1.13632120e-01 2.43125573e-01 1.06716049e+00 2.85935640e-01 -3.85361701e-01 -3.29402447e-01 4.02036399e-01 5.26502192e-01 4.30464476e-01 1.63155830e+00 2.96095479e-02 -4.15809095e-01 4.54541504e-01 1.21720815e+00 -4.52591836e-01 -4.68677372e-01 2.84726888e-01 5.81516922e-02 2.49318462e-02 5.26553631e-01 -1.02104783e+00 -1.18800867e+00 6.28285825e-01 1.17422545e+00 2.61787355e-01 1.16290808e+00 -1.01314855e+00 1.33164585e+00 9.15032446e-01 -4.13213611e-01 -1.11094201e+00 -2.57005781e-01 1.00781167e+00 5.93658447e-01 -1.23017097e+00 -6.24869615e-02 7.21888542e-01 -2.07168207e-01 1.39996338e+00 7.04727590e-01 -3.13081183e-02 1.25759518e+00 -1.06317922e-01 -3.33069712e-02 -2.07778335e-01 -8.43368292e-01 1.40982404e-01 3.92270029e-01 2.43018374e-01 -6.28889054e-02 2.54204988e-01 -5.35936765e-02 3.78615797e-01 -4.45562750e-01 -6.13741064e-03 1.61676720e-01 8.03686440e-01 -8.05105448e-01 -4.39825982e-01 -5.95001817e-01 8.73423457e-01 -4.83468622e-01 -2.52290398e-01 9.08161178e-02 6.14062130e-01 6.28789067e-01 1.24787962e+00 2.93582976e-01 -5.18566787e-01 3.03433269e-01 -3.69400471e-01 -1.32735312e-01 -3.32089424e-01 -1.13327026e+00 -6.50413573e-01 -1.10969245e-01 4.12615873e-02 -5.83040297e-01 -2.80205339e-01 -1.08156121e+00 -6.27609551e-01 -4.28299129e-01 5.75733304e-01 1.18699598e+00 1.26999211e+00 5.49914122e-01 6.27638221e-01 9.04969990e-01 -9.80542600e-01 -4.76745129e-01 -1.15127754e+00 -4.04288262e-01 -3.96880001e-01 4.62526411e-01 -6.13678932e-01 -6.56769276e-01 -4.31998432e-01]	[6.208837032318115, 2.8080077171325684]
f5c0df20-48a8-4a8e-85e9-17f01be52334	alfworld-aligning-text-and-embodied	2010.03768	null	https://arxiv.org/abs/2010.03768v2	https://arxiv.org/pdf/2010.03768v2.pdf	ALFWorld: Aligning Text and Embodied Environments for Interactive Learning	Given a simple request like Put a washed apple in the kitchen fridge, humans can reason in purely abstract terms by imagining action sequences and scoring their likelihood of success, prototypicality, and efficiency, all without moving a muscle. Once we see the kitchen in question, we can update our abstract plans to fit the scene. Embodied agents require the same abilities, but existing work does not yet provide the infrastructure necessary for both reasoning abstractly and executing concretely. We address this limitation by introducing ALFWorld, a simulator that enables agents to learn abstract, text based policies in TextWorld (C\^ot\'e et al., 2018) and then execute goals from the ALFRED benchmark (Shridhar et al., 2020) in a rich visual environment. ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions. In turn, as we demonstrate empirically, this fosters better agent generalization than training only in the visually grounded environment. BUTLER's simple, modular design factors the problem to allow researchers to focus on models for improving every piece of the pipeline (language understanding, planning, navigation, and visual scene understanding).	['Matthew Hausknecht', 'Adam Trischler', 'Yonatan Bisk', 'Marc-Alexandre Côté', 'Xingdi Yuan', 'Mohit Shridhar']	2020-10-08	null	null	null	null	['natural-language-visual-grounding']	['reasoning']	[-1.66168720e-01 5.28659046e-01 2.32431024e-01 -1.10899761e-01 -2.41449684e-01 -7.76110470e-01 8.25336695e-01 8.49458724e-02 -4.54164654e-01 6.06761754e-01 4.83621418e-01 -6.00640655e-01 3.96933407e-02 -6.60447001e-01 -8.79109561e-01 -3.29742521e-01 -1.60561964e-01 6.94540381e-01 1.02322049e-01 -4.23333913e-01 3.05159181e-01 4.29326326e-01 -1.49694383e+00 4.28724200e-01 6.24066770e-01 3.49319786e-01 7.18747199e-01 9.21077311e-01 2.24007756e-01 1.36376488e+00 -3.96768123e-01 -1.88373983e-01 4.08890277e-01 -4.73698884e-01 -1.14311862e+00 5.33974618e-02 2.68774480e-01 -6.99131727e-01 -3.18055660e-01 6.46302521e-01 8.81276950e-02 5.75872302e-01 4.12783504e-01 -1.34092832e+00 -7.25900829e-01 9.38609779e-01 -1.81226164e-01 4.03524190e-02 8.03815365e-01 1.33981717e+00 8.03456366e-01 -4.28247988e-01 7.83747673e-01 1.46942985e+00 4.94275033e-01 7.59693563e-01 -1.17467976e+00 -2.66384423e-01 7.59731591e-01 8.18257928e-02 -7.83365428e-01 -4.09697652e-01 1.03185497e-01 -4.45412159e-01 1.48926950e+00 -2.20505297e-02 1.18734348e+00 1.38870168e+00 2.54105194e-03 9.18145716e-01 1.14958560e+00 -2.30683833e-01 5.84978163e-01 -1.95974737e-01 -1.23091213e-01 9.89825666e-01 3.10389876e-01 6.66468799e-01 -5.46962321e-01 1.83493018e-01 1.04451525e+00 -1.39297321e-01 -1.81057394e-01 -6.55728877e-01 -1.51099575e+00 4.25112873e-01 6.52654588e-01 1.12906657e-01 -7.32094407e-01 5.89758396e-01 1.78380519e-01 2.26866335e-01 -3.67954195e-01 1.05893564e+00 -3.89064729e-01 -3.31404656e-01 -2.63532668e-01 5.76575637e-01 8.06587398e-01 1.12354922e+00 5.51738441e-01 1.91047654e-01 -1.72469184e-01 1.04238883e-01 5.23351192e-01 4.41167802e-01 3.41631413e-01 -1.64684379e+00 3.80501449e-01 7.57139683e-01 4.70115572e-01 -5.26023448e-01 -8.95454288e-01 -2.03246251e-01 -5.02685830e-02 9.89520073e-01 6.18222058e-01 -2.85163045e-01 -9.68792140e-01 1.84363508e+00 2.32421666e-01 9.08626094e-02 5.49302518e-01 1.16894698e+00 6.87459290e-01 6.20704949e-01 6.36105478e-01 3.37087035e-01 1.44539464e+00 -1.34077871e+00 -3.11660916e-01 -8.63189757e-01 8.45089972e-01 -3.00322194e-02 1.64309955e+00 4.20999587e-01 -1.37974107e+00 -4.52731669e-01 -1.08045650e+00 -1.97016761e-01 -3.84903789e-01 -2.50053674e-01 1.16577554e+00 1.85990751e-01 -1.29671347e+00 4.18812901e-01 -1.11344862e+00 -7.51791298e-01 3.68540496e-01 1.70805588e-01 -5.00071406e-01 2.36935411e-02 -7.33042479e-01 1.42974639e+00 5.98348796e-01 -4.05066125e-02 -1.61507690e+00 -3.78523409e-01 -1.09219074e+00 1.59328699e-01 5.92997193e-01 -1.12715936e+00 1.82056904e+00 -6.83093369e-01 -1.78886783e+00 7.18077779e-01 3.35320562e-01 -6.50659859e-01 4.75438744e-01 -1.18945830e-01 5.48554063e-02 7.67784417e-02 1.33119375e-01 9.76904511e-01 2.59339184e-01 -1.44049191e+00 -7.63254464e-01 -3.87129247e-01 7.98840284e-01 7.23859131e-01 4.80678797e-01 -3.20368588e-01 -1.93483353e-01 -1.97794586e-01 -1.94360800e-02 -9.19967413e-01 -4.25879896e-01 -3.09563410e-02 -3.93668450e-02 -1.39415219e-01 2.14572519e-01 -5.96604168e-01 4.52512711e-01 -2.02411413e+00 4.32041824e-01 -1.40727580e-01 2.92894304e-01 1.85616855e-02 -3.93430322e-01 6.46358311e-01 2.01955646e-01 4.92496789e-02 -6.13878155e-03 -2.16404766e-01 4.92100060e-01 1.23663522e-01 -1.23820104e-01 9.71655250e-02 -2.29422405e-01 1.35714352e+00 -1.25542390e+00 -1.29513368e-01 4.84215826e-01 1.23931721e-01 -7.76909232e-01 1.76177546e-01 -7.35161364e-01 5.14634788e-01 -4.02866364e-01 2.03218535e-01 2.56018192e-01 -2.69542485e-01 3.08886647e-01 2.85875797e-01 -2.50501364e-01 4.40436691e-01 -1.06853962e+00 2.02480793e+00 -6.32883966e-01 5.80249310e-01 8.18696395e-02 -3.77427816e-01 4.04436022e-01 1.26850992e-01 -7.17676207e-02 -9.08690333e-01 1.95315238e-02 -9.16185305e-02 2.24500597e-01 -8.20362985e-01 3.22212845e-01 -1.36207610e-01 -4.23502997e-02 6.14183784e-01 -1.41819090e-01 -5.25415599e-01 2.79691517e-01 3.90433520e-01 1.28706932e+00 8.45111966e-01 5.25694013e-01 -1.02238074e-01 -1.84356973e-01 6.45091653e-01 -6.48348406e-02 1.13017416e+00 -2.46814743e-01 1.97621360e-01 3.24854732e-01 -6.88619494e-01 -1.09949434e+00 -1.31687295e+00 6.88146055e-01 1.36805820e+00 3.21324736e-01 -3.54092240e-01 -8.64078403e-01 -4.66000468e-01 -1.62536427e-01 1.48685253e+00 -8.36983085e-01 -2.43769675e-01 -6.94289207e-01 -9.33286920e-03 5.54154992e-01 6.72018111e-01 6.14913106e-01 -1.69744682e+00 -1.66828954e+00 8.77436250e-02 -9.40350816e-02 -8.79315853e-01 -1.45699114e-01 2.14716911e-01 -6.84456348e-01 -1.05483055e+00 -1.86230615e-01 -6.43509865e-01 5.35602510e-01 3.75951916e-01 1.24642611e+00 3.39550257e-01 -6.91683441e-02 8.26364815e-01 -3.48742545e-01 -4.31355774e-01 -4.62752253e-01 -2.91608214e-01 -9.91470069e-02 -7.81793237e-01 1.61142200e-01 -3.13576639e-01 -6.52337253e-01 4.62891273e-02 -5.69170892e-01 7.35494852e-01 6.83031380e-01 5.93205631e-01 3.13832983e-02 -2.13683218e-01 8.51138458e-02 -4.39010412e-01 8.23494911e-01 -3.61549854e-01 -7.27140546e-01 1.67634442e-01 -3.26313019e-01 2.40719572e-01 4.72545028e-01 -3.58028948e-01 -1.26181066e+00 -7.41112337e-04 1.19837224e-01 1.39879242e-01 -5.31911790e-01 4.57153112e-01 1.19542144e-02 2.71110177e-01 1.03261387e+00 2.14324996e-01 -1.22638457e-01 -1.26708940e-01 7.25194633e-01 -3.67355496e-02 6.37611508e-01 -8.75075221e-01 6.62129998e-01 3.55753034e-01 -2.52995968e-01 -3.53491008e-01 -4.43602115e-01 2.38275193e-02 -4.17141438e-01 -1.10252269e-01 1.09980643e+00 -8.95585597e-01 -1.61343801e+00 2.67307371e-01 -1.05726039e+00 -1.40262759e+00 -5.75954378e-01 5.09603798e-01 -1.13819325e+00 -2.88576782e-02 -4.64053482e-01 -7.54108310e-01 3.31770837e-01 -1.31382990e+00 8.43543172e-01 3.26712698e-01 -7.49043822e-01 -8.63200009e-01 5.60040250e-02 2.29125470e-01 3.50557774e-01 9.47409049e-02 9.29697573e-01 -5.25778592e-01 -9.41142857e-01 3.08332413e-01 -7.84835294e-02 -3.63990903e-01 -2.09471121e-01 -3.26319486e-01 -5.93736231e-01 -1.81644738e-01 -1.16255291e-01 -6.33911133e-01 5.21462440e-01 2.09869683e-01 7.93536425e-01 -5.00670314e-01 -4.08456147e-01 6.01888776e-01 1.07251275e+00 4.84795153e-01 7.12557793e-01 8.80124390e-01 3.02302420e-01 5.46148360e-01 5.46195269e-01 2.94212222e-01 9.05477107e-01 6.41064346e-01 7.44283259e-01 2.64966954e-02 -1.40879661e-01 -6.10320807e-01 5.08668780e-01 -2.20299169e-01 -2.65032560e-01 -4.15645003e-01 -1.09651423e+00 3.38911682e-01 -2.01443529e+00 -1.31653702e+00 1.81181893e-01 1.78890538e+00 6.39455259e-01 2.85651356e-01 1.82332933e-01 -4.77741301e-01 1.69909939e-01 3.72173525e-02 -7.81934977e-01 -4.94970411e-01 1.67507112e-01 -1.45940453e-01 2.94867754e-01 8.77262056e-01 -5.83775461e-01 1.41894209e+00 6.80206394e+00 1.93877183e-02 -7.07718730e-01 -1.51928827e-01 3.02381128e-01 -2.01024935e-01 -2.62205809e-01 1.77839637e-01 -3.98842961e-01 7.68614560e-02 7.19149411e-01 -1.71898436e-02 1.10976803e+00 8.36054385e-01 2.87054241e-01 -5.17569661e-01 -1.48967314e+00 7.75987267e-01 -1.06133357e-01 -1.29153490e+00 3.07797338e-03 -1.10390373e-01 3.41623813e-01 -1.04290321e-02 2.26783827e-01 8.35651398e-01 1.25407994e+00 -1.57795036e+00 1.17885852e+00 4.34711337e-01 1.97376534e-01 -1.77565426e-01 2.59223044e-01 7.40826070e-01 -8.05096328e-01 -2.87998796e-01 -2.14316547e-02 -7.03382075e-01 2.50094205e-01 -6.49343789e-01 -1.08421636e+00 1.17197163e-01 6.28725350e-01 2.99421132e-01 -5.17021060e-01 8.01028311e-01 -5.24940252e-01 1.01834670e-01 -2.26169959e-01 -3.12890261e-01 5.29383361e-01 -8.98091048e-02 4.37071830e-01 8.71318996e-01 1.58727974e-01 5.86180508e-01 2.13993624e-01 9.25423265e-01 3.27271014e-01 -3.12584668e-01 -7.43890166e-01 -1.63761169e-01 4.06218469e-01 8.60986590e-01 -7.57593632e-01 -3.67693454e-01 -3.11156452e-01 9.22467053e-01 5.37887037e-01 7.67233729e-01 -7.71467566e-01 1.82998300e-01 7.19496310e-01 6.40195515e-03 1.14878587e-01 -5.26028275e-01 -4.59180564e-01 -9.31236267e-01 -2.47061133e-01 -1.45729983e+00 2.29284316e-01 -1.50970459e+00 -6.39305234e-01 4.67338175e-01 1.43937930e-01 -7.20700920e-01 -3.53178382e-01 -9.25048649e-01 -4.95333254e-01 7.51515090e-01 -9.55019951e-01 -1.25500143e+00 -7.58948445e-01 4.79223371e-01 7.74320424e-01 -1.56642854e-01 8.69145572e-01 -6.47436559e-01 -2.31637165e-01 9.65816230e-02 -6.13005042e-01 -1.61335409e-01 2.94839829e-01 -1.29214513e+00 1.08590364e+00 5.67382395e-01 5.29059768e-02 8.04660857e-01 1.11565423e+00 -7.43531942e-01 -1.48009038e+00 -3.90666246e-01 1.07505649e-01 -1.04512656e+00 5.25023937e-01 -2.78709352e-01 -6.31700039e-01 1.40227377e+00 5.15540600e-01 -4.24372911e-01 2.08357483e-01 7.59665947e-03 -3.71860623e-01 4.83213931e-01 -1.13742769e+00 1.44849646e+00 1.67156017e+00 -2.65593499e-01 -1.01982033e+00 3.29619199e-01 8.87174964e-01 -6.61760509e-01 -3.39122415e-01 7.07817674e-02 6.60981059e-01 -1.29090488e+00 1.06576550e+00 -1.14303303e+00 3.15705538e-01 -5.64433753e-01 -1.82368383e-01 -1.74360728e+00 -5.81808209e-01 -6.45049810e-01 -1.73848476e-02 4.87731993e-01 4.22978938e-01 -6.16801441e-01 6.70900464e-01 7.13060677e-01 -3.29505861e-01 -3.52515131e-01 -4.15011257e-01 -6.72722340e-01 -6.86807483e-02 -4.86015022e-01 8.47661018e-01 4.58824456e-01 5.95400989e-01 2.77781576e-01 1.07986696e-01 3.57670933e-01 3.40943873e-01 -1.96512610e-01 1.11333621e+00 -8.98463905e-01 -5.32384813e-01 -7.84005284e-01 -2.36090180e-02 -1.30138886e+00 1.54353855e-02 -8.40059817e-01 2.69165903e-01 -2.18648052e+00 1.49069265e-01 -3.68534803e-01 1.35258436e-01 6.64054275e-01 1.11137070e-01 -3.25828135e-01 6.72689259e-01 -8.81411601e-03 -9.49209929e-01 3.74009550e-01 1.56836498e+00 -2.29386855e-02 -3.10005605e-01 -3.66692483e-01 -9.54151690e-01 1.10809624e+00 9.03902173e-01 5.37889116e-02 -7.36630499e-01 -8.50880206e-01 5.01350939e-01 9.22295675e-02 9.40978408e-01 -1.30004156e+00 4.18940336e-01 -7.16873825e-01 4.99193281e-01 -9.07549486e-02 5.62916338e-01 -9.15685713e-01 2.30820030e-01 6.66928947e-01 -6.17595732e-01 5.14388919e-01 5.29921174e-01 3.64621699e-01 4.56782639e-01 -2.50599921e-01 5.07272184e-01 -6.52202845e-01 -1.23266912e+00 -8.51731896e-02 -7.37663686e-01 1.00828186e-01 1.30556393e+00 -4.30902570e-01 -7.97774076e-01 -6.90803528e-01 -9.59527373e-01 5.48779249e-01 9.37092781e-01 2.90605158e-01 5.75420916e-01 -9.87839818e-01 -5.29457331e-01 -5.09523042e-02 1.65156722e-01 -5.03174728e-03 1.92468420e-01 5.19747913e-01 -8.41592371e-01 2.73574024e-01 -5.88470757e-01 -2.05264926e-01 -6.43342555e-01 9.72636998e-01 5.72395086e-01 -5.92574252e-05 -9.10064876e-01 9.32725966e-01 6.30410314e-01 -5.94976127e-01 3.02905321e-01 -6.17402136e-01 -1.61771148e-01 -5.09654343e-01 5.60434759e-01 2.10802138e-01 -4.41792011e-01 -2.36657768e-01 -2.80408829e-01 2.41859496e-01 1.95040658e-01 -6.20864391e-01 1.26149154e+00 -2.05694437e-01 2.68454671e-01 2.83612549e-01 2.51712888e-01 -1.38303593e-01 -1.90806210e+00 1.67865574e-01 -3.01375706e-02 -3.13684791e-01 -3.55725706e-01 -1.38946271e+00 -3.63012820e-01 7.30736911e-01 2.89832711e-01 2.42274150e-01 7.20240414e-01 1.97328299e-01 2.17727140e-01 1.01419473e+00 7.50308156e-01 -1.00933909e+00 5.76030135e-01 6.85887277e-01 1.20691180e+00 -1.19057381e+00 -1.30274937e-01 1.56499594e-01 -1.07495320e+00 8.43662202e-01 1.10007727e+00 4.61785831e-02 -1.94501176e-01 3.51769775e-01 1.06563777e-01 -4.89233583e-01 -1.10778546e+00 -3.56989294e-01 -2.29542956e-01 1.20063269e+00 1.61535535e-02 1.42436683e-01 4.11400884e-01 3.21836799e-01 -5.68942487e-01 -1.45580709e-01 6.16959691e-01 8.58586967e-01 -7.87604451e-01 -4.47261959e-01 -3.03154886e-01 5.22871912e-02 3.22019577e-01 -3.80340079e-03 -4.06310201e-01 1.14068103e+00 -3.97263542e-02 9.21205461e-01 -4.62817550e-02 -8.29059780e-02 5.15200794e-01 8.07240680e-02 8.29049826e-01 -7.76595652e-01 -5.77789545e-01 -5.14201701e-01 2.06487119e-01 -9.05220985e-01 -4.22719792e-02 -7.55290568e-01 -1.83559299e+00 -4.12937522e-01 4.34716433e-01 -5.87750934e-02 5.45697808e-01 9.74329948e-01 2.27221891e-01 6.24147832e-01 -2.19494835e-01 -1.09617734e+00 -4.43303555e-01 -7.97377825e-01 -3.14247794e-03 5.25951862e-01 4.25746590e-01 -7.18619823e-01 -2.78740615e-01 -4.13870923e-02]	[4.2787184715271, 0.8953312039375305]
04740d3a-6a51-4e98-9888-89caf83e92c0	fully-sparse-fusion-for-3d-object-detection	2304.1231	null	https://arxiv.org/abs/2304.12310v2	https://arxiv.org/pdf/2304.12310v2.pdf	Fully Sparse Fusion for 3D Object Detection	Currently prevalent multimodal 3D detection methods are built upon LiDAR-based detectors that usually use dense Bird's-Eye-View (BEV) feature maps. However, the cost of such BEV feature maps is quadratic to the detection range, making it not suitable for long-range detection. Fully sparse architecture is gaining attention as they are highly efficient in long-range perception. In this paper, we study how to effectively leverage image modality in the emerging fully sparse architecture. Particularly, utilizing instance queries, our framework integrates the well-studied 2D instance segmentation into the LiDAR side, which is parallel to the 3D instance segmentation part in the fully sparse detector. This design achieves a uniform query-based fusion framework in both the 2D and 3D sides while maintaining the fully sparse characteristic. Extensive experiments showcase state-of-the-art results on the widely used nuScenes dataset and the long-range Argoverse 2 dataset. Notably, the inference speed of the proposed method under the long-range LiDAR perception setting is 2.7 $\times$ faster than that of other state-of-the-art multimodal 3D detection methods. Code will be released at \url{https://github.com/BraveGroup/FullySparseFusion}.	['Tieniu Tan', 'Zhaoxiang Zhang', 'Naiyan Wang', 'Yuntao Chen', 'Zehao Huang', 'Yang Liu', 'Lue Fan', 'Yingyan Li']	2023-04-24	null	null	null	null	['3d-instance-segmentation-1']	['computer-vision']	[ 1.46448851e-01 -1.47174060e-01 -1.41216338e-01 -5.21597326e-01 -1.20304024e+00 -5.51527739e-01 4.85300660e-01 5.40691987e-02 -6.27857506e-01 1.47828624e-01 -2.64800191e-01 1.97134999e-04 2.37762071e-02 -8.68503511e-01 -7.87945330e-01 -6.41186297e-01 2.78572530e-01 5.66066504e-01 5.68697393e-01 -2.11497083e-01 1.16221711e-01 5.81824243e-01 -2.08925843e+00 -7.17683658e-02 7.77264178e-01 1.28585505e+00 4.12046492e-01 5.68947196e-01 -1.41985258e-02 -1.23042725e-01 -4.95185554e-02 -3.89610499e-01 5.38048923e-01 1.91123173e-01 1.06398329e-01 1.43612042e-01 1.15516996e+00 -6.09007537e-01 -2.29481012e-01 1.18792653e+00 7.81269729e-01 -8.31465125e-02 5.39510429e-01 -1.11748505e+00 -6.71108812e-02 5.96662015e-02 -1.16109896e+00 9.18761194e-02 5.50181329e-01 9.66533199e-02 1.06770074e+00 -1.49878883e+00 4.89912361e-01 1.41386700e+00 7.35760689e-01 6.04489818e-02 -1.15970433e+00 -8.64464462e-01 1.43974304e-01 3.71963643e-02 -1.81315947e+00 -4.68613833e-01 7.01309741e-01 -3.89232397e-01 8.17457080e-01 2.04763547e-01 5.18990457e-01 9.19701159e-01 -5.32414541e-02 9.10681307e-01 1.17479324e+00 -8.58509541e-02 -1.95598789e-03 4.69213985e-02 1.19350515e-01 8.61655831e-01 3.65447640e-01 3.48694146e-01 -8.45136404e-01 -1.34879485e-01 5.97325861e-01 2.08557785e-01 -4.95479442e-02 -6.63997650e-01 -9.60699677e-01 8.55139017e-01 7.87034392e-01 -1.87678754e-01 -2.43921086e-01 1.35684177e-01 7.76662603e-02 -1.70912936e-01 5.76158404e-01 -2.24849507e-01 -1.89978659e-01 2.00123399e-01 -1.04665482e+00 3.66767019e-01 3.62486392e-01 1.15697968e+00 1.15140831e+00 -2.68563956e-01 1.57429057e-03 7.23368466e-01 5.50101936e-01 1.08919954e+00 -2.67856598e-01 -1.04534566e+00 4.71933782e-01 7.98765421e-01 4.83471602e-02 -8.06594193e-01 -4.04988468e-01 -6.13420010e-01 -7.68208385e-01 2.63808727e-01 2.36697510e-01 8.59515965e-02 -1.02873886e+00 1.28852236e+00 7.99470246e-01 -4.83522899e-02 -2.03932062e-01 1.19014955e+00 9.11472678e-01 3.85439336e-01 -3.04957390e-01 5.53979054e-02 1.57261097e+00 -5.46257257e-01 -2.85349041e-01 -5.15517771e-01 1.78018749e-01 -8.38015258e-01 7.82074034e-01 3.35027874e-01 -9.98010933e-01 -6.96261108e-01 -9.72794354e-01 -4.32980716e-01 -3.67614359e-01 3.84902418e-01 5.19189417e-01 5.77394426e-01 -9.19815183e-01 -8.45361128e-02 -7.65471041e-01 -5.82790136e-01 5.43361068e-01 1.75118044e-01 -3.48447174e-01 -5.10424435e-01 -7.71064043e-01 6.73039436e-01 3.00984770e-01 2.50965118e-01 -9.02388275e-01 -5.90972662e-01 -1.11626077e+00 -2.88805855e-03 9.14716005e-01 -9.30137634e-01 1.06184387e+00 1.77276924e-01 -8.40958655e-01 1.17146885e+00 -4.11446959e-01 -3.76687914e-01 5.80205321e-01 -4.21384811e-01 9.58541483e-02 1.88897967e-01 4.31107432e-01 1.00192249e+00 9.55766082e-01 -1.38608611e+00 -1.00275636e+00 -9.41998243e-01 6.39055744e-02 3.38317692e-01 8.67367536e-02 -4.16989565e-01 -7.74719119e-01 -2.18451440e-01 6.16656721e-01 -1.01303184e+00 -1.77093327e-01 4.46678489e-01 -5.39714515e-01 -3.33864808e-01 7.66362429e-01 -7.02828765e-02 8.16605687e-01 -2.32624698e+00 1.24378512e-02 4.49958667e-02 2.32769087e-01 -6.34372681e-02 6.79752752e-02 5.28421044e-01 4.79311705e-01 -3.09816271e-01 -3.76501054e-01 -7.22072482e-01 1.51490763e-01 2.06232458e-01 -1.85372844e-01 7.36082733e-01 5.43108247e-02 7.72892535e-01 -7.73847103e-01 -5.55361807e-01 5.29428899e-01 5.73192656e-01 -5.58907509e-01 2.55103290e-01 -6.67495057e-02 2.80350715e-01 -5.72430432e-01 1.20841646e+00 1.23179913e+00 -9.11773443e-02 -3.20310026e-01 -5.14348686e-01 -5.64687908e-01 -8.23992863e-02 -1.23582876e+00 2.16002107e+00 -2.49674350e-01 3.30258667e-01 5.62890768e-01 -6.41581476e-01 9.55153048e-01 -2.75628060e-01 2.47271001e-01 -6.34320319e-01 4.55351993e-02 4.62533295e-01 -3.53290528e-01 -1.95592821e-01 6.50408208e-01 -7.65076056e-02 -2.04366878e-01 -1.20245172e-02 6.65747821e-02 -6.53265595e-01 2.51709521e-01 3.29872400e-01 7.66162753e-01 2.24145234e-01 3.62358630e-01 1.20848250e-02 4.18250442e-01 -3.21828462e-02 3.87714863e-01 9.96650636e-01 -1.08655490e-01 7.29497612e-01 1.12085149e-01 1.56550780e-02 -5.98020375e-01 -1.36268926e+00 -5.11541367e-01 9.55477297e-01 4.81337577e-01 -4.20109212e-01 -3.68968695e-01 -5.55380523e-01 4.97725964e-01 4.86528307e-01 -3.92621189e-01 3.34337950e-01 -2.21132487e-01 -5.10668218e-01 5.29905498e-01 4.15471226e-01 6.26353443e-01 -2.45868176e-01 -9.90795553e-01 -1.19479030e-01 4.74567199e-03 -1.44435334e+00 -2.31302097e-01 1.93760559e-01 -6.23050928e-01 -1.08573258e+00 -6.04696870e-01 -2.41889492e-01 3.54412019e-01 8.78123403e-01 7.94732392e-01 -3.06860864e-01 -5.02532363e-01 6.81336284e-01 -1.98820665e-01 -4.38672841e-01 3.24727803e-01 -4.93993890e-03 1.15375675e-01 -4.36516479e-02 4.30073351e-01 -5.56891263e-01 -8.09451520e-01 3.97914290e-01 -6.88655853e-01 -1.31981030e-01 8.20323467e-01 6.28808856e-01 1.05036187e+00 -3.63027483e-01 7.39100650e-02 -5.35017550e-01 -6.87953979e-02 -3.89661610e-01 -9.34213042e-01 -6.01148903e-02 -5.38009584e-01 -2.79840440e-01 -1.62145764e-01 1.16838068e-01 -8.62859786e-01 5.35179257e-01 -2.50363767e-01 -6.10281467e-01 -2.99790412e-01 2.09659219e-01 -1.73283443e-01 -1.99805290e-01 5.02345741e-01 3.54743332e-01 1.22436481e-02 -6.30989909e-01 4.65172321e-01 6.49345279e-01 5.64260840e-01 -3.59600753e-01 1.14940822e+00 1.05948818e+00 2.88675100e-01 -1.14111948e+00 -1.14437628e+00 -1.02987099e+00 -7.03111529e-01 -2.30838791e-01 7.60952890e-01 -1.46582317e+00 -8.14489603e-01 3.40063453e-01 -1.11665654e+00 2.00044468e-01 -2.09456414e-01 3.57309490e-01 -3.15378934e-01 3.80829543e-01 -9.82462242e-02 -1.22213566e+00 -2.46576920e-01 -1.22769845e+00 2.07188034e+00 2.58710682e-01 2.83055454e-01 -3.87540132e-01 -8.80351439e-02 6.24918401e-01 1.58548057e-01 2.41057485e-01 2.50546575e-01 -2.30275631e-01 -9.40608025e-01 -3.79240155e-01 -7.57065833e-01 1.79133222e-01 -3.74561429e-01 -3.04682523e-01 -1.34242809e+00 -3.32521379e-01 -1.00576349e-01 -3.88702869e-01 1.32843316e+00 3.41685295e-01 7.92440534e-01 4.60076451e-01 -5.53842485e-01 6.61992371e-01 1.38893068e+00 -3.65320474e-01 2.08478615e-01 -2.23393664e-01 8.11988652e-01 6.76080525e-01 1.11636734e+00 6.05896413e-01 7.66552925e-01 8.61383736e-01 9.43151653e-01 -1.20663932e-02 -2.13224605e-01 -4.15647835e-01 2.39451766e-01 2.74365336e-01 -3.86792757e-02 -1.53775036e-01 -9.69357550e-01 3.19738418e-01 -1.84322739e+00 -8.21254909e-01 -3.90934199e-01 2.08781266e+00 2.59854853e-01 1.42389089e-01 -6.83491351e-03 -1.01236803e-02 5.49291670e-01 4.02335346e-01 -6.63350105e-01 2.33409956e-01 -2.82090694e-01 1.83217153e-02 7.55504906e-01 4.20353234e-01 -1.15111959e+00 8.33757162e-01 5.02402687e+00 9.63037729e-01 -7.62621403e-01 3.20955515e-01 1.01552613e-01 -3.50379288e-01 -2.03160316e-01 9.04934704e-02 -1.50760710e+00 1.30123302e-01 3.82665366e-01 1.65758282e-01 4.95154411e-02 7.98565984e-01 2.60787219e-01 -6.87745035e-01 -1.00371397e+00 1.37261498e+00 2.19430372e-01 -1.06716025e+00 -1.79952025e-01 3.90791625e-01 2.71905065e-01 4.86793011e-01 1.09323554e-01 2.20811874e-01 -3.04457098e-01 -7.76712298e-01 8.97792697e-01 3.45646679e-01 1.04470646e+00 -5.96295536e-01 5.32579780e-01 7.29893029e-01 -1.51729107e+00 -4.20994721e-02 -4.26485151e-01 4.16466333e-02 4.57497537e-01 1.00838554e+00 -7.31741011e-01 7.18849897e-01 1.03448951e+00 8.56980860e-01 -8.01447213e-01 9.44344401e-01 -2.21697345e-01 1.22575551e-01 -9.13727164e-01 2.69256413e-01 3.30659986e-01 -2.44846538e-01 9.33255792e-01 1.18995225e+00 6.24743342e-01 7.74118677e-02 5.07106841e-01 8.27292025e-01 -1.52911574e-01 -2.27825493e-01 -8.90062630e-01 3.88066441e-01 5.31987190e-01 1.33855808e+00 -4.85587686e-01 -1.09684147e-01 -4.77102309e-01 6.79787695e-01 2.31649652e-01 8.97820368e-02 -7.81082988e-01 -1.05732739e-01 6.10536098e-01 4.32514906e-01 7.15882242e-01 -4.40492004e-01 -1.59790695e-01 -1.07224822e+00 2.62735486e-01 -3.22438627e-01 3.36881518e-01 -7.65769482e-01 -1.37763536e+00 2.14297801e-01 1.82388380e-01 -1.25053751e+00 2.29293592e-02 -5.54680943e-01 -2.11957604e-01 7.34576464e-01 -1.86746001e+00 -1.62430334e+00 -6.30789876e-01 6.56031191e-01 5.45331538e-01 1.82818204e-01 5.34934223e-01 4.95238572e-01 -3.67763132e-01 3.28943163e-01 -2.29553521e-01 -2.71442086e-01 7.01024652e-01 -1.05877423e+00 8.62548426e-02 8.44858587e-01 2.80454397e-01 3.54904681e-01 5.06743371e-01 -5.86051941e-01 -1.92304087e+00 -9.29994345e-01 5.10186315e-01 -4.65513974e-01 4.48304445e-01 -6.31958008e-01 -6.00354433e-01 3.16091269e-01 -2.51168124e-02 2.45397061e-01 4.71480131e-01 9.13852230e-02 -5.43900192e-01 -3.68163437e-01 -1.16284108e+00 1.38241500e-01 1.40125740e+00 -5.60647130e-01 -3.76929969e-01 2.37818494e-01 3.94086719e-01 -6.67530715e-01 -6.36024833e-01 7.68340349e-01 7.12464094e-01 -1.38571703e+00 1.31704664e+00 3.77378404e-01 4.88848537e-02 -6.44310653e-01 -6.82014167e-01 -7.08085358e-01 8.75247791e-02 -3.06932718e-01 -2.70934761e-01 1.12432098e+00 6.37583435e-02 -6.17645502e-01 7.37573922e-01 -2.02710833e-02 -1.79274023e-01 -6.54182911e-01 -1.34103942e+00 -6.48057044e-01 -4.91426468e-01 -7.46730149e-01 1.79615185e-01 3.76473308e-01 -7.56638646e-01 6.10715568e-01 -1.75427333e-01 5.91398776e-01 1.22456348e+00 5.49848795e-01 1.04204226e+00 -1.28209472e+00 -1.60415381e-01 -1.90283015e-01 -4.97202367e-01 -1.53824258e+00 -1.03375465e-01 -8.79787982e-01 9.96420085e-02 -1.43542683e+00 2.90399760e-01 -3.20618033e-01 2.29780059e-02 1.76990613e-01 -8.52295905e-02 5.58727026e-01 3.34865451e-01 1.41526684e-01 -7.00456858e-01 7.44287789e-01 9.99117911e-01 -1.30690187e-02 8.89958367e-02 6.69495761e-02 -4.89688128e-01 8.12089801e-01 4.90545005e-01 -4.40968394e-01 -1.85557842e-01 -5.80129206e-01 2.74736345e-01 8.48579258e-02 7.95147479e-01 -1.05448973e+00 5.25965393e-01 1.28369510e-01 3.61293554e-01 -1.46250880e+00 1.04677856e+00 -8.35835993e-01 -9.25388932e-02 2.90926367e-01 1.83861345e-01 -1.84277460e-01 8.85444209e-02 9.60238516e-01 -2.65177399e-01 6.30235299e-02 9.05106843e-01 -1.16628245e-01 -8.45125973e-01 5.24667144e-01 1.33748248e-01 -5.68682775e-02 1.06126773e+00 -3.40704232e-01 -2.60680795e-01 -1.89707771e-01 -3.95958006e-01 5.05038202e-01 6.16909027e-01 2.06414834e-01 9.78683293e-01 -1.05446565e+00 -7.69566298e-01 1.99816123e-01 5.19721508e-01 5.70315301e-01 4.72035289e-01 1.21669590e+00 -8.93206298e-02 3.65936995e-01 2.49816984e-01 -1.31587040e+00 -1.26375926e+00 3.39744568e-01 5.94408549e-02 9.15252268e-02 -5.16667962e-01 9.47139561e-01 4.16094601e-01 -5.98635912e-01 1.37898818e-01 -1.95299730e-01 1.38901368e-01 4.58893627e-01 3.56125861e-01 4.99382794e-01 -3.21185663e-02 -7.85523057e-01 -7.15569139e-01 1.10275507e+00 1.62215173e-01 -1.05426684e-01 1.18415928e+00 -3.16898346e-01 5.97704835e-02 4.05815274e-01 1.05382216e+00 2.23678336e-01 -1.33054793e+00 -2.59883761e-01 -3.64665627e-01 -7.04318285e-01 2.39460856e-01 -3.86735588e-01 -8.93503845e-01 1.19728935e+00 8.60587955e-01 7.64229521e-02 9.98383284e-01 3.43342900e-01 7.23017514e-01 3.45862150e-01 7.04320431e-01 -7.32823431e-01 -1.36927202e-01 5.41068614e-01 8.10156167e-01 -1.70448816e+00 3.48205149e-01 -8.40166450e-01 -3.46072167e-01 8.34661186e-01 5.00068128e-01 -1.79462686e-01 6.11323476e-01 2.29238003e-01 -2.11575806e-01 -5.35999537e-01 -3.91957164e-01 -8.35996032e-01 3.49472404e-01 5.20964742e-01 9.55502614e-02 9.78504270e-02 -1.28633901e-02 1.40585661e-01 -3.76221980e-03 -3.18676144e-01 1.65310040e-01 9.22770739e-01 -6.16168797e-01 -8.12402248e-01 -5.55423141e-01 4.01268184e-01 5.42758033e-02 -4.82384637e-02 -2.24352941e-01 9.07241464e-01 4.32267517e-01 9.85889733e-01 -1.51412003e-02 -2.15601057e-01 6.34526908e-01 -1.81802377e-01 6.67474806e-01 -8.46475899e-01 -2.55358189e-01 3.78372192e-01 -5.95755056e-02 -1.02682006e+00 -5.48972905e-01 -8.34300458e-01 -1.11137581e+00 -1.22195788e-01 -3.72185886e-01 -3.10343802e-01 8.45280051e-01 5.95309913e-01 5.49386203e-01 -6.72094822e-02 4.55070019e-01 -1.34355831e+00 -6.42837107e-01 -7.79569864e-01 -6.13156497e-01 -5.36096506e-02 4.19145584e-01 -1.04636192e+00 -3.75287205e-01 -4.53429699e-01]	[7.786181926727295, -2.603565216064453]
bab385e5-ba3e-4169-8dbc-c153fde224a5	dynamic-context-sensitive-filtering-network	null	null	http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html	http://openaccess.thecvf.com//content/ICCV2021/papers/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.pdf	Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection	The ability to capture inter-frame dynamics has been critical to the development of video salient object detection (VSOD). While many works have achieved great success in this field, a deeper insight into its dynamic nature should be developed. In this work, we aim to answer the following questions: How can a model adjust itself to dynamic variations as well as perceive fine differences in the real-world environment; How are the temporal dynamics well introduced into spatial information over time? To this end, we propose a dynamic context-sensitive filtering network (DCFNet) equipped with a dynamic context-sensitive filtering module (DCFM) and an effective bidirectional dynamic fusion strategy. The proposed DCFM sheds new light on dynamic filter generation by extracting location-related affinities between consecutive frames. Our bidirectional dynamic fusion strategy encourages the interaction of spatial and temporal information in a dynamic manner. Experimental results demonstrate that our proposed method can achieve state-of-the-art performance on most VSOD datasets while ensuring a real-time speed of 28 fps. The source code is publicly available at https://github.com/OIPLab-DUT/DCFNet.	['Zhongxuan Luo', 'Huchuan Lu', 'Jingjing Li', 'Wei Ji', 'Shunyu Yao', 'Yongri Piao', 'Yifei Wang', 'Jie Liu', 'Miao Zhang']	2021-01-01	null	null	null	iccv-2021-1	['video-salient-object-detection', 'video-polyp-segmentation']	['computer-vision', 'computer-vision']	[ 2.50541300e-01 -5.37208974e-01 -9.76144299e-02 -3.65324944e-01 -2.61576891e-01 -4.61741865e-01 5.48657358e-01 -4.14566956e-02 -3.93990546e-01 5.10262191e-01 2.95962095e-01 1.45669088e-01 -1.51558191e-01 -6.95299149e-01 -6.20339632e-01 -6.95749938e-01 -1.22899614e-01 -1.87540710e-01 1.11050189e+00 -5.32705903e-01 1.83527574e-01 5.55511892e-01 -1.93290186e+00 2.65926301e-01 7.81940818e-01 1.08352566e+00 6.88115835e-01 7.33505249e-01 2.76307076e-01 9.05394316e-01 -2.35337585e-01 -1.46612763e-01 3.01621020e-01 -2.84840047e-01 -5.72028279e-01 -5.94085036e-03 4.46300268e-01 -1.68411419e-01 -4.08204615e-01 1.12049890e+00 5.29403329e-01 4.24341917e-01 -1.73711067e-03 -1.15811718e+00 -4.49795663e-01 5.60271323e-01 -4.84314650e-01 9.76828814e-01 3.55164111e-01 2.54723907e-01 7.91682065e-01 -9.67499018e-01 7.37785101e-01 1.20950699e+00 2.69547641e-01 4.59169120e-01 -1.13739347e+00 -4.79095399e-01 5.50664246e-01 6.55824602e-01 -1.09101689e+00 -4.41543847e-01 1.06982303e+00 -3.83984238e-01 5.26638508e-01 3.51241946e-01 9.88770366e-01 1.04152918e+00 3.12928200e-01 8.80641341e-01 9.13116455e-01 -2.44784519e-01 1.59115225e-01 -1.91782966e-01 -1.19671375e-02 5.01126707e-01 1.39865905e-01 3.24429959e-01 -1.01324677e+00 2.37473026e-01 7.81137466e-01 1.25077635e-01 -5.23210108e-01 -5.23891270e-01 -1.24644971e+00 5.23330629e-01 4.83830780e-01 4.25313175e-01 -2.83580303e-01 6.35408461e-02 3.26587051e-01 1.41697511e-01 3.59317631e-01 1.23966083e-01 -2.07403883e-01 -4.25559014e-01 -7.65564620e-01 3.08397740e-01 2.99995631e-01 8.04906368e-01 5.03105581e-01 -1.89690068e-02 -2.20399022e-01 5.41987181e-01 6.61486760e-02 4.61663783e-01 3.53396416e-01 -1.01195943e+00 2.80970961e-01 4.26512957e-01 2.80095577e-01 -1.42082620e+00 -4.93816763e-01 -3.06026459e-01 -5.65855861e-01 1.87779814e-01 4.35809642e-01 -4.45507802e-02 -5.30864477e-01 1.80260658e+00 6.06244326e-01 4.82778996e-01 -3.51123810e-01 1.35340989e+00 6.13883913e-01 5.52220285e-01 1.62549898e-01 -2.41015539e-01 1.22520387e+00 -9.02638078e-01 -8.18775415e-01 -2.63029575e-01 1.23590447e-01 -9.22375917e-01 9.06559765e-01 1.24513850e-01 -1.20722246e+00 -8.81664932e-01 -9.48536277e-01 -8.15476254e-02 -2.91965514e-01 -1.67006925e-01 5.26818573e-01 2.88442731e-01 -1.02700496e+00 2.66711235e-01 -1.03541088e+00 -4.66708928e-01 2.60731339e-01 2.54759490e-01 -1.58788741e-01 -1.53253367e-02 -1.26520360e+00 7.19934106e-01 4.11978364e-01 2.15086386e-01 -6.40032530e-01 -5.52987337e-01 -5.95259547e-01 -1.14712700e-01 7.90794313e-01 -7.29840279e-01 1.17954648e+00 -1.16590226e+00 -1.25039935e+00 4.55912858e-01 -2.87420392e-01 -5.15639901e-01 5.98916233e-01 -2.58082390e-01 -5.71800947e-01 3.53973538e-01 4.74714711e-02 6.15419507e-01 8.16608906e-01 -1.19324303e+00 -1.16646838e+00 -3.29487473e-01 2.80088991e-01 3.22749674e-01 -3.41262817e-01 1.59407079e-01 -6.53368175e-01 -9.50919628e-01 1.26133766e-02 -1.00371027e+00 1.85997225e-02 3.21473122e-01 3.13611403e-02 4.94041387e-03 1.16830897e+00 -3.34117651e-01 1.47823131e+00 -2.23103499e+00 3.60000342e-01 -1.42889544e-01 2.02892452e-01 5.55920720e-01 2.47373823e-02 3.45367014e-01 2.39137918e-01 -4.06319827e-01 -9.25968364e-02 -1.16804093e-01 -2.99501151e-01 -1.70895699e-02 -2.86775321e-01 3.74839246e-01 1.84946269e-01 8.43579173e-01 -1.31418085e+00 -4.72173095e-01 6.07220590e-01 7.71960557e-01 -4.62053955e-01 8.72233808e-02 -1.66044742e-01 4.13210064e-01 -4.82401848e-01 7.48922706e-01 6.93509102e-01 -2.50577331e-01 6.08550832e-02 -3.62988919e-01 -3.84590268e-01 -1.95103407e-01 -1.34386265e+00 1.59862256e+00 4.74484786e-02 8.21023524e-01 1.63138300e-01 -7.00947285e-01 7.75550008e-01 -5.75453937e-02 6.35517716e-01 -9.44167316e-01 1.93635151e-01 2.62437612e-02 -3.07941567e-02 -4.30091888e-01 8.08232784e-01 1.45976946e-01 3.28581065e-01 -5.04591540e-02 -1.41534463e-01 3.46654445e-01 3.26759607e-01 1.74771503e-01 8.70107532e-01 2.77716100e-01 1.88841701e-01 -3.29893708e-01 7.29182601e-01 -7.22284988e-02 9.08980906e-01 5.87745190e-01 -6.07416511e-01 5.85590482e-01 7.68423378e-02 -6.70918524e-01 -7.36097932e-01 -1.02840602e+00 -9.27266702e-02 1.22167838e+00 9.21577573e-01 -4.15836424e-01 -6.25602901e-01 -3.46244484e-01 -3.84716839e-02 2.59292662e-01 -7.44423568e-01 -2.08341107e-01 -6.70329571e-01 -6.17964566e-01 7.48222023e-02 5.74098349e-01 7.78437972e-01 -9.35801327e-01 -1.21381068e+00 4.30094481e-01 -3.98766667e-01 -1.26801002e+00 -6.87599182e-01 -1.59011140e-01 -6.88446641e-01 -1.07529891e+00 -5.69030225e-01 -7.39636242e-01 2.69372463e-01 8.42395306e-01 1.00292492e+00 2.62772827e-03 -2.15984538e-01 3.17326039e-01 -5.74215531e-01 -2.79665172e-01 3.69928889e-02 -5.33620939e-02 1.36576230e-02 2.96630591e-01 3.85866880e-01 -5.65351069e-01 -1.01070762e+00 6.79841995e-01 -1.04988205e+00 3.81138235e-01 1.86039612e-01 6.62993670e-01 7.19876647e-01 1.36793675e-02 3.73997837e-01 -5.24776220e-01 3.95704836e-01 -2.97770321e-01 -7.07869530e-01 1.02532968e-01 -3.79200459e-01 -3.31635267e-01 4.77006644e-01 -5.70962131e-01 -1.33049989e+00 6.63900748e-02 -2.99984813e-02 -3.99586082e-01 4.87606376e-02 2.18253493e-01 -6.10171519e-02 -1.96795240e-01 4.86610681e-01 1.91924050e-01 -1.50625437e-01 -2.81048208e-01 3.17880541e-01 3.40031296e-01 7.10009217e-01 -5.00072062e-01 6.82863116e-01 9.78008151e-01 -1.16528779e-01 -6.16253555e-01 -8.30501378e-01 -6.58458292e-01 -6.14405334e-01 -6.14172935e-01 8.60349059e-01 -9.14784253e-01 -5.42792678e-01 6.32076442e-01 -8.31545115e-01 -4.44963515e-01 -2.83266932e-01 3.10004473e-01 -5.15197992e-01 3.09108853e-01 -4.49224144e-01 -5.85924089e-01 -2.16964662e-01 -1.21133816e+00 1.03509629e+00 5.43627083e-01 8.42682123e-02 -9.12684500e-01 -9.01300274e-03 2.32385978e-01 4.64832067e-01 3.50671321e-01 1.17845550e-01 4.04477958e-03 -8.92790616e-01 2.29405761e-01 -2.29873717e-01 9.70371366e-02 2.26323277e-01 1.91104606e-01 -8.06871712e-01 -3.40961218e-01 -4.72872816e-02 1.57161385e-01 8.45216095e-01 6.58152282e-01 9.36746180e-01 6.64973864e-04 -2.82819211e-01 7.16400027e-01 1.36848307e+00 3.06399733e-01 4.66516554e-01 5.29522777e-01 6.53643668e-01 5.72080851e-01 1.05445206e+00 6.31581903e-01 4.19049978e-01 1.09714103e+00 5.75414300e-01 -7.31482282e-02 -3.18908155e-01 -2.02202857e-01 2.14495614e-01 6.05038941e-01 -2.42996871e-01 -3.07668149e-01 -7.29329944e-01 6.29061699e-01 -2.28309870e+00 -1.34556448e+00 -6.73720166e-02 1.96449983e+00 5.95169246e-01 2.59029746e-01 2.77848542e-01 7.51705915e-02 8.25686276e-01 4.54149812e-01 -5.31120241e-01 1.03519633e-02 -4.92774516e-01 -4.13783222e-01 2.97771156e-01 5.25456429e-01 -1.21196866e+00 8.69102776e-01 5.36982155e+00 7.31981039e-01 -1.48462391e+00 6.64612874e-02 5.16638577e-01 -2.82551229e-01 -1.11431211e-01 -6.64195344e-02 -7.00045109e-01 8.29101503e-01 5.18971562e-01 -2.57163346e-01 3.77360374e-01 6.62989318e-01 6.10060990e-01 -2.75367469e-01 -5.93224168e-01 9.97281432e-01 -2.94674542e-02 -1.58863509e+00 -1.19231082e-01 -1.43426165e-01 7.12818384e-01 1.63591892e-01 7.82326013e-02 -2.33320624e-01 -4.69698980e-02 -4.35914338e-01 1.15952504e+00 7.01741457e-01 4.24454391e-01 -6.67810023e-01 5.59067309e-01 2.08031163e-01 -1.63802111e+00 -3.26183617e-01 -1.94830909e-01 -1.11013331e-01 3.51824313e-01 6.47831917e-01 -2.80679762e-01 4.41135973e-01 1.09502459e+00 1.03768480e+00 -6.58099532e-01 1.14428985e+00 1.15508381e-02 4.30431843e-01 -3.07692230e-01 3.19366194e-02 1.49502844e-01 -6.41144365e-02 9.71133292e-01 1.29026079e+00 5.86206764e-02 1.77856162e-01 1.13257430e-01 4.98605579e-01 3.03841919e-01 -8.64861161e-02 -2.20005244e-01 2.57964373e-01 5.28899550e-01 1.25234330e+00 -8.91866565e-01 -2.69123912e-01 -3.99500668e-01 8.02251577e-01 1.57905012e-01 3.29468489e-01 -9.99318123e-01 -1.69770308e-02 8.04816127e-01 3.49594414e-01 4.80633080e-01 -2.58224040e-01 1.52140902e-03 -1.32511878e+00 2.12305024e-01 -6.71827793e-01 5.92173576e-01 -8.78701210e-01 -9.99518871e-01 6.01195633e-01 3.38733234e-02 -1.40483952e+00 1.71156734e-01 -2.90853113e-01 -4.58338886e-01 4.64607894e-01 -1.67144537e+00 -1.05145347e+00 -6.95266187e-01 7.94238210e-01 7.62693226e-01 9.47189406e-02 1.90020502e-01 4.20410872e-01 -4.39458430e-01 2.70860463e-01 -1.29763791e-02 -8.95131379e-02 7.24763215e-01 -8.49514306e-01 1.48599446e-01 1.31569207e+00 2.22630110e-02 4.01970655e-01 9.03670371e-01 -5.53306758e-01 -1.35743284e+00 -1.03481543e+00 5.93096256e-01 -3.40925366e-01 6.11832738e-01 -2.35164076e-01 -9.35868621e-01 3.03213984e-01 2.19363142e-02 4.81754154e-01 2.30991572e-01 -3.49549830e-01 -2.34190673e-02 -3.42131644e-01 -9.94758606e-01 5.79865098e-01 1.34993017e+00 -3.24012876e-01 -3.01591933e-01 -9.48507711e-02 8.07131171e-01 -5.78682661e-01 -6.72987580e-01 5.62556624e-01 6.22765839e-01 -1.38212502e+00 9.68346477e-01 -1.06943429e-01 1.79219782e-01 -8.31811488e-01 -1.76753834e-01 -8.38421822e-01 -5.12695134e-01 -7.11690843e-01 -4.35612679e-01 1.04436684e+00 -1.78943574e-01 -5.10704339e-01 6.02183878e-01 4.37599748e-01 -5.96589036e-02 -1.02811182e+00 -9.73633707e-01 -5.69877684e-01 -5.87638021e-01 -4.69924778e-01 5.19856155e-01 8.04061651e-01 -1.24519892e-01 -1.03500679e-01 -4.00265157e-01 2.51187086e-01 5.07996500e-01 1.98578879e-01 5.58323264e-01 -1.09732032e+00 -7.70995021e-02 -3.91961187e-01 -7.32243478e-01 -1.09383583e+00 -2.33630583e-01 -2.38535166e-01 -1.39488846e-01 -1.25271916e+00 2.51787901e-01 -2.58648127e-01 -4.71879482e-01 1.96717575e-01 -4.31005299e-01 4.16156799e-01 4.80856568e-01 2.22619697e-01 -8.77587199e-01 6.48875952e-01 1.38429511e+00 1.02503635e-01 -2.41394103e-01 -1.50918230e-01 -5.80422342e-01 5.96441746e-01 8.22799444e-01 -1.53511330e-01 -5.81953108e-01 -4.25009280e-01 5.84737025e-02 -3.78054678e-02 5.51862717e-01 -1.20383966e+00 3.80044460e-01 -4.13421363e-01 2.65428871e-01 -6.30750358e-01 3.70499462e-01 -8.90566468e-01 2.27562025e-01 2.42599100e-01 -1.09554470e-01 3.57044995e-01 2.67142922e-01 7.71784842e-01 -4.19888884e-01 3.63613039e-01 9.54492211e-01 6.27766103e-02 -1.31933594e+00 3.51850629e-01 -3.17747146e-01 -2.24882178e-02 1.17438769e+00 -5.06644189e-01 -3.77680212e-01 -2.89259136e-01 -4.95181829e-01 2.72480965e-01 7.90125132e-01 7.95560360e-01 6.51734352e-01 -1.26424086e+00 -3.61240119e-01 1.75229669e-01 8.54597688e-02 -1.72134414e-01 6.06209517e-01 9.81974483e-01 -4.01907235e-01 2.33677894e-01 -2.89983034e-01 -7.49022365e-01 -1.35550714e+00 5.52905619e-01 4.50683624e-01 6.58954531e-02 -7.19635129e-01 8.52202654e-01 1.77990466e-01 2.57719845e-01 1.86912566e-01 -2.42108047e-01 -2.66569555e-01 1.62042692e-01 6.47653580e-01 3.94245118e-01 -1.81849003e-01 -1.01208162e+00 -4.34067488e-01 6.37770295e-01 3.04383300e-02 7.40055814e-02 1.19768763e+00 -6.26965165e-01 1.95787951e-01 3.30887884e-01 8.81963432e-01 -1.83571372e-02 -1.84215510e+00 -3.23413283e-01 -1.95840642e-01 -9.08019602e-01 2.35335559e-01 -6.12704277e-01 -1.21253359e+00 4.45822686e-01 8.70765150e-01 2.14339659e-01 1.48877001e+00 -9.49893221e-02 9.07945931e-01 -5.70596419e-02 4.56262439e-01 -1.22982049e+00 1.48275048e-01 3.30193818e-01 7.31534958e-01 -1.25478387e+00 -1.15333032e-02 -6.59865141e-01 -6.35004818e-01 1.01149881e+00 6.55690491e-01 -5.74868433e-02 6.81626320e-01 2.82127291e-01 4.86510992e-02 -1.09064035e-01 -7.77978778e-01 -3.51719439e-01 3.68613243e-01 5.25869727e-01 2.18113303e-01 -1.50237679e-01 -2.15973258e-01 1.35305613e-01 7.21940249e-02 1.40442431e-01 3.69555414e-01 1.08868968e+00 -4.82396305e-01 -8.20744514e-01 -2.55254298e-01 5.29157072e-02 -3.45807642e-01 2.68496364e-01 -9.78238881e-02 6.08628631e-01 3.56419802e-01 9.82911766e-01 7.96573982e-02 -3.99270743e-01 3.69420290e-01 -4.61108863e-01 2.72574663e-01 -2.32015759e-01 -4.17772144e-01 2.40340248e-01 -1.25592723e-01 -9.28331316e-01 -9.45629716e-01 -8.78142536e-01 -1.14347148e+00 -2.85351425e-01 -2.01698691e-01 -1.42956838e-01 3.17478091e-01 6.17579460e-01 5.89534879e-01 5.67820966e-01 4.12634760e-01 -9.82854903e-01 9.40086469e-02 -5.31478167e-01 -2.83497095e-01 5.54415584e-01 6.28741026e-01 -9.83427763e-01 -2.55782515e-01 2.84962058e-01]	[9.418055534362793, -0.4368710219860077]
f6f84f09-297b-4e37-922f-5d0a47b1262b	video-colorization-with-pre-trained-text-to	2306.01732	null	https://arxiv.org/abs/2306.01732v1	https://arxiv.org/pdf/2306.01732v1.pdf	Video Colorization with Pre-trained Text-to-Image Diffusion Models	Video colorization is a challenging task that involves inferring plausible and temporally consistent colors for grayscale frames. In this paper, we present ColorDiffuser, an adaptation of a pre-trained text-to-image latent diffusion model for video colorization. With the proposed adapter-based approach, we repropose the pre-trained text-to-image model to accept input grayscale video frames, with the optional text description, for video colorization. To enhance the temporal coherence and maintain the vividness of colorization across frames, we propose two novel techniques: the Color Propagation Attention and Alternated Sampling Strategy. Color Propagation Attention enables the model to refine its colorization decision based on a reference latent frame, while Alternated Sampling Strategy captures spatiotemporal dependencies by using the next and previous adjacent latent frames alternatively as reference during the generative diffusion sampling steps. This encourages bidirectional color information propagation between adjacent video frames, leading to improved color consistency across frames. We conduct extensive experiments on benchmark datasets, and the results demonstrate the effectiveness of our proposed framework. The evaluations show that ColorDiffuser achieves state-of-the-art performance in video colorization, surpassing existing methods in terms of color fidelity, temporal consistency, and visual quality.	['Tien-Tsin Wong', 'Chengze Li', 'Jinbo Xing', 'Minshan Xie', 'Hanyuan Liu']	2023-06-02	null	null	null	null	['colorization']	['computer-vision']	[ 2.73702681e-01 -5.10717571e-01 -1.07119143e-01 -1.18035920e-01 -4.20546383e-01 -5.31677306e-01 6.21676385e-01 -4.91601914e-01 -3.23774129e-01 6.56064212e-01 1.98638842e-01 -2.14460567e-01 2.23113894e-01 -5.08901954e-01 -7.35244215e-01 -9.67560828e-01 2.28513017e-01 -2.66209573e-01 3.11425209e-01 2.19560832e-01 3.65140736e-01 3.38765770e-01 -1.32061744e+00 3.98873985e-01 9.39363003e-01 8.37839127e-01 2.30837390e-01 8.56386840e-01 -2.31972352e-01 9.18896198e-01 -3.15789729e-01 -2.32410759e-01 2.37491593e-01 -7.57121503e-01 -6.23883724e-01 3.60110492e-01 5.47519982e-01 -7.27763832e-01 -2.49702170e-01 1.13031507e+00 9.43003073e-02 4.02878016e-01 4.32989568e-01 -1.42562270e+00 -1.40328443e+00 3.09107810e-01 -1.01713765e+00 1.81543320e-01 3.46688837e-01 3.71000975e-01 6.41012847e-01 -9.79838192e-01 6.45672321e-01 1.51388836e+00 1.56880334e-01 5.91351926e-01 -1.36343920e+00 -7.15394258e-01 8.17300260e-01 3.44197124e-01 -1.32870114e+00 -4.74792719e-01 9.25335824e-01 -3.68635386e-01 4.47811127e-01 2.71094769e-01 8.78494978e-01 8.02843094e-01 1.96288317e-01 7.92095661e-01 1.17356551e+00 -3.65212053e-01 2.98070788e-01 -1.94781736e-01 -2.09234834e-01 9.45988059e-01 3.65628265e-02 1.43743604e-01 -6.35824502e-01 -5.11561781e-02 1.15775120e+00 2.87712812e-01 -5.24097085e-01 -2.63905019e-01 -1.31764054e+00 3.86390060e-01 3.48160028e-01 1.01501651e-01 -5.16125083e-01 5.02386391e-01 4.25263820e-03 -3.46982777e-02 5.95935702e-01 -9.07935202e-02 2.32718848e-02 -2.05020621e-01 -1.20905590e+00 -1.12665877e-01 9.03449953e-02 1.06504703e+00 8.72834027e-01 3.23910743e-01 -6.16851926e-01 7.66878843e-01 4.99265909e-01 6.03742599e-01 1.75877452e-01 -1.32869494e+00 3.57460678e-01 3.43973219e-01 4.07035559e-01 -1.02193475e+00 3.17528754e-01 1.45052016e-01 -9.49344695e-01 4.76092875e-01 1.24099098e-01 -5.01924604e-02 -1.22712708e+00 1.69732547e+00 3.44170809e-01 5.09012520e-01 -2.21066065e-02 1.11650753e+00 3.64853859e-01 1.14111507e+00 4.04524654e-01 -4.85297292e-01 1.06537676e+00 -1.32595265e+00 -9.63724017e-01 1.95583608e-03 -1.97032228e-01 -1.01369953e+00 1.22303414e+00 5.28640270e-01 -1.38259685e+00 -8.20138812e-01 -9.94011581e-01 -2.29885474e-01 3.57126258e-02 1.74678609e-01 4.84566271e-01 5.75975239e-01 -1.29620337e+00 4.90401179e-01 -1.00306809e+00 -1.79688737e-01 2.67845213e-01 -1.59060821e-01 -2.10854188e-01 -3.39225650e-01 -1.01467037e+00 2.31513605e-01 2.65661210e-01 3.11061859e-01 -1.08754611e+00 -6.05350077e-01 -4.73978668e-01 -1.24638923e-01 1.42469540e-01 -7.74288952e-01 8.52267742e-01 -1.52807570e+00 -1.84916592e+00 5.31195045e-01 -4.67244804e-01 3.86361070e-02 6.90420985e-01 -3.44464898e-01 -4.28037435e-01 4.22844052e-01 -4.30255634e-04 8.98326397e-01 1.32563984e+00 -1.63162875e+00 -8.14955115e-01 9.76451337e-02 1.16546452e-01 2.97123283e-01 -3.03093374e-01 -1.36717603e-01 -1.41544437e+00 -9.65072632e-01 7.91492388e-02 -9.07908559e-01 5.07997684e-02 4.85538125e-01 -4.79787439e-01 1.22507326e-01 1.06767213e+00 -7.94737279e-01 1.39666069e+00 -2.32084942e+00 3.38804275e-01 2.00402692e-01 2.18309492e-01 -1.91906318e-02 -3.29833925e-01 1.04575776e-01 -1.42210484e-01 1.33178592e-01 -3.07496250e-01 -4.03851628e-01 -2.47245237e-01 5.01420498e-02 -1.83678478e-01 4.12260115e-01 2.26545662e-01 6.71336114e-01 -9.70182240e-01 -6.37696087e-01 4.22343463e-01 7.45867193e-01 -5.27613103e-01 4.06994730e-01 -1.85117826e-01 6.06740177e-01 -3.29572588e-01 5.42037427e-01 1.12829924e+00 -1.57863185e-01 1.28506720e-01 -5.63504755e-01 -1.81379467e-01 -4.23322856e-01 -1.19098341e+00 1.86225450e+00 -4.46359932e-01 6.37108266e-01 -6.21298291e-02 -2.67459571e-01 5.84203780e-01 6.89586774e-02 5.09222269e-01 -7.03634262e-01 -1.21328019e-01 -1.74610227e-01 -4.50237900e-01 -4.25595552e-01 7.22698510e-01 1.82011262e-01 3.66004944e-01 6.16492033e-01 -3.81007969e-01 1.17849343e-01 3.70191187e-01 5.24944186e-01 4.41333830e-01 6.82176769e-01 -3.33652496e-01 -1.76574916e-01 5.88345468e-01 -3.80499184e-01 5.01150668e-01 4.08599854e-01 -1.97559029e-01 8.04920435e-01 4.32786107e-01 -2.10643396e-01 -1.03226638e+00 -1.29603517e+00 4.16435659e-01 1.23213565e+00 7.16446817e-01 -2.21326753e-01 -8.17593813e-01 -5.64622462e-01 -3.24253052e-01 8.72681499e-01 -8.46484601e-01 -8.64578560e-02 -4.77169245e-01 -5.26942074e-01 1.42812297e-01 4.81772214e-01 6.67493165e-01 -8.29928994e-01 -3.20591122e-01 4.65506651e-02 -3.67132306e-01 -8.77790928e-01 -1.13944578e+00 -4.10679787e-01 -7.37822175e-01 -9.58245456e-01 -1.22920322e+00 -7.04098523e-01 1.02255905e+00 7.20543981e-01 8.99450719e-01 3.20916355e-01 2.12769955e-02 5.15354514e-01 -5.32784879e-01 4.22613263e-01 -3.03639770e-01 -5.47664225e-01 -3.23967785e-01 5.41719615e-01 -1.28440022e-01 -2.93305397e-01 -1.20551896e+00 2.18604952e-01 -1.38351607e+00 7.44767368e-01 5.51966310e-01 7.18578458e-01 8.05582523e-01 -1.73581496e-01 -1.29663721e-01 -7.63727844e-01 5.29721558e-01 -2.57380635e-01 -4.63684648e-01 5.74168622e-01 -6.08868420e-01 1.56046227e-01 5.17553329e-01 -5.38475275e-01 -1.53349042e+00 -3.91672738e-02 2.68250376e-01 -7.35431075e-01 1.28735393e-01 1.90833479e-01 -1.35723963e-01 4.97963876e-02 6.49590269e-02 4.54219013e-01 -1.52783304e-01 -2.41308242e-01 9.54583943e-01 2.86820024e-01 6.11033857e-01 -7.14309335e-01 8.11935544e-01 7.15195835e-01 -3.69547993e-01 -4.81107652e-01 -2.27384105e-01 2.31229179e-02 -4.90833998e-01 -4.97350693e-01 1.22187889e+00 -8.89143884e-01 -4.80396777e-01 6.42263114e-01 -1.11305165e+00 -6.34552598e-01 9.39880386e-02 2.53125489e-01 -3.26595008e-01 7.29461491e-01 -6.58405960e-01 -7.47802436e-01 -3.05855215e-01 -1.27866197e+00 1.10729504e+00 3.99636358e-01 3.08320075e-01 -9.31705773e-01 -5.71704768e-02 -1.58605784e-01 4.86411393e-01 1.42542869e-01 9.82023895e-01 5.30410528e-01 -9.42487061e-01 3.30256224e-01 -6.31144226e-01 2.63454854e-01 4.29475576e-01 7.09907293e-01 -6.79782033e-01 -4.42204505e-01 -5.41567922e-01 3.88664342e-02 1.05425406e+00 4.37749296e-01 1.33707273e+00 -2.64852285e-01 -1.26133457e-01 7.80251682e-01 1.57063031e+00 5.17384648e-01 8.63127768e-01 2.15982184e-01 9.27823186e-01 2.18060240e-01 5.81606448e-01 4.30078149e-01 3.23048204e-01 5.32544613e-01 1.56739697e-01 -5.99196553e-01 -4.52177972e-01 -3.82766545e-01 4.51438099e-01 6.66944444e-01 -3.32307935e-01 -3.49070162e-01 -3.50134432e-01 2.66255975e-01 -1.73594606e+00 -1.08493209e+00 1.33838937e-01 2.12614369e+00 8.28389883e-01 -3.51947248e-02 -4.32924516e-02 -2.18853578e-01 9.97796834e-01 3.28150004e-01 -6.59875393e-01 -1.51950151e-01 -1.13597713e-01 -1.02319330e-01 3.24227005e-01 7.31623769e-01 -8.60141277e-01 1.08659351e+00 5.87304020e+00 8.51683199e-01 -1.20288062e+00 1.88753098e-01 1.12502241e+00 -7.51296580e-02 -8.12567949e-01 9.40805152e-02 -1.93592772e-01 6.96470439e-01 2.25875869e-01 2.81952433e-02 9.66139257e-01 3.84299666e-01 6.29322827e-01 -3.02013159e-01 -9.42439318e-01 1.11414111e+00 9.30163488e-02 -1.17194903e+00 5.44727981e-01 -4.13165241e-01 1.08422470e+00 -5.72153926e-01 4.92073685e-01 -8.01922753e-02 3.57393205e-01 -5.35722077e-01 1.20264137e+00 8.77149999e-01 1.14950025e+00 -6.91784203e-01 4.90472950e-02 -4.80307400e-01 -1.60739970e+00 1.33859843e-01 -1.80728108e-01 4.43169206e-01 3.82735699e-01 2.86012322e-01 5.86157106e-02 5.82016468e-01 7.45902181e-01 9.20951366e-01 -7.57067978e-01 7.73093343e-01 -2.95355141e-01 4.40484703e-01 4.99073006e-02 2.29861170e-01 2.84507871e-01 -6.31859958e-01 1.60702974e-01 1.24218237e+00 3.19985241e-01 1.89857662e-01 1.34649649e-01 1.11686671e+00 8.44368637e-02 2.90570711e-03 6.62469417e-02 -8.87134224e-02 5.04086494e-01 1.21673596e+00 -8.83025050e-01 -6.09205425e-01 -4.99288887e-01 1.66545272e+00 -3.73612829e-02 1.13942599e+00 -1.34479594e+00 -3.45391512e-01 4.71240669e-01 -1.95918649e-01 3.24602008e-01 -2.87473619e-01 -4.74473983e-02 -1.14315903e+00 -1.54421344e-01 -7.09451735e-01 2.73083776e-01 -1.30813003e+00 -1.11337817e+00 7.30314910e-01 5.45260087e-02 -1.34010804e+00 7.93589801e-02 -2.34291077e-01 -7.74813771e-01 9.32469010e-01 -1.64480984e+00 -1.27800429e+00 -6.58870339e-01 9.28719163e-01 6.86504543e-01 1.65785208e-01 2.22662762e-01 2.85586387e-01 -6.58613980e-01 4.93594497e-01 3.06285441e-01 -3.98716442e-02 9.61002231e-01 -1.09608185e+00 4.43987787e-01 1.32280219e+00 -5.11561297e-02 6.48202956e-01 5.22428691e-01 -7.26193190e-01 -1.53874826e+00 -1.20169532e+00 6.16204515e-02 1.05782084e-01 2.99507976e-01 2.14745160e-02 -7.16346800e-01 4.29343492e-01 6.52571023e-01 -1.96175277e-01 3.15426856e-01 -3.93204272e-01 -3.45068902e-01 -3.49330306e-01 -8.09617102e-01 8.98075938e-01 8.64886582e-01 -5.10040045e-01 -1.46768972e-01 -1.24971062e-01 7.68791080e-01 -2.04187542e-01 -4.24081415e-01 -1.10872425e-01 7.63394892e-01 -9.79236364e-01 9.49084938e-01 -1.85190648e-01 5.61875284e-01 -7.65045762e-01 3.68781462e-02 -1.03525305e+00 -6.08373463e-01 -7.64758706e-01 1.35120481e-01 1.38828182e+00 2.02219561e-01 -3.39669824e-01 5.72923422e-01 9.17675197e-01 -2.33682934e-02 -4.56964910e-01 -5.27414382e-01 -2.98022926e-01 -2.31515333e-01 -2.02753246e-01 5.09436190e-01 8.90921414e-01 -4.14717734e-01 -1.89736515e-01 -7.18801081e-01 1.83339000e-01 6.79692686e-01 3.08814824e-01 7.29049623e-01 -4.80611742e-01 -4.46572304e-01 -5.03415823e-01 9.09351856e-02 -1.40294433e+00 -1.94055930e-01 -4.13171142e-01 4.81273346e-02 -1.67773008e+00 5.16594589e-01 -1.54008374e-01 -6.22259974e-01 4.37654912e-01 -6.17401719e-01 5.36595643e-01 4.80259597e-01 2.64638275e-01 -8.51868272e-01 7.02373505e-01 1.55060172e+00 -4.04215962e-01 -3.78304869e-01 -6.51994586e-01 -5.51862538e-01 4.78387207e-01 3.85649890e-01 -1.58978298e-01 -6.44899905e-01 -8.15122187e-01 -8.61444324e-02 1.63639441e-01 3.11342686e-01 -8.06516230e-01 1.02978624e-01 -6.01362467e-01 7.52780139e-01 -5.08495927e-01 3.59167784e-01 -8.14516187e-01 4.73081559e-01 4.73555535e-01 -4.04228866e-01 3.62727433e-01 1.88202530e-01 9.43376124e-01 -1.65100545e-01 1.44809201e-01 9.64601099e-01 6.51655495e-02 -1.02792013e+00 5.58594048e-01 -4.50474292e-01 -6.99516088e-02 1.05441117e+00 -4.19817150e-01 -2.46241227e-01 -4.56764519e-01 -6.36518955e-01 5.39098158e-02 7.93364346e-01 5.74734986e-01 9.69152153e-01 -1.58083558e+00 -6.72270656e-01 4.41800833e-01 3.38242725e-02 -5.35602450e-01 7.38124132e-01 7.78989494e-01 -8.92224491e-01 -7.43717402e-02 -4.46237803e-01 -6.22524321e-01 -1.18186116e+00 8.16243589e-01 1.82049304e-01 2.93900460e-01 -5.86922944e-01 8.96485209e-01 6.42087758e-01 6.48176849e-01 1.45694703e-01 -6.02641344e-01 3.35186138e-03 -3.19240034e-01 5.42705417e-01 3.72049093e-01 -5.13085425e-01 -6.12265885e-01 -2.15208903e-01 8.59736621e-01 -1.51567057e-01 -4.85029072e-01 8.23645413e-01 -7.26841152e-01 -1.75399125e-01 2.37234592e-01 1.10301006e+00 1.58449829e-01 -2.00317788e+00 -8.64339843e-02 -6.00438774e-01 -1.04182923e+00 6.80430606e-02 -7.27079928e-01 -1.58062494e+00 7.42123783e-01 9.64822710e-01 8.03103447e-02 1.56432569e+00 -4.47165042e-01 8.25181782e-01 -2.44303212e-01 1.56080857e-01 -9.97973025e-01 4.81718123e-01 -3.91753055e-02 7.88409054e-01 -9.17975903e-01 5.47557510e-02 -2.74369657e-01 -9.53972697e-01 1.16474938e+00 5.96154273e-01 -7.50517398e-02 3.69393408e-01 -2.97919828e-02 1.30927831e-01 2.27802753e-01 -6.67346358e-01 5.63107096e-02 4.36366111e-01 3.65322351e-01 4.55649287e-01 -1.22386932e-01 -2.37179726e-01 8.87669474e-02 5.96999109e-01 3.60244475e-02 3.77024323e-01 5.71727037e-01 -2.31268793e-01 -1.00555325e+00 -5.58478653e-01 -7.67164528e-02 -1.51952714e-01 -2.90107071e-01 -1.11342721e-01 4.37286735e-01 1.17985964e-01 1.09965503e+00 1.11689672e-01 -3.00486833e-01 -3.95863596e-03 -1.84012085e-01 5.31225681e-01 -2.69116703e-02 -1.14178695e-02 6.00342870e-01 -2.90243149e-01 -8.48920524e-01 -7.57677138e-01 -3.49576205e-01 -1.18395829e+00 -4.38521057e-01 -1.07103914e-01 1.78507850e-01 3.67976785e-01 5.81174314e-01 4.25991654e-01 7.17660606e-01 7.55732059e-01 -1.09825873e+00 2.01140061e-01 -6.80435240e-01 -5.83635628e-01 8.72215748e-01 3.88414502e-01 -5.90003371e-01 -1.24718018e-01 7.69498348e-01]	[11.141531944274902, -1.1852284669876099]
15ea292b-8390-4d1b-b654-7da21b68ea3f	semi-supervised-credit-card-fraud-detection	null	null	https://doi.org/10.1609/aaai.v37i12.26702	https://ojs.aaai.org/index.php/AAAI/article/view/26702/26474	Semi-supervised Credit Card Fraud Detection via Attribute-driven Graph Representation	Credit card fraud incurs a considerable cost for both cardholders and issuing banks. Contemporary methods apply machine learning-based classifiers to detect fraudulent behavior from labeled transaction records. But labeled data are usually a small proportion of billions of real transactions due to expensive labeling costs, which implies that they do not well exploit many natural features from unlabeled data. Therefore, we propose a semi-supervised graph neural network for fraud detection. Specifically, we leverage transaction records to construct a temporal transaction graph, which is composed of temporal transactions (nodes) and interactions (edges) among them. Then we pass messages among the nodes through a Gated Temporal Attention Network (GTAN) to learn the transaction representation. We further model the fraud patterns through risk propagation among transactions. The extensive experiments are conducted on a real-world transaction dataset and two publicly available fraud detection datasets. The result shows that our proposed method, namely GTAN, outperforms other state-of-the-art baselines on three fraud detection datasets. Semi-supervised experiments demonstrate the excellent fraud detection performance of our model with only a tiny proportion of labeled data.	['Yefeng Zheng', 'Ling Chen', 'Yi Ouyang', 'Ruihui Zhao', 'Enxia Li', 'Dawei Cheng', 'Mingzhi Zhu', 'Sheng Xiang']	2023-06-26	null	null	null	aaai-2023-6	['fraud-detection']	['miscellaneous']	[-2.51431763e-01 -2.58726835e-01 -5.09283066e-01 -6.94628298e-01 -1.50399417e-01 -6.08092397e-02 3.39138865e-01 2.31539845e-01 -3.68359178e-01 5.10134399e-01 2.57846899e-02 -4.69671905e-01 3.42461228e-01 -1.11996806e+00 -5.79539120e-01 -1.38905346e-01 -5.12338042e-01 5.32764494e-01 1.08452760e-01 -2.13039041e-01 4.03243124e-01 1.46531835e-01 -7.60147512e-01 5.51919460e-01 8.26595843e-01 1.05437565e+00 -6.81561530e-01 6.22228011e-02 -2.65229404e-01 1.54904604e+00 -3.36419821e-01 -1.05206513e+00 1.24842040e-01 -6.59761786e-01 -7.22803354e-01 1.04196161e-01 -2.22593635e-01 -8.54842544e-01 -7.07933307e-01 1.02084196e+00 -2.62140423e-01 -2.19088733e-01 7.17359900e-01 -1.34632742e+00 -9.88266408e-01 7.96389461e-01 -1.09335041e+00 4.56488311e-01 6.12403788e-02 -7.00151846e-02 1.18551207e+00 -7.49077618e-01 6.91622496e-01 9.66398418e-01 1.11442864e+00 3.60514849e-01 -1.12898934e+00 -7.11326778e-01 3.09188217e-01 1.86048418e-01 -6.99121535e-01 -2.38611922e-02 1.09237564e+00 -3.91554683e-01 1.27046978e+00 -1.96625993e-01 8.31130505e-01 1.27042162e+00 1.98201865e-01 1.07508099e+00 6.53894484e-01 -3.29893023e-01 3.78352553e-02 -1.07893258e-01 8.80231798e-01 7.88788378e-01 9.13139164e-01 1.93915531e-01 -8.22531641e-01 -7.24007070e-01 8.79179418e-01 9.37600613e-01 4.13604602e-02 -3.94554853e-01 -8.25825989e-01 1.28291619e+00 6.39028251e-01 1.77556977e-01 -4.98585522e-01 4.44673687e-01 1.01956737e+00 8.18621039e-01 7.12277234e-01 -2.31675088e-01 -2.21963629e-01 8.00105259e-02 -6.75666869e-01 2.69365221e-01 1.07974124e+00 8.02931666e-01 5.81089377e-01 5.94152976e-03 1.40916795e-01 8.89508843e-01 7.15055466e-01 -1.72475800e-01 6.43748045e-01 -3.72633874e-01 1.05154991e+00 1.36440635e+00 1.24644585e-01 -1.22651124e+00 -2.49479219e-01 -3.99817992e-03 -1.05136800e+00 -1.56712025e-01 5.29325843e-01 -1.14062615e-01 -7.22948968e-01 1.16358280e+00 -1.03364773e-01 1.26585722e-01 -3.23130995e-01 9.39937174e-01 1.30369946e-01 1.36201546e-01 1.91745088e-01 -3.04841012e-01 1.17693543e+00 -9.15533781e-01 -6.74746275e-01 -2.77766287e-01 1.14088452e+00 -9.24450830e-02 7.10496545e-01 4.30747390e-01 -5.93980253e-01 9.11493152e-02 -9.24394071e-01 4.14917665e-03 -2.68756926e-01 -1.35690942e-01 1.31660807e+00 6.43733799e-01 -3.16181690e-01 8.09465766e-01 -1.36123359e+00 -2.23841399e-01 9.69420314e-01 1.72516927e-01 -5.89254275e-02 -2.66240001e-01 -1.24517453e+00 5.27899206e-01 2.02373162e-01 5.80373883e-01 -6.26591504e-01 1.90161802e-02 -9.13404167e-01 -1.12709299e-01 2.19351724e-01 -5.39030254e-01 1.21926236e+00 -1.14923680e+00 -7.66368508e-01 1.18649137e+00 1.26259960e-02 -1.06290340e+00 1.02007186e+00 -4.40367758e-01 -5.20537734e-01 -1.10890359e-01 1.82687938e-01 -3.73315126e-01 6.57072484e-01 -9.01017666e-01 -5.90841532e-01 -6.76750422e-01 -4.16522861e-01 -1.07168362e-01 -3.39380294e-01 2.42017597e-01 -3.35638285e-01 -1.12932086e+00 4.89828885e-01 -5.77659190e-01 -1.85222045e-01 -2.80876577e-01 -6.29093587e-01 -2.55663186e-01 9.99579072e-01 -7.93442547e-01 1.57395983e+00 -1.91586912e+00 -5.72748482e-01 3.35153520e-01 1.93598881e-01 -1.34311408e-01 4.68575120e-01 7.73247659e-01 -1.32340274e-03 2.86509655e-02 -6.40242636e-01 -5.37264168e-01 -8.65487233e-02 1.95937216e-01 -6.29619360e-01 6.84417605e-01 1.90942466e-01 1.14250803e+00 -9.93965030e-01 -2.84284353e-01 -1.44386530e-01 -1.60219625e-01 -4.17127192e-01 2.42896274e-01 -9.13872421e-02 -4.47362214e-02 -7.19130278e-01 1.22224641e+00 6.54823363e-01 -3.95773500e-01 4.98495996e-01 3.28334093e-01 6.02683902e-01 3.41902822e-01 -6.98194504e-01 1.42272127e+00 7.91667923e-02 3.20677698e-01 -3.94810379e-01 -1.62695575e+00 1.11138749e+00 1.10839710e-01 4.27071273e-01 -7.31514752e-01 -1.17316013e-02 5.07318377e-01 -2.37590194e-01 -5.07953882e-01 2.79168427e-01 -4.00943786e-01 -4.18999434e-01 1.19232011e+00 -1.68808609e-01 6.49880707e-01 2.55836900e-02 4.07315522e-01 1.32717156e+00 8.13325793e-02 2.32215345e-01 2.11962283e-01 -3.87524217e-02 2.42031813e-01 9.25425053e-01 8.88629913e-01 -5.25443733e-01 4.09061521e-01 1.07146716e+00 -1.02146649e+00 -7.70876765e-01 -6.87954605e-01 1.78357080e-01 9.67420638e-01 1.67159721e-01 -4.15159054e-02 -5.17388463e-01 -1.37344790e+00 8.01644802e-01 3.66357148e-01 -8.94397140e-01 -3.63319427e-01 -9.58508253e-01 -1.36339676e+00 6.63632035e-01 7.84292877e-01 6.91217244e-01 -1.55646992e+00 -3.45853597e-01 5.50044000e-01 -1.45488298e-02 -6.69222414e-01 -6.12958550e-01 1.41957849e-01 -1.48910677e+00 -1.58208859e+00 -3.36597711e-01 -9.01913106e-01 7.97741055e-01 3.63270670e-01 1.27739680e+00 5.26493013e-01 -1.62690163e-01 -3.78259778e-01 -3.54814261e-01 -2.33128145e-01 -2.00277343e-01 -2.74708420e-01 -3.66739556e-02 4.29313570e-01 1.33223438e+00 -5.55502713e-01 -6.49128735e-01 1.58233270e-01 -7.09663272e-01 -2.03164682e-01 4.30759877e-01 1.27887869e+00 3.12120229e-01 -1.23420037e-01 1.03263724e+00 -1.78032839e+00 7.99990714e-01 -9.81802225e-01 -5.13440967e-01 1.76763147e-01 -1.05566430e+00 -1.90906480e-01 4.81713086e-01 -2.26112813e-01 -1.06448650e+00 -2.50767469e-01 6.87301934e-01 -4.63367283e-01 1.44680992e-01 9.25212801e-01 3.34656894e-01 3.63522708e-01 4.61487561e-01 -1.15778726e-02 -2.45054379e-01 -6.61282718e-01 3.97086628e-02 7.46701062e-01 3.75560433e-01 -2.81345457e-01 3.41693908e-01 7.53784955e-01 -5.10891974e-01 -3.95279825e-02 -7.27058291e-01 -5.05354106e-01 -5.19973457e-01 2.55693346e-01 2.11477652e-01 -7.74259806e-01 -7.00613439e-01 1.30325389e+00 -1.07543790e+00 -2.11192697e-01 -2.75214128e-02 4.75508273e-01 -4.09359038e-01 6.34656906e-01 -1.61034250e+00 -1.10690391e+00 -4.61261481e-01 -2.02440694e-01 6.12294555e-01 -2.15994358e-01 -1.19791068e-01 -1.11898541e+00 1.82458282e-01 5.44419587e-01 -7.62612224e-02 4.85612392e-01 8.88778090e-01 -9.09406245e-01 -5.66146731e-01 -6.86487198e-01 -5.73532999e-01 3.05461764e-01 3.02776933e-01 -3.29519928e-01 -5.85847199e-01 -3.39644760e-01 3.17194313e-01 -5.85454881e-01 1.71026027e+00 2.31890038e-01 1.03992796e+00 -3.88456136e-01 -5.08024454e-01 5.82501233e-01 1.38348794e+00 2.39586249e-01 5.17835557e-01 5.15388191e-01 9.12966907e-01 6.63071573e-01 6.10629320e-01 4.92950380e-01 4.96159703e-01 3.68143246e-02 3.93415987e-01 1.01918124e-01 6.97733879e-01 -7.44069219e-01 3.81913245e-01 7.16909409e-01 -9.20035243e-02 -9.06619653e-02 -1.14713442e+00 7.22291112e-01 -2.59185314e+00 -1.04816377e+00 -4.39196259e-01 2.09407377e+00 5.58197081e-01 4.97266978e-01 3.91509265e-01 1.74484164e-01 8.81777167e-01 6.18273916e-04 -9.41700459e-01 -2.52009660e-01 -5.59109077e-02 -2.89623171e-01 5.27638197e-01 1.11248074e-02 -1.20027769e+00 7.54359245e-01 6.20188951e+00 1.94313973e-01 -6.81589484e-01 -3.68035994e-02 1.11727834e+00 -1.00138538e-01 -1.60680950e-01 1.61742106e-01 -2.84952998e-01 8.31302464e-01 7.45305896e-01 -6.97821826e-02 2.41495922e-01 8.06797683e-01 2.70576060e-01 -4.66492958e-02 -1.28832257e+00 8.85459542e-01 -1.20494418e-01 -1.28627181e+00 3.03203285e-01 1.36984229e-01 5.77657402e-01 2.43781880e-01 -4.61427361e-01 4.59870964e-01 6.15921199e-01 -1.11472201e+00 5.21514118e-01 6.51943922e-01 3.50360513e-01 -8.36688876e-01 1.13402712e+00 3.77169102e-01 -9.33283389e-01 -3.04704159e-01 -3.04641455e-01 -2.39916265e-01 1.82720348e-01 6.61189079e-01 -3.40577364e-01 4.68012571e-01 8.50856602e-01 1.35900879e+00 -3.74864906e-01 8.02625418e-01 -1.18848272e-01 1.06944597e+00 -5.85647896e-02 7.88556635e-02 2.27469578e-01 -7.82096982e-01 -1.55517951e-01 1.36839616e+00 1.20106414e-01 4.21842560e-02 -6.78126141e-03 1.09169424e+00 -6.96131945e-01 1.05222473e-02 -9.72441554e-01 -1.98452145e-01 2.48766020e-01 6.76770806e-01 -6.92331553e-01 -3.91463608e-01 -9.12426710e-01 1.23708081e+00 8.05189490e-01 5.04713178e-01 -5.60383737e-01 -5.43221116e-01 2.08081260e-01 8.32222775e-02 1.93988830e-01 1.12884127e-01 -6.00305259e-01 -1.66311336e+00 5.42049050e-01 -7.29298830e-01 1.12094462e+00 -2.64318734e-01 -2.04326391e+00 6.28666058e-02 -5.21687627e-01 -1.35067344e+00 -2.17068791e-01 -3.80982280e-01 -1.04062843e+00 6.90487325e-01 -1.39765298e+00 -1.13043976e+00 -4.70577106e-02 6.89044058e-01 2.14834616e-01 -2.94466436e-01 5.65331280e-01 2.23424092e-01 -9.14335728e-01 3.79810929e-01 2.21629962e-01 1.04167032e+00 3.33273947e-01 -1.14760447e+00 1.03168702e+00 7.38206446e-01 3.13507050e-01 7.79052675e-01 -3.76210399e-02 -1.04850042e+00 -1.16088617e+00 -1.15979362e+00 1.17919624e+00 -4.78392243e-01 8.87986600e-01 -4.17284578e-01 -1.54551983e+00 1.27718735e+00 -2.91428238e-01 3.45441818e-01 5.46740532e-01 1.39519155e-01 -6.39927864e-01 9.63607710e-03 -1.21625304e+00 4.55605201e-02 1.21879530e+00 -7.54434884e-01 -9.09818828e-01 3.31776023e-01 3.99992883e-01 9.23991948e-02 -4.21830654e-01 1.31320924e-01 4.94378477e-01 -1.31915069e+00 4.71040726e-01 -1.14923775e+00 4.83399600e-01 2.72923678e-01 3.22941363e-01 -8.46030593e-01 2.89982688e-02 -5.17820120e-01 -8.40995729e-01 1.01236522e+00 2.95398265e-01 -1.00665104e+00 1.28667498e+00 6.55463338e-01 3.82953912e-01 -7.37896442e-01 -8.12521756e-01 -7.24153101e-01 -1.11734971e-01 -5.57959259e-01 5.27305782e-01 1.68751013e+00 5.78500330e-01 1.28228754e-01 -5.44471204e-01 -3.24076831e-01 9.90148842e-01 5.91528118e-01 3.48458797e-01 -1.26381648e+00 -2.93206960e-01 -3.49899143e-01 -3.54480833e-01 -7.63358414e-01 5.02271391e-02 -7.82718003e-01 -4.82522815e-01 -1.17299247e+00 5.25166512e-01 -5.79006433e-01 -7.40699649e-01 5.17449319e-01 -2.33915761e-01 8.85165930e-02 -3.59472781e-01 9.46595669e-01 -4.67381239e-01 4.31008637e-01 6.86986148e-01 -2.32144892e-01 -4.48331058e-01 2.21001625e-01 -6.87144279e-01 8.75994921e-01 7.73553848e-01 -8.35127890e-01 -7.63860643e-02 -5.44332623e-01 2.84988999e-01 2.73551226e-01 4.48792249e-01 -3.13769020e-02 1.91604540e-01 -2.47074023e-01 2.19413429e-01 -5.32713413e-01 -3.01028609e-01 -3.58606279e-01 -2.12541044e-01 8.08326602e-01 -2.23223835e-01 -3.31488205e-03 -3.25206250e-01 1.26313102e+00 -5.79096377e-01 -1.33259326e-01 3.62743407e-01 -2.38621116e-01 -5.18729866e-01 4.72907096e-01 -4.78905141e-02 1.45019889e-01 7.81903744e-01 -2.01387048e-01 -3.02927226e-01 -3.07255685e-01 -5.64752162e-01 5.75001955e-01 4.00861740e-01 4.50239718e-01 7.12808192e-01 -1.50419927e+00 -8.25914204e-01 4.33620095e-01 3.33151162e-01 7.86282569e-02 -4.91738096e-02 7.52659798e-01 -7.75782406e-01 3.05041254e-01 -2.81420462e-02 -1.92727759e-01 -6.95267498e-01 5.08583009e-01 4.60599899e-01 -6.76659644e-01 -7.78189361e-01 8.11432302e-01 -1.24681085e-01 -3.23789805e-01 2.20663831e-01 -5.49853802e-01 -2.48453021e-02 6.82444572e-02 1.43295974e-01 4.64901239e-01 -6.09318949e-02 -2.49272570e-01 -4.33776081e-01 -6.28880877e-03 -6.62995458e-01 2.37526610e-01 1.56007302e+00 2.26098582e-01 -2.65641659e-01 4.95727152e-01 1.10561943e+00 -5.01095772e-01 -1.14119983e+00 -5.22307754e-01 8.47788453e-01 -7.19610095e-01 -1.94440871e-01 -3.74872118e-01 -1.38435602e+00 7.56270468e-01 2.98224930e-02 6.07207716e-01 7.11838365e-01 -2.46559948e-01 1.06280947e+00 6.13149107e-01 7.94143379e-01 -1.26247728e+00 3.23730260e-02 2.61132181e-01 6.04827821e-01 -1.60231996e+00 -1.07556954e-01 -2.06742361e-01 -9.14306521e-01 8.93333673e-01 6.32433236e-01 -8.51974189e-01 7.68663049e-01 -2.37315893e-01 1.84511244e-01 -6.71356559e-01 -7.28940010e-01 3.68345529e-01 -3.99692208e-01 3.79050612e-01 5.33565223e-01 1.56864941e-01 -3.80573004e-01 9.62215960e-01 2.96871781e-01 3.82941276e-01 4.95764911e-01 1.20846593e+00 -1.08651660e-01 -1.01588297e+00 3.39818522e-02 1.17332757e+00 -7.25508451e-01 -4.86389920e-03 -6.85090840e-01 7.95309782e-01 -2.87157297e-01 8.02480876e-01 8.37018639e-02 -1.68708086e-01 3.96216273e-01 1.87800303e-01 -6.65500909e-02 -7.18742311e-01 -8.81143272e-01 -2.39429623e-01 1.40019447e-01 -6.74149096e-01 -3.58547747e-01 -9.28831935e-01 -1.27951777e+00 -5.50919056e-01 -5.86903036e-01 5.58169410e-02 -8.60133991e-02 6.84576035e-01 1.68314010e-01 8.94858129e-03 8.68733644e-01 -2.56185174e-01 -8.63990545e-01 -1.10804307e+00 -1.24715018e+00 1.05417633e+00 3.85761678e-01 -4.37310815e-01 -4.43481416e-01 1.07816719e-01]	[7.326705455780029, 5.809619903564453]
507932d6-0dd4-4511-8ea6-308f0a87c7dc	multimodal-garment-designer-human-centric	2304.02051	null	https://arxiv.org/abs/2304.02051v1	https://arxiv.org/pdf/2304.02051v1.pdf	Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editing	Fashion illustration is used by designers to communicate their vision and to bring the design idea from conceptualization to realization, showing how clothes interact with the human body. In this context, computer vision can thus be used to improve the fashion design process. Differently from previous works that mainly focused on the virtual try-on of garments, we propose the task of multimodal-conditioned fashion image editing, guiding the generation of human-centric fashion images by following multimodal prompts, such as text, human body poses, and garment sketches. We tackle this problem by proposing a new architecture based on latent diffusion models, an approach that has not been used before in the fashion domain. Given the lack of existing datasets suitable for the task, we also extend two existing fashion datasets, namely Dress Code and VITON-HD, with multimodal annotations collected in a semi-automatic manner. Experimental results on these new datasets demonstrate the effectiveness of our proposal, both in terms of realism and coherence with the given multimodal inputs. Source code and collected multimodal annotations will be publicly released at: https://github.com/aimagelab/multimodal-garment-designer.	['Rita Cucchiara', 'Marco Bertini', 'Marcella Cornia', 'Giuseppe Cartella', 'Davide Morelli', 'Alberto Baldrati']	2023-04-04	null	null	null	null	['multimodal-fashion-image-editing']	['computer-vision']	[ 1.59566671e-01 1.11680338e-02 2.58866362e-02 -3.41968507e-01 -2.42167726e-01 -7.77371943e-01 1.00202751e+00 3.97775471e-02 -8.76179859e-02 3.73959810e-01 4.24408406e-01 -3.33491005e-02 2.91911457e-02 -6.03854656e-01 -5.86536527e-01 -4.41348970e-01 4.53332931e-01 5.04792452e-01 -6.52476624e-02 -5.38584173e-01 -5.16659543e-02 2.62895346e-01 -1.43834484e+00 5.94597518e-01 3.63685936e-01 7.52037704e-01 1.97775468e-01 9.08335090e-01 7.91897699e-02 6.64076388e-01 -1.46890759e-01 -8.24751437e-01 4.15958799e-02 -5.33782661e-01 -5.55079103e-01 6.46723747e-01 3.29070896e-01 -3.32180738e-01 -2.72057623e-01 8.28564584e-01 4.13346469e-01 1.95551351e-01 5.52309334e-01 -1.00278962e+00 -1.13755667e+00 7.15001643e-01 -2.87098914e-01 -7.09099352e-01 7.62868643e-01 4.37792242e-01 9.70337927e-01 -8.02673757e-01 1.12401593e+00 1.42524898e+00 4.50510174e-01 7.42623031e-01 -1.59469175e+00 -1.79883078e-01 2.75991499e-01 -6.21547401e-02 -1.13220882e+00 -5.99125624e-01 1.27418041e+00 -5.72798669e-01 7.61936158e-02 5.61641097e-01 1.02854037e+00 1.77947068e+00 -5.44559181e-01 1.19619942e+00 1.27549887e+00 -6.64526582e-01 2.55756259e-01 3.04240912e-01 -4.68716361e-02 6.56297445e-01 -2.86844343e-01 -1.01861179e-01 -4.93872315e-01 7.91889280e-02 1.04489386e+00 -7.88206831e-02 -1.03316084e-01 -7.46068478e-01 -1.54524326e+00 7.55613565e-01 3.01791936e-01 3.55132014e-01 -6.15544915e-01 4.74336386e-01 4.85159934e-01 2.45825842e-01 4.82778907e-01 2.42225066e-01 -1.77313879e-01 -1.22748792e-01 -7.65665352e-01 4.52727169e-01 8.73980761e-01 1.06791508e+00 2.67134100e-01 -2.51868665e-01 -3.02340180e-01 8.75810266e-01 6.40008688e-01 4.57628280e-01 -2.45511845e-01 -9.02499557e-01 2.23734841e-01 5.86544573e-01 2.92240351e-01 -1.12544835e+00 -1.32564560e-01 5.74000888e-02 -7.02920079e-01 1.11417368e-01 5.58447599e-01 -1.00372352e-01 -9.07856047e-01 1.52088583e+00 5.09131789e-01 -1.34601131e-01 -1.57331020e-01 1.39849234e+00 1.04666710e+00 3.89651597e-01 4.24428701e-01 1.22576497e-01 1.78289282e+00 -9.85635817e-01 -9.66883540e-01 4.56345528e-02 5.68237305e-02 -1.19627392e+00 1.30817103e+00 4.30970728e-01 -1.20912480e+00 -6.90691292e-01 -7.38871813e-01 -2.12545246e-01 -4.91942078e-01 5.27633667e-01 7.58595884e-01 5.66953242e-01 -8.45324993e-01 3.28644633e-01 -5.80957234e-01 -7.77428687e-01 4.48170394e-01 -1.24175072e-01 -3.88352215e-01 -1.18044741e-01 -9.51194108e-01 6.96253657e-01 7.44975731e-02 5.34547925e-01 -7.42249787e-01 -4.86000538e-01 -8.80477071e-01 -4.83552843e-01 5.07409334e-01 -1.13692534e+00 1.23749220e+00 -1.23447859e+00 -1.86287594e+00 1.09023499e+00 1.07300386e-01 1.34337589e-01 1.10752785e+00 -2.13729650e-01 -1.88840449e-01 7.61040673e-02 -2.76032001e-01 9.23004389e-01 9.97905135e-01 -1.95497286e+00 3.78684662e-02 -3.12979072e-01 3.89436960e-01 2.60500144e-02 -1.70552954e-01 -1.00038439e-01 -9.58222270e-01 -7.92300701e-01 -1.59284636e-01 -1.29886949e+00 -3.43219995e-01 3.21679801e-01 -7.06115484e-01 2.67109107e-02 5.55222273e-01 -9.23956215e-01 8.18867028e-01 -2.09589744e+00 7.00302958e-01 2.92747051e-01 1.28959864e-01 1.09817259e-01 -1.38808906e-01 7.30995774e-01 2.18832478e-01 -2.33177751e-01 -2.87677765e-01 -8.97977293e-01 5.42190254e-01 2.65720874e-01 1.44716818e-02 3.92392099e-01 -1.25524318e-02 1.29368079e+00 -9.75263178e-01 -3.15261722e-01 5.92519224e-01 8.06412160e-01 -3.77748877e-01 1.52863547e-01 -6.58659220e-01 8.91629755e-01 -3.99680108e-01 5.98763704e-01 6.40555441e-01 -4.66108285e-02 5.98120034e-01 -7.28057683e-01 -1.03150159e-01 -4.32456881e-01 -1.22990453e+00 2.29492831e+00 -6.29500329e-01 5.17654121e-01 2.08009869e-01 -4.57383752e-01 1.05978417e+00 3.43445480e-01 2.37099856e-01 -5.83737910e-01 3.61045480e-01 -1.66289181e-01 -4.63521212e-01 -8.40689838e-01 8.37627470e-01 -2.48141717e-02 -3.31424713e-01 3.18291605e-01 -5.75524978e-02 -2.94384122e-01 2.30892614e-01 9.56497118e-02 5.35244763e-01 7.85547853e-01 -1.13274060e-01 1.37627706e-01 2.60150641e-01 7.01202080e-02 -1.73294947e-01 4.23198760e-01 2.55512863e-01 7.01259673e-01 3.45774829e-01 -3.65098059e-01 -1.32459319e+00 -1.02659631e+00 2.44222343e-01 1.09649706e+00 1.08585253e-01 -4.55353051e-01 -7.05908835e-01 -5.06904721e-01 -2.37435102e-03 6.84066057e-01 -8.29524398e-01 2.81387657e-01 -4.12728786e-01 -2.37981856e-01 2.55537540e-01 2.79640585e-01 1.66978374e-01 -1.22650564e+00 -5.74345648e-01 1.35391057e-01 -2.06778705e-01 -1.29595184e+00 -3.24991196e-01 -3.12510282e-01 -5.11806369e-01 -8.85030329e-01 -1.11372876e+00 -6.45744205e-01 7.00619757e-01 -1.67616308e-01 1.09760809e+00 2.30182894e-02 -5.02205014e-01 1.04516268e+00 -5.24925470e-01 -9.34898406e-02 -7.39724100e-01 -7.27192536e-02 -3.14281195e-01 4.60637510e-01 1.25452569e-02 -5.34734786e-01 -8.62841189e-01 3.16166431e-01 -1.15803885e+00 7.06309259e-01 4.11032617e-01 5.54902077e-01 2.10709497e-01 -6.58526003e-01 2.56867647e-01 -8.68900478e-01 7.25681365e-01 -3.04858893e-01 -1.11101635e-01 2.26824835e-01 6.71039000e-02 -1.81289375e-01 1.98344991e-01 -6.93517625e-01 -1.05020356e+00 4.17881340e-01 -1.86255589e-01 -4.60967183e-01 -6.76848173e-01 2.08863646e-01 -1.59288749e-01 2.28806898e-01 3.01575691e-01 -1.31577924e-01 8.63407403e-02 -7.83538520e-01 1.25784922e+00 3.80950958e-01 4.58868891e-01 -6.72123790e-01 7.07744002e-01 6.15011573e-01 -1.44146264e-01 -7.18737304e-01 -1.93034604e-01 -2.76598066e-01 -8.92605305e-01 -7.45942950e-01 1.10465896e+00 -7.35562265e-01 -1.09288621e+00 2.55531162e-01 -1.28186679e+00 -4.73684043e-01 -4.03636962e-01 2.98423707e-01 -7.95311153e-01 4.16031390e-01 -6.79536939e-01 -8.78905654e-01 -7.23247156e-02 -1.13389230e+00 1.27237689e+00 -6.56863749e-02 -6.99172676e-01 -1.12110496e+00 3.73619758e-02 6.00556433e-01 2.89278299e-01 6.85712993e-01 8.28034043e-01 -3.25080343e-02 -4.73429650e-01 -6.51318952e-02 -1.45563781e-01 1.34285927e-01 5.22197187e-02 1.12198912e-01 -1.06289816e+00 1.53029904e-01 -5.96595764e-01 -3.81067336e-01 7.52048612e-01 1.32851020e-01 5.43237567e-01 -5.07060215e-02 -1.02315135e-01 1.41678929e-01 1.32889593e+00 -1.89693063e-01 6.19593501e-01 1.09021544e-01 9.32910442e-01 8.78994703e-01 4.82181996e-01 5.77176869e-01 6.42032444e-01 1.06045496e+00 4.22201842e-01 -4.28677261e-01 -5.75776696e-01 -4.97145504e-01 1.83586866e-01 8.40774834e-01 -5.30952394e-01 -1.33409381e-01 -6.04940891e-01 5.82941592e-01 -2.24598312e+00 -7.41039753e-01 -4.82161492e-01 1.68105555e+00 7.07911432e-01 -3.51478636e-01 3.76462638e-01 -9.51003730e-02 4.73753184e-01 9.32282880e-02 -1.56623870e-01 -5.00705063e-01 -1.41365439e-01 -1.32722124e-01 1.64249778e-01 5.05110621e-01 -1.07817149e+00 9.70914006e-01 5.12202787e+00 5.46486139e-01 -8.63973081e-01 1.88052341e-01 3.85013938e-01 6.10994473e-02 -7.20999360e-01 -2.39916425e-02 -2.64432102e-01 2.29870170e-01 4.07923847e-01 6.58258379e-01 6.63047135e-01 5.37083328e-01 4.28698480e-01 -3.40432636e-02 -1.29436314e+00 1.05276668e+00 1.94275245e-01 -1.29585004e+00 -2.26769894e-02 -1.32068396e-01 6.55089855e-01 -7.72180676e-01 2.27087662e-01 4.41328734e-02 2.92797416e-01 -5.86364806e-01 1.32959735e+00 1.10549200e+00 6.93885148e-01 -2.98752755e-01 1.73865855e-01 -9.64004695e-02 -1.13720548e+00 2.21017972e-01 2.24559009e-01 3.38552073e-02 6.33849084e-01 2.41502985e-01 -6.11103833e-01 6.84930325e-01 2.60281920e-01 6.64306641e-01 -6.52781546e-01 6.80539966e-01 -3.54554206e-01 2.43988410e-01 -1.15183286e-01 -2.20005408e-01 1.32429555e-01 -3.85655165e-01 6.47543013e-01 1.37090468e+00 1.55741841e-01 -3.27578515e-01 2.48027369e-01 1.19650841e+00 2.44545322e-02 3.62667978e-01 -6.90616548e-01 -2.25840926e-01 -1.00255109e-01 1.56206477e+00 -9.26201701e-01 -2.60960609e-01 -2.00063705e-01 1.58769596e+00 -5.74805364e-02 5.66906631e-01 -9.27509189e-01 9.04513150e-02 3.37084740e-01 7.14593530e-02 4.37275946e-01 -4.98610735e-01 -2.26327360e-01 -1.06551909e+00 -1.62781887e-02 -8.05950224e-01 -6.32557496e-02 -1.06359982e+00 -1.41552734e+00 4.62538242e-01 6.12648688e-02 -9.85532343e-01 9.38425586e-02 -4.80248392e-01 -2.69870132e-01 5.13036609e-01 -1.15878427e+00 -2.14420843e+00 -3.82624924e-01 5.39757311e-01 7.56902575e-01 2.64060497e-01 9.22497272e-01 5.46094835e-01 -3.15491438e-01 2.46081233e-01 -3.14400405e-01 1.58517994e-02 7.66904175e-01 -1.02700508e+00 4.45783466e-01 2.94263989e-01 2.67535269e-01 5.88103473e-01 9.36420858e-01 -6.39894366e-01 -1.97631967e+00 -6.76962435e-01 5.86832225e-01 -6.51775479e-01 6.54065907e-01 -7.77404785e-01 -4.04352725e-01 4.62092668e-01 5.68548560e-01 -3.12483728e-01 5.80774486e-01 2.20393494e-01 -1.61368757e-01 2.29032680e-01 -8.47388029e-01 1.01162481e+00 1.27314842e+00 -5.45483649e-01 -3.71883631e-01 1.60335273e-01 4.57366288e-01 -2.55965203e-01 -1.10907912e+00 1.48813441e-01 8.73250008e-01 -5.79160571e-01 1.08778179e+00 -5.55501997e-01 6.65591121e-01 -3.11340392e-01 -2.21957013e-01 -1.21618915e+00 -1.95086077e-01 -7.61663377e-01 -3.19478437e-02 1.60272932e+00 2.85047919e-01 6.21688552e-02 5.65648198e-01 7.02962637e-01 -7.64705753e-03 -3.29329729e-01 -4.31065142e-01 -1.85797065e-01 -5.19056201e-01 -6.66662395e-01 4.99225289e-01 1.13857591e+00 -1.94473371e-01 4.31959301e-01 -1.01976609e+00 -7.19360933e-02 5.58302164e-01 3.39378357e-01 1.22925472e+00 -1.06247389e+00 -3.94233912e-01 -4.04564351e-01 -1.58190459e-01 -9.56404209e-01 -1.42982870e-01 -9.20922697e-01 1.84218865e-02 -1.77394676e+00 1.42107695e-01 -3.68960172e-01 2.09335312e-01 4.37439620e-01 2.63106655e-02 6.09255791e-01 6.98622048e-01 -8.23714212e-02 -8.30637395e-01 6.71578765e-01 1.65739238e+00 -2.37564087e-01 -2.71931797e-01 -3.64845783e-01 -4.95175958e-01 7.99238801e-01 5.35850048e-01 -6.10904209e-02 -1.95982695e-01 -3.72239977e-01 3.29055667e-01 1.17137551e-01 9.88374770e-01 -6.66279614e-01 8.31711888e-02 1.36459451e-02 4.12484735e-01 -2.93029010e-01 7.50275075e-01 -1.13538063e+00 6.59891307e-01 3.04162621e-01 -5.08942127e-01 -1.13437593e-01 1.54067412e-01 6.61128104e-01 1.66534603e-01 1.41782552e-01 2.56029278e-01 -1.71991184e-01 -9.11075532e-01 -5.66534027e-02 -5.22588968e-01 -6.26895607e-01 9.43497598e-01 -8.57890397e-02 -8.18216503e-02 -4.65172589e-01 -1.36064065e+00 -4.08578478e-02 6.12680674e-01 8.00827026e-01 7.16886640e-01 -1.62881339e+00 -6.42982006e-01 1.51703775e-01 4.12438601e-01 -6.16739571e-01 6.38527691e-01 8.68333578e-01 -4.16450411e-01 5.11159152e-02 -3.14305842e-01 -6.65195465e-01 -1.37523162e+00 6.42473638e-01 -1.46032259e-01 1.09343626e-01 -7.16525137e-01 5.04623294e-01 3.28215398e-02 -5.71989536e-01 9.27997530e-02 -3.71591479e-01 -1.60836816e-01 3.24975997e-01 1.74521893e-01 1.07266352e-01 -3.23689133e-01 -7.48979986e-01 -4.89983298e-02 7.21824408e-01 3.44893187e-01 -3.81422192e-01 1.34132206e+00 -4.68870223e-01 -2.75716130e-02 8.27560961e-01 8.70555222e-01 1.51168659e-01 -1.35562396e+00 -1.14712909e-01 -9.76525098e-02 -5.92534065e-01 -1.75835878e-01 -9.66194272e-01 -8.23974192e-01 6.83990359e-01 7.26236105e-01 1.21245600e-01 8.27093482e-01 1.92962840e-01 7.20650911e-01 -6.14374280e-02 2.91992575e-01 -9.51337159e-01 2.99826562e-01 6.51452914e-02 1.34477377e+00 -1.17334938e+00 -1.94354326e-01 -4.35652316e-01 -1.07915664e+00 1.13324833e+00 2.14344844e-01 -3.43177691e-02 3.87694150e-01 2.47282465e-03 1.50947824e-01 -4.24089313e-01 -5.52862287e-01 -4.37577397e-01 5.27506173e-01 5.33931434e-01 4.45860207e-01 3.43045324e-01 -2.30841771e-01 6.59516692e-01 2.13799238e-01 3.83844912e-01 4.59509753e-02 9.31507945e-01 2.35324830e-01 -1.39784968e+00 -3.67390603e-01 -2.90863693e-01 9.66485292e-02 1.70962349e-01 -6.55824840e-01 6.85823083e-01 3.16457689e-01 8.34102452e-01 -2.45973065e-01 -2.60450810e-01 7.65568376e-01 1.26942754e-01 9.12895322e-01 -2.32900873e-01 -7.46182084e-01 2.89978921e-01 5.04506528e-01 -4.38351542e-01 -7.27805436e-01 -4.98220146e-01 -6.50721431e-01 -4.10414666e-01 1.58050418e-01 -2.73807257e-01 1.11334407e+00 6.47252202e-01 1.33666143e-01 7.78210700e-01 2.24521741e-01 -1.39089811e+00 4.65275683e-02 -8.38151217e-01 -3.45181525e-01 9.57545161e-01 1.26609638e-01 -5.42413116e-01 3.76468927e-01 6.20464444e-01]	[11.71531867980957, -0.6738238334655762]
e2b23958-7393-4504-a689-3d925ec75c2e	phd-thesis-exploring-the-role-of-self	2306.1465	null	https://arxiv.org/abs/2306.14650v2	https://arxiv.org/pdf/2306.14650v2.pdf	PhD Thesis: Exploring the role of (self-)attention in cognitive and computer vision architecture	We investigate the role of attention and memory in complex reasoning tasks. We analyze Transformer-based self-attention as a model and extend it with memory. By studying a synthetic visual reasoning test, we refine the taxonomy of reasoning tasks. Incorporating self-attention with ResNet50, we enhance feature maps using feature-based and spatial attention, achieving efficient solving of challenging visual reasoning tasks. Our findings contribute to understanding the attentional needs of SVRT tasks. Additionally, we propose GAMR, a cognitive architecture combining attention and memory, inspired by active vision theory. GAMR outperforms other architectures in sample efficiency, robustness, and compositionality, and shows zero-shot generalization on new reasoning tasks.	['Mohit Vaishnav']	2023-06-26	null	null	null	null	['visual-reasoning', 'visual-reasoning']	['computer-vision', 'reasoning']	[-3.65703143e-02 3.16753954e-01 3.09587270e-01 1.64627045e-01 -6.00793399e-02 -4.60717082e-01 6.75386071e-01 9.53289717e-02 -5.66136241e-01 2.64192909e-01 6.75139189e-01 -2.65290916e-01 -6.41338825e-01 -9.69989717e-01 -4.11700457e-01 -3.57620209e-01 4.91041429e-02 5.81148684e-01 4.52706724e-01 -5.94189942e-01 5.82104981e-01 6.82604611e-01 -1.41615808e+00 5.22429585e-01 9.60056007e-01 5.77201486e-01 4.21905339e-01 6.55127525e-01 -2.52250105e-01 1.75967252e+00 -5.16252518e-01 -6.04750454e-01 1.66740328e-01 -1.66331887e-01 -1.15787089e+00 -1.55073076e-01 2.84552813e-01 -4.01268661e-01 -7.21895218e-01 7.04860151e-01 3.06911737e-01 9.03935969e-01 5.32010972e-01 -1.02201974e+00 -1.80865908e+00 5.92461884e-01 -4.88860697e-01 9.84169781e-01 4.84570831e-01 5.84248304e-01 8.91773164e-01 -1.13185847e+00 5.05287409e-01 1.44401848e+00 7.35418499e-01 5.73752046e-01 -1.23487413e+00 -3.04093570e-01 3.18302274e-01 8.50505769e-01 -1.12382448e+00 -4.67863947e-01 6.65592134e-01 -2.81871200e-01 1.63828290e+00 3.13883781e-01 1.06623018e+00 1.00779712e+00 1.11360386e-01 1.08150709e+00 7.74838448e-01 -3.65834951e-01 3.95299733e-01 -3.02877784e-01 6.05768859e-01 8.97668242e-01 6.97107166e-02 1.52986199e-01 -6.91839218e-01 8.80153477e-02 9.81732130e-01 4.33633894e-01 -1.29794165e-01 -5.45020640e-01 -1.25524747e+00 8.11149180e-01 9.58377779e-01 3.13900441e-01 -8.92296076e-01 3.24661076e-01 1.80227593e-01 4.05416965e-01 1.31289765e-01 1.10292065e+00 4.10005115e-02 3.32519531e-01 -6.12858057e-01 6.99345097e-02 1.55378729e-01 6.89875305e-01 5.97297251e-01 4.72689301e-01 -8.72859001e-01 8.85968506e-01 2.55837977e-01 3.99571270e-01 6.29056275e-01 -1.40169597e+00 1.52023375e-01 9.23004866e-01 -1.17155880e-01 -1.00445998e+00 -5.82011938e-01 -5.96544027e-01 -7.18707442e-01 3.66466850e-01 4.26417440e-02 3.87536705e-01 -8.51771235e-01 1.56177604e+00 -2.09070399e-01 -2.26396263e-01 2.51153767e-01 9.69534039e-01 1.10821187e+00 2.43408069e-01 2.76425183e-01 5.23648560e-02 1.22392452e+00 -1.50490868e+00 -7.32168138e-01 -4.79133934e-01 1.22046843e-01 -1.80083364e-01 1.19187450e+00 1.29792243e-01 -1.69884586e+00 -8.92982900e-01 -8.79131615e-01 -4.98430669e-01 -6.55342758e-01 -3.54586095e-01 8.20526242e-01 2.59127796e-01 -1.63338661e+00 4.38842088e-01 -5.88917613e-01 -4.67779070e-01 8.44624937e-01 9.43248719e-02 -1.35754898e-01 -2.23418757e-01 -1.19497371e+00 1.37406898e+00 2.63063729e-01 -1.04924753e-01 -9.12902594e-01 -8.56998742e-01 -8.74953866e-01 4.91222590e-01 4.36159402e-01 -1.21172369e+00 1.04168868e+00 -7.13508487e-01 -1.22149086e+00 8.14899564e-01 -9.54202842e-03 -7.49064863e-01 2.62571007e-01 -1.38969257e-01 -1.62616253e-01 4.20152813e-01 -3.02593261e-02 8.13718438e-01 7.50691712e-01 -8.64184797e-01 -7.13419467e-02 -2.81653821e-01 6.78860188e-01 3.59682560e-01 -2.81951100e-01 -2.73317188e-01 -1.90401196e-01 -6.95900738e-01 2.92242095e-02 -5.64033151e-01 -2.78715372e-01 1.91968396e-01 1.27985433e-01 -2.84122735e-01 6.83720708e-01 -7.19481409e-01 6.84945047e-01 -2.22180033e+00 4.16392535e-01 -2.21715774e-02 9.37422037e-01 2.82648087e-01 -5.75574100e-01 2.97969639e-01 -1.98643595e-01 -1.49402648e-01 2.23525334e-02 -3.20875235e-02 1.76226437e-01 1.75773293e-01 -7.57227719e-01 7.69509748e-02 3.63375008e-01 1.96551311e+00 -9.68786240e-01 -2.52289981e-01 3.44905645e-01 4.20596689e-01 -7.19585896e-01 2.06809372e-01 -8.65145549e-02 1.10412180e-01 6.67470619e-02 3.76308769e-01 3.85352820e-01 -6.47963524e-01 -1.45064797e-02 -1.36957526e-01 2.58728247e-02 5.99857680e-02 -4.98478830e-01 1.83186364e+00 -4.63388801e-01 9.77629185e-01 -4.75157201e-01 -9.00225878e-01 9.10830438e-01 9.08950251e-03 -1.44155314e-02 -1.51524580e+00 3.13734002e-02 -5.68099320e-01 4.09199029e-01 -4.79037672e-01 6.57783866e-01 2.97570497e-01 2.28451371e-01 7.84054279e-01 3.44724417e-01 -3.91034670e-02 4.30209100e-01 6.13588572e-01 1.54734731e+00 3.69779021e-02 5.87538362e-01 -3.60062093e-01 3.00452381e-01 8.18812847e-02 -1.01160116e-01 1.15941119e+00 -2.75821745e-01 3.06650132e-01 1.26185149e-01 -6.63001239e-01 -9.19893146e-01 -1.52206111e+00 5.20982683e-01 1.66388750e+00 5.19271903e-02 -2.79749632e-01 -2.53215522e-01 -4.47566807e-01 2.66088382e-03 1.05437875e+00 -1.10944736e+00 -6.79936409e-01 -4.70119089e-01 -5.12320399e-01 3.16923022e-01 1.05701017e+00 8.65164280e-01 -1.66672051e+00 -1.12528265e+00 -4.30673361e-02 7.41034839e-03 -6.64498150e-01 -6.61265850e-02 2.76555773e-02 -6.33334339e-01 -1.24410021e+00 -7.89523721e-01 -6.13431633e-01 6.11354232e-01 7.31131375e-01 1.52258658e+00 4.73726898e-01 -7.34415710e-01 1.10693741e+00 -1.93079293e-01 -3.72403152e-02 -5.06434776e-02 -1.61921293e-01 -4.06061202e-01 -5.59920847e-01 1.96742162e-01 -6.09230161e-01 -6.15587294e-01 4.23387773e-02 -6.64080083e-01 2.38919467e-01 7.67144620e-01 7.26138473e-01 1.12736829e-01 -2.81443179e-01 4.93545413e-01 -4.49423254e-01 1.06879902e+00 -4.08839911e-01 -3.34645927e-01 5.15169024e-01 -2.83013195e-01 2.10435778e-01 4.00008142e-01 -4.47498381e-01 -1.33922768e+00 -4.61565197e-01 1.51720852e-01 -6.22889340e-01 2.87520200e-01 2.57225752e-01 3.31947595e-01 -2.58507133e-01 9.27910745e-01 6.40499234e-01 -2.09949970e-01 8.11671540e-02 6.78068638e-01 -2.34503821e-01 5.47041535e-01 -5.60694993e-01 7.12260842e-01 5.07540584e-01 -1.78868338e-01 -7.17201054e-01 -9.96063650e-01 -8.17219540e-02 -5.90997636e-01 -2.71701068e-01 8.37105453e-01 -8.98111522e-01 -1.38824797e+00 1.26570880e-01 -1.15186536e+00 -7.02637196e-01 -8.79513443e-01 1.05864234e-01 -8.32532167e-01 2.28340000e-01 -7.92883933e-01 -8.33980381e-01 -5.26487827e-01 -9.05245662e-01 4.93231833e-01 1.89550310e-01 -8.01303685e-01 -1.08465898e+00 1.44072905e-01 5.51728427e-01 1.06614065e+00 -3.51551384e-01 8.67734849e-01 -5.17316997e-01 -8.61809075e-01 4.63996500e-01 -7.06252337e-01 -2.61281908e-01 -3.09208870e-01 -5.09605169e-01 -9.29944932e-01 -1.72843441e-01 2.09108070e-02 -6.70920551e-01 1.52332842e+00 1.29480854e-01 1.31252098e+00 -1.18378624e-01 5.88233657e-02 6.04463577e-01 1.10411251e+00 4.77228343e-01 1.03046572e+00 3.50087047e-01 4.67701554e-01 4.51607287e-01 1.53963774e-01 3.38763624e-01 6.01433158e-01 1.70323387e-01 4.08347696e-01 -1.57883763e-01 -5.48272192e-01 -3.14977905e-03 -5.37695251e-02 4.77134138e-01 -5.16565084e-01 7.75418654e-02 -1.26963651e+00 5.36333144e-01 -1.84858930e+00 -1.46195722e+00 2.72638530e-01 1.56645715e+00 5.28406560e-01 2.32150592e-02 -1.04876257e-01 1.40196279e-01 5.01457453e-01 1.13149270e-01 -9.04661000e-01 -3.64826113e-01 -2.71706223e-01 5.33246100e-01 -5.19015454e-02 3.63040894e-01 -6.62829220e-01 9.99013484e-01 7.63817453e+00 4.07019198e-01 -5.15422463e-01 3.45207155e-01 1.02872446e-01 -2.33787671e-01 -2.40546077e-01 -3.73081028e-01 -1.77997977e-01 -2.16925338e-01 5.07630527e-01 -3.93194377e-01 9.87666488e-01 5.53063452e-01 -4.26031858e-01 -4.79439311e-02 -1.04542935e+00 1.05804777e+00 5.92448890e-01 -1.58042264e+00 1.49163723e-01 -2.59456038e-01 5.97005427e-01 -1.02750406e-01 4.38041121e-01 9.22808886e-01 9.24080312e-01 -1.12222517e+00 7.42157757e-01 1.02288306e+00 2.62912184e-01 -4.97320324e-01 2.44426310e-01 1.02926090e-01 -1.12618661e+00 -6.72319949e-01 -4.62786794e-01 -5.00019372e-01 -2.23345563e-01 -1.47363856e-01 -4.03108567e-01 7.17290118e-02 7.33972013e-01 7.15124905e-01 -1.11557472e+00 1.10011160e+00 -4.07960415e-01 -1.12237170e-01 3.83942783e-01 1.67590864e-02 8.09183158e-03 3.05057913e-01 3.99896532e-01 9.34640765e-01 4.78047383e-04 2.64285386e-01 -6.95092306e-02 1.39933765e+00 3.45679149e-02 -2.47100860e-01 -4.59733635e-01 -2.86354814e-02 4.77318257e-01 1.10578680e+00 -9.34063256e-01 -5.11069119e-01 -2.21568897e-01 1.18839943e+00 9.87183630e-01 4.98888254e-01 -9.47966874e-01 -1.50966123e-01 3.92442435e-01 -1.48754373e-01 4.11108613e-01 -2.23417789e-01 -2.77916253e-01 -1.08417451e+00 -4.74630207e-01 -6.22617364e-01 4.24069494e-01 -1.59236431e+00 -1.24779475e+00 5.14256954e-01 -1.88658699e-01 -5.49554825e-01 1.24217533e-02 -7.02080488e-01 -6.78845584e-01 7.14174688e-01 -1.20995712e+00 -1.02910995e+00 -7.32467771e-01 9.44039404e-01 7.47683287e-01 -5.76366782e-01 1.02832198e+00 -2.02588335e-01 -4.20495480e-01 3.57802391e-01 -4.09729332e-01 3.72384101e-01 2.04455048e-01 -1.13219321e+00 9.30638731e-01 5.84880054e-01 2.16664732e-01 1.08313334e+00 3.52153599e-01 -4.90427434e-01 -1.45901370e+00 -8.95074308e-01 2.25387439e-01 -6.15214705e-01 7.36257672e-01 -2.85997897e-01 -1.01586092e+00 9.82358277e-01 6.56438947e-01 -1.19869426e-01 6.26734436e-01 3.63000810e-01 -7.87206650e-01 3.67779583e-01 -1.21831453e+00 9.86334324e-01 1.62621629e+00 -6.92118406e-01 -1.56969118e+00 1.26475483e-01 8.44531298e-01 -1.19866274e-01 -5.10670900e-01 2.76275650e-02 4.85337794e-01 -1.23626864e+00 1.55847073e+00 -7.97063649e-01 4.77794588e-01 1.22370571e-01 -6.01882115e-02 -1.48199046e+00 -1.46486735e+00 -8.42443435e-04 -4.88280147e-01 7.67977595e-01 3.11329085e-02 -7.83390641e-01 5.19253790e-01 4.45710450e-01 -1.79698274e-01 -3.09657156e-01 -5.33128202e-01 -7.28718638e-01 -1.29000187e-01 -2.10429922e-01 5.50703168e-01 1.07057035e+00 2.06805497e-01 6.13163054e-01 8.34584758e-02 -3.39029253e-01 5.97619236e-01 8.29169899e-02 3.50589901e-01 -1.43783438e+00 -3.49206239e-01 -7.04032779e-01 -2.91937411e-01 -6.51866555e-01 4.71978009e-01 -1.03938794e+00 -4.45709020e-01 -2.01683855e+00 6.00397706e-01 3.18343163e-01 -3.67948532e-01 8.26564193e-01 -1.00739561e-01 4.60271537e-01 6.50298834e-01 1.85329005e-01 -1.20956910e+00 5.23275375e-01 1.31873965e+00 -5.27862132e-01 5.93074709e-02 -6.77950680e-01 -9.02168155e-01 7.47695804e-01 8.83056700e-01 1.45737723e-01 -6.96986020e-01 -5.68708777e-01 5.97642839e-01 7.24161342e-02 7.84372687e-01 -1.24747562e+00 4.25617844e-01 -9.67127234e-02 9.69290674e-01 -5.94643056e-01 6.00202858e-01 -7.66787350e-01 -1.28015801e-01 7.57783413e-01 -8.58922780e-01 3.94511938e-01 5.32284915e-01 3.45957160e-01 1.73870757e-01 7.77623057e-02 6.92991674e-01 -6.60283804e-01 -1.28170168e+00 -3.88902649e-02 -7.35991955e-01 2.85799086e-01 9.51335311e-01 -2.33594120e-01 -1.09921658e+00 -1.45262703e-01 -1.21284664e+00 2.23172322e-01 1.61444783e-01 4.71582234e-01 1.12143016e+00 -1.44637227e+00 -5.73830247e-01 2.96664834e-01 1.95298120e-01 -5.07617235e-01 7.67208815e-01 7.71085978e-01 -3.91139925e-01 5.16912341e-01 -8.13816428e-01 -1.09542601e-01 -9.73349512e-01 1.32816303e+00 3.74923497e-01 -1.45700261e-01 -7.49653697e-01 8.27799737e-01 5.47616720e-01 -1.88563406e-01 5.69420010e-02 4.58326302e-02 -5.58966815e-01 4.95156348e-02 9.11917508e-01 7.03428984e-01 -1.95549697e-01 -1.39898598e-01 -2.86944062e-01 2.80301750e-01 -1.05330810e-01 2.55774837e-02 1.23642170e+00 -1.13895990e-01 -2.41974130e-01 3.31708163e-01 5.35097122e-01 -3.21793169e-01 -1.06399679e+00 -3.71221840e-01 -4.57229204e-02 -2.89889157e-01 -1.10267460e-01 -1.13490868e+00 -1.10361600e+00 9.33478892e-01 4.32705969e-01 2.62449265e-01 1.06790340e+00 1.96314882e-02 9.11638066e-02 9.56555367e-01 1.64668903e-01 -8.07913423e-01 9.59185481e-01 9.97844875e-01 1.50174785e+00 -9.34644938e-01 -4.84153852e-02 1.50245562e-01 -6.86028898e-01 9.62918937e-01 1.03490078e+00 -4.88549620e-01 2.24162281e-01 2.01690733e-01 -3.03764582e-01 -4.07049209e-01 -1.19226384e+00 -6.22311652e-01 3.89816821e-01 8.62979710e-01 2.31403247e-01 -3.03901613e-01 2.57570416e-01 4.35328960e-01 -3.11394691e-01 9.54905227e-02 2.95686394e-01 7.07474470e-01 -5.98514438e-01 -9.02001783e-02 -5.39110482e-01 3.18122953e-01 1.52157873e-01 -4.76859540e-01 -4.87870693e-01 7.26709068e-01 -1.41621709e-01 6.95360959e-01 5.03030181e-01 -1.14903763e-01 3.60672385e-01 2.51578420e-01 9.80966628e-01 -5.34704387e-01 -7.86403835e-01 -6.50649309e-01 -2.57578313e-01 -6.00871205e-01 -1.61392227e-01 -3.77332509e-01 -1.14535594e+00 -5.07483780e-01 1.65102690e-01 -1.95554599e-01 -8.84958729e-02 8.27749491e-01 4.35583949e-01 1.31451344e+00 -1.65420249e-01 -7.01397240e-01 -3.62047732e-01 -9.13207650e-01 -2.75055289e-01 4.64686841e-01 9.41642299e-02 -8.23336720e-01 -1.46915734e-01 -3.05591613e-01]	[10.628929138183594, 2.237187623977661]
bd3b8fd5-0630-4f58-a208-0e4727b2dfd9	superocr-a-conversion-from-optical-character	2012.02033	null	https://arxiv.org/abs/2012.02033v1	https://arxiv.org/pdf/2012.02033v1.pdf	SuperOCR: A Conversion from Optical Character Recognition to Image Captioning	Optical Character Recognition (OCR) has many real world applications. The existing methods normally detect where the characters are, and then recognize the character for each detected location. Thus the accuracy of characters recognition is impacted by the performance of characters detection. In this paper, we propose a method for recognizing characters without detecting the location of each character. This is done by converting the OCR task into an image captioning task. One advantage of the proposed method is that the labeled bounding boxes for the characters are not needed during training. The experimental results show the proposed method outperforms the existing methods on both the license plate recognition and the watermeter character recognition tasks. The proposed method is also deployed into a low-power (300mW) CNN accelerator chip connected to a Raspberry Pi 3 for on-device applications.	['Lin Yang', 'Hao Sha', 'Michael Lin', 'Baohua Sun']	2020-11-21	null	null	null	null	['license-plate-recognition']	['computer-vision']	[ 4.73863721e-01 -5.70995510e-01 -3.01571824e-02 -2.35970840e-01 1.05776213e-01 -7.19707072e-01 2.25759059e-01 8.54481361e-04 -5.19105136e-01 3.64502043e-01 -5.60664296e-01 -4.79564965e-01 5.30868411e-01 -7.55839229e-01 -4.03019249e-01 -7.09770501e-01 5.73085964e-01 2.66275167e-01 7.29717731e-01 2.69096226e-01 6.94561839e-01 9.91872549e-01 -1.35276830e+00 3.61068070e-01 6.13852084e-01 1.09625840e+00 4.59362507e-01 8.16992581e-01 -1.10775247e-01 9.41044867e-01 -1.00677919e+00 6.24305243e-03 2.41851717e-01 -1.53144047e-01 2.83205267e-02 3.44560891e-01 2.49946043e-01 -5.40739059e-01 -3.54160428e-01 1.19199872e+00 1.98893160e-01 -1.15220128e-02 5.33922493e-01 -1.23603368e+00 -6.18511617e-01 6.94486573e-02 -7.49632120e-01 2.68334955e-01 -5.36557324e-02 -3.38544361e-02 3.32290322e-01 -5.17769635e-01 1.17318347e-01 8.86494756e-01 6.36657417e-01 6.14279985e-01 -4.02711630e-01 -8.07090163e-01 -2.62050182e-01 2.67402232e-01 -1.42620683e+00 -2.67904162e-01 5.79714894e-01 -4.78627563e-01 1.03994858e+00 2.97821552e-01 3.76914203e-01 3.88145924e-01 3.86971354e-01 6.88179791e-01 1.05186093e+00 -6.72098935e-01 2.90023744e-01 3.63622934e-01 5.59957027e-01 6.19768202e-01 5.18247485e-01 -3.63920718e-01 2.03085784e-02 5.25711104e-02 9.60512638e-01 5.65758705e-01 5.27296066e-02 2.77738273e-01 -8.73490512e-01 4.24714148e-01 4.62837517e-02 1.75607234e-01 3.57916839e-02 2.51952559e-01 3.57815444e-01 -2.98179537e-01 3.74371652e-03 1.10194005e-01 -1.24646492e-01 -1.61205575e-01 -9.79337752e-01 -1.56604275e-01 6.92434430e-01 1.13131940e+00 5.22782922e-01 2.49428466e-01 -8.59757140e-02 7.66989648e-01 5.69510996e-01 5.87502718e-01 7.18838692e-01 -1.02555826e-01 3.82930279e-01 8.46309483e-01 2.74527222e-01 -1.04296529e+00 -2.65333176e-01 1.16403848e-01 -4.76499289e-01 3.79240036e-01 4.16256428e-01 -2.57282704e-01 -1.13726473e+00 7.14906216e-01 3.68905514e-02 1.98830530e-01 2.00924084e-01 1.11622918e+00 6.47384465e-01 1.27541602e+00 -8.03546011e-02 3.48015904e-01 1.69076002e+00 -1.13403904e+00 -7.31360078e-01 -6.06914997e-01 3.64139169e-01 -1.04475474e+00 8.23141873e-01 2.69716114e-01 -3.41317773e-01 -7.10751235e-01 -1.41098952e+00 -1.53925329e-01 -5.35319924e-01 1.04587650e+00 4.84049976e-01 1.14919531e+00 -5.16085327e-01 1.71723843e-01 -8.55346680e-01 -2.80806422e-01 1.25251487e-01 5.80584347e-01 -6.59730211e-02 5.26150204e-02 -5.78890502e-01 6.74678087e-01 4.59153414e-01 4.43552375e-01 -4.79212105e-01 4.34489101e-02 -6.15216255e-01 1.94033980e-01 -4.80793566e-02 3.85818750e-01 1.12520349e+00 -1.35875678e+00 -1.59346259e+00 6.55561030e-01 -7.18392134e-02 -2.16247559e-01 3.28543514e-01 7.91466702e-03 -6.85830534e-01 1.83876440e-01 -3.38874429e-01 4.01293665e-01 7.95561731e-01 -7.93801665e-01 -8.16820920e-01 -2.99215317e-01 -3.29997897e-01 7.87857994e-02 -4.40406024e-01 2.63753116e-01 -7.45963573e-01 -3.31029296e-01 -1.08428886e-02 -9.06063557e-01 1.33836687e-01 1.53921977e-01 -5.74313045e-01 -2.54384905e-01 1.60701573e+00 -6.31857216e-01 7.50040114e-01 -2.29003906e+00 -8.54123116e-01 1.84306070e-01 -3.62020999e-01 7.86041796e-01 1.40941799e-01 2.03024343e-01 2.50127129e-02 -2.33298764e-01 1.39178738e-01 -2.04069987e-01 -3.02188337e-01 9.92553979e-02 -5.11403322e-01 7.92011082e-01 1.73812166e-01 4.44596618e-01 -1.41766861e-01 -3.53403211e-01 4.19359237e-01 5.27572751e-01 -3.41501050e-02 1.08953141e-01 4.13433239e-02 -1.95772186e-01 -4.44961369e-01 8.81034732e-01 9.59455669e-01 -5.45847006e-02 1.52816281e-01 2.46186573e-02 -3.61109614e-01 -1.69609308e-01 -1.34785986e+00 7.44544506e-01 -3.65224741e-02 1.13177705e+00 -2.00373635e-01 -7.68628776e-01 1.45540786e+00 1.04043096e-01 -3.92561108e-02 -6.38599157e-01 2.87597239e-01 2.05587357e-01 8.53193998e-02 -4.97098058e-01 7.95823872e-01 1.29286051e-01 1.50784299e-01 2.75377572e-01 -5.26308060e-01 2.20427290e-01 1.14383653e-01 -2.03507647e-01 7.48554826e-01 2.47492492e-02 1.01665452e-01 -2.11120859e-01 5.27428687e-01 4.64123160e-01 6.73517287e-01 6.51133299e-01 -1.48305908e-01 5.34449100e-01 2.28610069e-01 -5.90054810e-01 -1.40693915e+00 -5.29044211e-01 -1.82619825e-01 6.53175652e-01 4.39100593e-01 1.16037406e-01 -8.46235991e-01 -4.23256338e-01 -1.06632650e-01 5.62076807e-01 -1.26992226e-01 1.50767908e-01 -7.17890263e-01 -6.38364851e-01 7.60480285e-01 7.84811139e-01 6.96986973e-01 -1.27614951e+00 -1.11914814e+00 9.44066569e-02 3.93654376e-01 -1.29054344e+00 -5.17188728e-01 -4.42027077e-02 -8.72482419e-01 -7.63423026e-01 -7.34352291e-01 -1.43063009e+00 1.04842031e+00 4.68736142e-01 3.49427044e-01 3.06069493e-01 -5.62655389e-01 -7.00942650e-02 -3.47294450e-01 -6.20297492e-01 -2.69328296e-01 -9.02186781e-02 -4.49475497e-02 1.88517898e-01 7.16234505e-01 1.05523560e-02 -6.55137837e-01 6.07766151e-01 -8.61141026e-01 1.04716875e-01 8.54882598e-01 3.92920524e-01 3.69817585e-01 1.99908927e-01 2.28291661e-01 -8.52298319e-01 4.53737944e-01 4.13449481e-02 -1.26419127e+00 2.52988338e-01 -4.11308855e-01 -2.28585169e-01 1.01850832e+00 -7.20742106e-01 -8.29006672e-01 6.75569594e-01 1.60804421e-01 -2.05953702e-01 -3.69369090e-01 4.56245840e-02 -2.16460079e-01 -2.09778294e-01 2.15018436e-01 5.56553483e-01 -5.06204441e-02 -3.74443382e-01 -3.91851157e-01 1.31694007e+00 5.85184038e-01 -1.97670609e-01 6.28957391e-01 3.34419012e-01 -1.46680966e-01 -1.15063989e+00 -1.03470194e-03 -5.82643688e-01 -2.81686574e-01 -3.19256395e-01 8.05463195e-01 -9.21374142e-01 -1.04249442e+00 8.44098926e-01 -1.30837572e+00 -5.49774803e-02 3.36942673e-01 4.26542848e-01 -7.92100187e-03 6.57929003e-01 -6.44371569e-01 -1.15682507e+00 -5.64157963e-01 -1.31145298e+00 8.24970424e-01 9.03054178e-01 2.37709001e-01 -6.06650770e-01 -2.43050635e-01 2.07662478e-01 4.69475210e-01 -1.33184209e-01 6.98555052e-01 -7.63908148e-01 -6.67857885e-01 -1.02668810e+00 -5.92800319e-01 3.08070868e-01 1.25004426e-02 3.29512686e-01 -8.16370189e-01 -1.20422803e-01 -1.09501332e-02 -4.58386689e-02 4.52324420e-01 1.35045588e-01 1.23145211e+00 -2.71618456e-01 -5.34402013e-01 3.30673218e-01 1.76858294e+00 9.29085672e-01 1.25849760e+00 4.70991194e-01 8.48267794e-01 1.86587125e-01 5.53724051e-01 2.56150782e-01 -2.33704954e-01 5.74195683e-01 2.00677902e-01 -1.92001387e-01 1.28440797e-01 5.51410913e-02 5.66437304e-01 4.90317136e-01 1.51516631e-01 -5.91303885e-01 -1.10473967e+00 2.66126335e-01 -1.69266796e+00 -7.79078364e-01 -4.36551362e-01 2.01599932e+00 4.20884788e-01 1.11984529e-01 -2.22221419e-01 1.76920161e-01 1.28659046e+00 -2.72127420e-01 -5.79247475e-01 -6.46602929e-01 1.60098389e-01 -2.49927789e-02 8.96581650e-01 1.25179172e-01 -1.09780145e+00 8.47682893e-01 6.11463356e+00 7.37775564e-01 -1.54904974e+00 -3.63202631e-01 7.72783101e-01 3.86682212e-01 5.46739817e-01 -1.27656505e-01 -1.27523851e+00 6.42992139e-01 7.17056811e-01 2.92877853e-01 1.07620470e-01 1.23177171e+00 1.79762021e-01 -5.14568090e-01 -9.57465410e-01 1.03683567e+00 3.04566443e-01 -1.09539056e+00 -5.67249916e-02 -3.28235812e-02 2.94628114e-01 -2.43453175e-01 9.97623149e-03 9.85587295e-03 -2.63022929e-01 -8.71545613e-01 7.71395385e-01 2.24909827e-01 7.45934606e-01 -7.97233999e-01 8.37127328e-01 4.76964653e-01 -9.78074133e-01 -5.21357208e-02 -8.47727537e-01 -2.20596686e-01 -2.06319124e-01 3.57041270e-01 -1.14426219e+00 -4.36557829e-01 3.61595750e-01 2.78600991e-01 -6.28747046e-01 1.41217577e+00 -2.46542618e-02 7.84684777e-01 -2.78229952e-01 -7.62072086e-01 1.93200529e-01 -2.60745555e-01 1.44341782e-01 1.50425577e+00 5.35275102e-01 1.94786444e-01 4.51077186e-02 8.23017001e-01 1.07962370e-01 1.29480422e-01 -2.00317085e-01 -3.38270754e-01 2.97377437e-01 1.51494217e+00 -1.34688151e+00 -3.47675443e-01 -4.02227402e-01 1.30736220e+00 -3.13144714e-01 -2.94318255e-02 -1.09471524e+00 -1.21222031e+00 2.40033329e-01 2.27990121e-01 4.07863677e-01 -5.12133121e-01 -2.56026477e-01 -9.35997546e-01 1.68091819e-01 -5.60168386e-01 -2.29691081e-02 -9.51260746e-01 -7.79603541e-01 4.59800452e-01 -6.04303718e-01 -1.46229470e+00 1.76277295e-01 -1.35271776e+00 -8.31717849e-01 9.09233510e-01 -1.37186897e+00 -8.07358801e-01 -6.04494393e-01 2.53238201e-01 5.97195327e-01 -2.89587259e-01 7.08703458e-01 3.56174499e-01 -1.06982327e+00 6.67645633e-01 4.48742896e-01 9.10277367e-01 5.17115116e-01 -8.03054154e-01 4.39920336e-01 1.14701295e+00 -1.98719054e-01 5.40915549e-01 4.67374504e-01 -7.19681144e-01 -1.53055477e+00 -1.02816045e+00 6.66873395e-01 1.52403101e-01 2.44555891e-01 -6.46952987e-01 -6.43392205e-01 6.06194615e-01 1.26540586e-01 1.88035682e-01 5.82585573e-01 -5.96461654e-01 -2.08574563e-01 -1.92930415e-01 -1.44669259e+00 5.76863766e-01 2.22231913e-02 -2.46390596e-01 -2.04971388e-01 4.58296239e-01 1.98157981e-01 -4.70093280e-01 -1.57760113e-01 -2.93888658e-01 7.25640476e-01 -5.84198534e-01 6.19717062e-01 -1.39718264e-01 4.43501800e-01 -8.93258393e-01 -4.81684841e-02 -5.32619298e-01 -1.33817494e-01 -1.34920299e-01 3.40871930e-01 1.16780603e+00 4.97421831e-01 -5.22726715e-01 1.13398099e+00 9.09456730e-01 -8.96520466e-02 -1.57768324e-01 -8.24181139e-01 -6.65573001e-01 -4.91147310e-01 4.15843911e-03 2.48415232e-01 6.41299665e-01 4.43454757e-02 3.52658741e-02 -4.03851122e-01 5.22478998e-01 3.61939102e-01 9.89865959e-02 4.58938420e-01 -8.13428104e-01 -3.95271719e-01 -1.18124992e-01 -1.00871038e+00 -1.07616949e+00 -3.71277422e-01 -3.93740147e-01 3.34090114e-01 -1.29364467e+00 3.53957474e-01 -3.48467439e-01 -6.71668947e-02 5.42334616e-01 6.52698874e-02 4.83060837e-01 1.82543427e-01 3.78962934e-01 -5.25804758e-01 -1.14605971e-01 7.54501581e-01 -2.51213640e-01 -1.00041315e-01 9.30229053e-02 -1.22240126e-01 6.52285755e-01 9.93529558e-01 -5.38596749e-01 -4.43589501e-02 -5.73271036e-01 -2.49153987e-01 -1.32585913e-01 2.50864297e-01 -1.56023979e+00 6.64829671e-01 -1.43403754e-01 9.33060408e-01 -8.47112775e-01 2.64785081e-01 -1.10116374e+00 -1.60116091e-01 7.79728293e-01 1.43745258e-01 3.50477964e-01 5.26078820e-01 2.68574148e-01 -3.36103258e-03 -8.36344779e-01 1.05589569e+00 2.24440754e-03 -1.05695224e+00 -2.20253989e-01 -9.17131543e-01 -7.02376366e-01 1.37314034e+00 -6.97530687e-01 -6.36382699e-01 -4.94580232e-02 -1.06850594e-01 -2.66655445e-01 3.61741871e-01 1.76177472e-01 8.23636532e-01 -1.01115263e+00 -2.89873213e-01 3.44479412e-01 7.00882673e-02 -1.39223799e-01 1.59444749e-01 2.70270854e-01 -1.46106029e+00 5.76043248e-01 -5.13588548e-01 -6.06393814e-01 -1.57265508e+00 4.26554859e-01 3.71544749e-01 2.21018031e-01 -5.80844402e-01 4.13724124e-01 -2.43103772e-01 -2.35289074e-02 3.45911473e-01 -3.35960209e-01 -3.57392132e-01 -4.18325990e-01 9.70894396e-01 3.08662176e-01 -2.65954621e-02 -4.76739883e-01 -4.07079607e-01 6.42245650e-01 -4.15684640e-01 4.22134390e-03 1.15338397e+00 4.07083869e-01 -1.57402188e-01 2.61548370e-01 9.96426105e-01 8.03188682e-02 -1.13666677e+00 2.00314164e-01 -2.80047879e-02 -4.37449336e-01 -3.22731808e-02 -7.20884085e-01 -1.11270881e+00 9.55689609e-01 1.07990360e+00 -7.17282156e-03 9.55507755e-01 -7.06015825e-01 7.16720283e-01 6.52167499e-01 1.83236986e-01 -1.26388240e+00 -1.02478929e-01 4.59477544e-01 2.26633593e-01 -9.83911514e-01 1.73423346e-02 -4.11977053e-01 -7.60558605e-01 1.72274685e+00 9.48428094e-01 -4.26238596e-01 3.42434347e-01 7.67706335e-01 2.45436579e-01 1.32743791e-01 -1.00422449e-01 2.72028059e-01 -3.17779370e-02 4.41274941e-01 3.47618103e-01 2.10769936e-01 -7.34157339e-02 5.00212491e-01 1.96924433e-01 -6.22854978e-02 1.03576577e+00 1.18032300e+00 -7.14799047e-01 -8.84168804e-01 -7.75496125e-01 2.69091278e-01 -5.91114044e-01 -4.10275795e-02 -4.71053302e-01 4.76766139e-01 2.81078629e-02 9.10189152e-01 6.81857288e-01 -4.60385233e-01 1.69539601e-01 -5.88362738e-02 -1.55675830e-02 -4.93562818e-01 -4.54406261e-01 4.05253582e-02 -2.93681592e-01 3.64455059e-02 4.44986001e-02 -4.86716717e-01 -1.41183543e+00 -2.63084114e-01 -5.94151437e-01 1.04159471e-02 1.16029334e+00 6.32198453e-01 3.23886216e-01 4.06735271e-01 6.30103767e-01 -6.19095981e-01 -2.45703548e-01 -8.57242465e-01 -6.06900573e-01 1.12731405e-01 -7.67625049e-02 -1.02752961e-01 -1.01896204e-01 2.31057946e-02]	[9.843330383300781, -4.929326057434082]
5d5229c5-f6be-4937-b155-2495de52d3ab	decoding-visemes-improving-machine-lipreading	1710.01288	null	http://arxiv.org/abs/1710.01288v1	http://arxiv.org/pdf/1710.01288v1.pdf	Decoding visemes: improving machine lipreading	Machine lipreading (MLR) is speech recognition from visual cues and a niche research problem in speech processing & computer vision. Current challenges fall into two groups: the content of the video, such as rate of speech or; the parameters of the video recording e.g, video resolution. We show that HD video is not needed to successfully lipread with a computer. The term "viseme" is used in machine lipreading to represent a visual cue or gesture which corresponds to a subgroup of phonemes where the phonemes are visually indistinguishable. A phoneme is the smallest sound one can utter, because there are more phonemes per viseme, maps between units show a many-to-one relationship. Many maps have been presented, we compare these and our results show Lee's is best. We propose a new method of speaker-dependent phoneme-to-viseme maps and compare these to Lee's. Our results show the sensitivity of phoneme clustering and we use our new knowledge to augment a conventional MLR system. It has been observed in MLR, that classifiers need training on test subjects to achieve accuracy. Thus machine lipreading is highly speaker-dependent. Conversely speaker independence is robust classification of non-training speakers. We investigate the dependence of phoneme-to-viseme maps between speakers and show there is not a high variability of visemes, but there is high variability in trajectory between visemes of individual speakers with the same ground truth. This implies a dependency upon the number of visemes within each set for each individual. We show that prior phoneme-to-viseme maps rarely have enough visemes and the optimal size, which varies by speaker, ranges from 11-35. Finally we decode from visemes back to phonemes and into words. Our novel approach uses the optimum range visemes within hierarchical training of phoneme classifiers and demonstrates a significant increase in classification accuracy.	['Helen L. Bear']	2017-10-03	null	null	null	null	['lipreading']	['computer-vision']	[ 2.94889122e-01 -2.23306403e-01 -3.52062315e-01 -1.23646140e-01 -8.82520795e-01 -4.84093726e-01 6.00154102e-01 -2.55310655e-01 -2.91625082e-01 6.64015472e-01 4.28665370e-01 -5.02110064e-01 1.56036600e-01 -1.98445886e-01 -7.45346963e-01 -8.18697989e-01 1.41255304e-01 1.52156204e-01 3.05484176e-01 -1.92345589e-01 4.49050754e-01 4.66558725e-01 -2.29873919e+00 5.10760486e-01 5.12914240e-01 6.93265617e-01 5.72833717e-01 1.28752077e+00 -3.57263476e-01 1.63319141e-01 -6.13344669e-01 7.71016553e-02 1.95444107e-01 -6.30981863e-01 -5.07021070e-01 3.30632001e-01 5.53471029e-01 -2.04267260e-02 8.54602642e-03 1.05618787e+00 6.79663301e-01 -1.34262055e-01 1.18122351e+00 -1.31870949e+00 -6.12054706e-01 3.63720447e-01 -4.81374025e-01 1.70834005e-01 6.69620931e-01 2.83781532e-02 4.01561856e-01 -9.47638512e-01 3.98542851e-01 1.35340428e+00 4.84196782e-01 9.14393246e-01 -9.67982292e-01 -5.22617638e-01 -2.36008346e-01 4.20379788e-01 -1.58219802e+00 -1.03473103e+00 5.31365156e-01 -5.96057057e-01 9.68311250e-01 6.03839099e-01 5.81295907e-01 8.72952878e-01 7.97365606e-03 4.25706923e-01 1.39058077e+00 -9.61954355e-01 7.63554499e-02 6.15573764e-01 8.83894321e-03 5.57002485e-01 -2.03269884e-01 1.23609275e-01 -6.65720701e-01 4.33817983e-01 5.37068784e-01 -4.74181980e-01 -6.41786873e-01 -4.31509353e-02 -1.04569602e+00 6.34505510e-01 -2.50378609e-01 4.64145988e-01 6.71772212e-02 -2.39390388e-01 2.79676110e-01 3.50057393e-01 3.27433757e-02 -2.70447671e-01 -1.77978203e-01 -2.82205522e-01 -1.00625086e+00 -5.01963913e-01 7.06357956e-01 8.44768226e-01 6.73097730e-01 2.72110440e-02 2.55008161e-01 1.34472394e+00 4.37033981e-01 6.34170890e-01 9.91844893e-01 -6.51748717e-01 4.53400433e-01 1.68515980e-01 -2.42130324e-01 -5.26191413e-01 -9.86503884e-02 5.01716912e-01 -5.35487175e-01 8.52716029e-01 5.48208237e-01 1.70590162e-01 -1.19957507e+00 1.60480392e+00 6.88975304e-02 1.46291554e-01 2.46136427e-01 6.82544053e-01 1.00517702e+00 7.57896245e-01 -1.30577877e-01 -6.21158481e-01 1.52634954e+00 -7.04581261e-01 -9.54845011e-01 4.53665219e-02 4.21739399e-01 -1.13768709e+00 1.37775135e+00 4.01259720e-01 -1.21460533e+00 -5.82848787e-01 -1.12387776e+00 6.26218617e-02 -8.45618665e-01 2.60563105e-01 4.58913669e-02 1.31613493e+00 -1.56062698e+00 1.34594679e-01 -1.76798001e-01 -6.93507075e-01 5.88875599e-02 6.55909717e-01 -7.14672148e-01 2.45964006e-01 -7.47059166e-01 1.10469735e+00 3.64664733e-01 -1.30206212e-01 -6.08556271e-01 -1.38797343e-01 -8.34657788e-01 -1.49813727e-01 -5.31058609e-02 -2.29765698e-01 9.63812232e-01 -1.06874788e+00 -1.99881864e+00 1.26958621e+00 -7.80185521e-01 -1.46196380e-01 4.38407183e-01 5.40392399e-01 -7.99384654e-01 2.73791343e-01 -3.95771652e-01 9.08318877e-01 1.13842559e+00 -1.60436475e+00 -7.72909105e-01 -1.38621375e-01 -5.42890072e-01 4.07031804e-01 -7.18665943e-02 4.20707166e-01 -4.67638612e-01 -2.77436972e-01 8.82886425e-02 -6.85312033e-01 8.53125989e-01 -2.99626023e-01 -2.58918613e-01 -5.18886983e-01 9.17898595e-01 -8.72038543e-01 1.01209617e+00 -2.18051338e+00 -1.65075913e-01 7.34280720e-02 5.38380519e-02 2.95549601e-01 -3.63212754e-03 2.17464700e-01 -3.29929978e-01 4.14724261e-01 -1.71009988e-01 -4.11207795e-01 1.03160098e-01 1.47313252e-01 -7.96542596e-03 7.27925122e-01 -2.85707980e-01 5.61711788e-01 -3.11583579e-01 -9.29464102e-01 6.29939377e-01 7.08554149e-01 -1.88776821e-01 7.45571777e-02 3.07145298e-01 -5.92293888e-02 4.35881943e-01 7.23528862e-01 8.80661428e-01 3.05875480e-01 -2.99888998e-01 -1.14388891e-01 -3.43374580e-01 2.77437925e-01 -1.15020072e+00 1.19446754e+00 -4.28430527e-01 1.39296937e+00 3.97313029e-01 -8.99061680e-01 9.16956306e-01 6.63383663e-01 6.74841404e-02 -3.08696389e-01 1.57210365e-01 4.01669919e-01 1.49950236e-01 -8.07822466e-01 3.06991607e-01 -2.47524798e-01 5.00273824e-01 1.73163146e-01 -3.98944467e-02 -2.02503368e-01 5.55642508e-02 -1.59441665e-01 3.81182760e-01 -3.75753969e-01 4.12261873e-01 -4.21983451e-01 8.83884549e-01 -5.03419638e-01 4.09572087e-02 5.23894727e-01 -4.86307114e-01 9.36423361e-01 1.73166648e-01 3.66756648e-01 -9.16936874e-01 -1.22996616e+00 -5.81697345e-01 1.20182467e+00 1.09179609e-01 -9.84566063e-02 -1.14266050e+00 -2.72028983e-01 -3.36087018e-01 5.48118472e-01 -5.59088707e-01 2.58282959e-01 -3.96013558e-01 -3.63695860e-01 5.79803705e-01 3.38643007e-02 3.15879434e-01 -1.34238756e+00 -2.37768397e-01 -2.06584886e-01 -2.16411158e-01 -1.03006029e+00 -6.56135976e-01 -8.29258934e-02 -4.67736930e-01 -7.72534311e-01 -9.56417441e-01 -1.34144258e+00 5.16164422e-01 3.14081162e-01 8.42203259e-01 1.45737967e-02 -2.04609543e-01 6.24128580e-01 -2.48332173e-01 -4.95356858e-01 -9.87878323e-01 -2.98893839e-01 4.86456960e-01 -3.86045221e-03 5.70123017e-01 -3.90198708e-01 -4.60542411e-01 5.29430747e-01 -5.11135459e-01 -8.19679499e-02 4.25438792e-01 4.41345125e-01 3.49063843e-01 -2.38990337e-02 5.36842406e-01 -1.44780487e-01 6.29423857e-01 -2.69828826e-01 -2.95516521e-01 4.14756149e-01 -3.87517482e-01 -2.49074951e-01 3.23446482e-01 -5.96171200e-01 -6.75177217e-01 4.02590819e-02 -1.89290345e-01 -3.94962192e-01 -7.11097896e-01 -2.89604783e-01 -4.76849914e-01 -1.41677037e-01 5.82230508e-01 5.32143474e-01 3.19660038e-01 -4.50031042e-01 2.86701977e-01 1.52377141e+00 7.80160189e-01 -3.06235533e-02 4.09446239e-01 3.35459709e-01 -3.11603874e-01 -1.61205459e+00 4.78877485e-01 -8.22485864e-01 -5.51069736e-01 -5.53583980e-01 1.16348863e+00 -5.86932302e-01 -1.13955677e+00 6.59672201e-01 -1.05425763e+00 -2.95366943e-01 -3.93244661e-02 7.32845485e-01 -7.96624660e-01 6.08843148e-01 -3.21753830e-01 -1.20493162e+00 -2.92532835e-02 -1.46720386e+00 8.88052702e-01 2.94286996e-01 1.10689858e-02 -1.00606108e+00 -7.04354048e-02 4.68880922e-01 2.30536461e-02 -4.27109033e-01 7.87595749e-01 -5.22698760e-01 -3.10852379e-01 1.37078613e-01 -2.15169251e-01 4.84069109e-01 5.70756257e-01 2.79908597e-01 -1.28852630e+00 -2.09910959e-01 -6.25055730e-02 -1.03417397e-01 9.18100417e-01 8.49914730e-01 9.08875942e-01 -3.73165488e-01 -4.46986824e-01 4.05493438e-01 1.22905564e+00 5.48680425e-01 9.10608351e-01 9.61055979e-02 5.53766727e-01 1.06533384e+00 1.08499087e-01 -1.78210303e-01 1.73334345e-01 8.23020458e-01 1.08556926e-01 -1.12992465e-01 -7.40032077e-01 -2.15598196e-01 8.58409941e-01 1.06955421e+00 -1.07286371e-01 -5.20477474e-01 -8.01633239e-01 5.89423835e-01 -1.11384821e+00 -1.11756814e+00 -9.76756960e-02 2.57725596e+00 7.05533385e-01 -3.50038446e-02 4.97599542e-01 7.00199425e-01 1.37074518e+00 -1.36147425e-01 -1.64620131e-02 -8.42888117e-01 -3.84991080e-01 -7.37838969e-02 5.50997138e-01 1.18064630e+00 -6.43257856e-01 1.09275031e+00 7.17150497e+00 1.15050435e+00 -1.43392193e+00 6.93839937e-02 3.22489947e-01 9.18949544e-02 -1.13487363e-01 -3.69242013e-01 -9.63081539e-01 6.95314944e-01 9.64691937e-01 1.05854526e-01 6.22577369e-01 3.03427637e-01 5.35703063e-01 -4.08222556e-01 -1.11640108e+00 1.64962173e+00 6.37969911e-01 -1.09183919e+00 4.72235680e-02 2.79153347e-01 3.15600276e-01 -1.16040654e-01 2.45969832e-01 -5.41886017e-02 -2.07275569e-01 -1.47975194e+00 6.60543382e-01 2.57401615e-01 1.26357532e+00 -4.92084295e-01 2.73667276e-01 2.08227634e-01 -1.43513346e+00 1.73067585e-01 -4.31284547e-01 4.13360685e-01 9.18832049e-02 -2.30778098e-01 -1.25037301e+00 -9.31689590e-02 5.23013175e-01 2.29684144e-01 -4.44002479e-01 1.12513304e+00 1.93715185e-01 5.27864277e-01 -3.39711189e-01 -2.43190870e-01 -1.21293753e-01 -1.07204251e-01 7.92453945e-01 1.58293509e+00 4.54321444e-01 5.55872656e-02 -3.84225518e-01 4.65018123e-01 2.65866905e-01 5.39153397e-01 -8.06963921e-01 2.66020268e-01 5.67752957e-01 9.13617313e-01 -7.24986613e-01 -2.88970977e-01 -3.66658390e-01 9.30824220e-01 -3.55930775e-01 4.19321984e-01 -4.20952559e-01 -3.43184412e-01 5.37404776e-01 2.84298450e-01 2.38562569e-01 -5.34413457e-02 -2.68449157e-01 -7.67056704e-01 -1.42906595e-03 -9.22107637e-01 2.49112248e-02 -9.84271944e-01 -9.67160106e-01 5.65077066e-01 -1.84449404e-02 -1.19334757e+00 -4.30302173e-01 -9.61528718e-01 -6.77870750e-01 9.75768745e-01 -1.39117885e+00 -8.58922243e-01 -1.76288471e-01 9.73000228e-01 9.27330196e-01 -6.16560817e-01 6.12129211e-01 2.89126728e-02 -3.03186804e-01 8.95962298e-01 9.40772295e-02 3.84192206e-02 7.63524234e-01 -1.21363938e+00 -1.22369520e-01 6.12497330e-01 2.83725411e-01 3.31809759e-01 7.63271868e-01 -3.99853975e-01 -9.97597456e-01 -3.47051948e-01 1.05038404e+00 -5.22712648e-01 2.30599433e-01 -6.18364215e-01 -8.58203232e-01 2.43501306e-01 4.96659279e-01 -3.89744341e-01 7.04136193e-01 -1.68569326e-01 -2.61970311e-01 -1.34792507e-01 -1.20939600e+00 5.71620286e-01 8.33088219e-01 -9.29608226e-01 -6.76294684e-01 2.25162342e-01 4.41333741e-01 6.42035678e-02 -3.90671164e-01 8.76799151e-02 7.83321202e-01 -1.30817819e+00 9.65888083e-01 -3.99093479e-02 -1.52090207e-01 -3.65306884e-01 -3.79536808e-01 -1.09483767e+00 2.26660013e-01 -7.16517329e-01 2.74503648e-01 1.50643861e+00 5.87645769e-01 -7.85585701e-01 7.47219443e-01 2.00811401e-01 -1.44144699e-01 -2.49487370e-01 -1.22032666e+00 -9.78605270e-01 1.88004896e-01 -5.29064953e-01 3.19248408e-01 8.45826626e-01 3.34511280e-01 9.15446952e-02 -2.40383685e-01 1.61087364e-01 5.78540742e-01 -4.56669688e-01 5.94969213e-01 -1.10563087e+00 -1.91662312e-01 -8.31228971e-01 -6.42676771e-01 -1.09238946e+00 2.09193632e-01 -8.37815762e-01 2.41578549e-01 -1.46842122e+00 1.76281765e-01 -2.71072716e-01 -1.07122853e-01 1.67991713e-01 1.51471794e-01 3.01511973e-01 2.38788679e-01 3.00308496e-01 1.07010081e-01 -1.61027387e-02 9.81487632e-01 -1.69310912e-01 -6.01813495e-01 1.52292391e-02 -9.97331291e-02 7.21889913e-01 9.25730884e-01 -1.02449961e-01 -4.38174754e-01 6.43726364e-02 -2.44590834e-01 1.78478315e-01 2.36836538e-01 -1.05964112e+00 3.07715714e-01 7.88690969e-02 1.30510569e-01 -7.86640465e-01 6.68203115e-01 -7.51392722e-01 -1.34397462e-01 1.57442659e-01 -1.13427959e-01 -1.25149116e-02 1.76806346e-01 3.72425526e-01 -1.40277728e-01 -4.80105460e-01 1.07219613e+00 5.72286099e-02 -6.55445814e-01 -6.83898628e-02 -8.06987643e-01 -1.54753581e-01 9.37464297e-01 -1.07211256e+00 -3.08158398e-01 -6.61000490e-01 -7.34616458e-01 -4.26120251e-01 4.83708650e-01 5.00928640e-01 6.77255630e-01 -1.10190761e+00 -6.77293181e-01 3.82989615e-01 -3.84404026e-02 -6.90413177e-01 5.33550195e-02 8.56600821e-01 -5.60946584e-01 4.60562944e-01 -3.65480244e-01 -9.81402159e-01 -2.10268855e+00 5.50911248e-01 4.95595396e-01 7.70925403e-01 -3.09463799e-01 8.84298921e-01 3.97959650e-01 2.72802357e-02 4.81898814e-01 -3.37090045e-01 -6.00339532e-01 3.26584637e-01 5.11061311e-01 5.80043614e-01 -8.17865953e-02 -1.21938682e+00 -3.95012856e-01 1.20951259e+00 6.11092821e-02 -6.03177786e-01 5.91011345e-01 -6.36109591e-01 1.22260980e-01 8.09877872e-01 1.51203084e+00 4.70836103e-01 -1.10800600e+00 4.51688796e-01 -4.72199231e-01 -4.04393852e-01 -1.44316433e-02 -6.65848434e-01 -6.76340640e-01 1.24713194e+00 1.15988863e+00 4.11609024e-01 1.10219789e+00 2.10522354e-01 3.64349753e-01 -7.33760446e-02 1.81728862e-02 -1.38875222e+00 -1.25990167e-01 1.91620484e-01 8.92529190e-01 -1.42444205e+00 -5.51290751e-01 -6.05656445e-01 -6.39291406e-01 1.05452919e+00 1.21461041e-01 4.22291338e-01 5.44495702e-01 3.50792885e-01 3.91512454e-01 2.82746494e-01 -3.43533188e-01 -5.13234377e-01 5.40663421e-01 1.19369173e+00 3.01639527e-01 2.35462353e-01 -1.84401646e-01 1.65252853e-02 -7.09124088e-01 -1.85141772e-01 4.58232433e-01 3.24116915e-01 -8.58110428e-01 -9.22272027e-01 -7.88604915e-01 6.58624843e-02 -3.33325148e-01 -2.91804373e-01 -3.87177497e-01 8.41327786e-01 3.67198348e-01 1.41909099e+00 1.79734617e-01 -5.37989616e-01 -1.16644070e-01 4.37814623e-01 5.61955512e-01 -3.12590778e-01 -1.90037876e-01 2.18250230e-01 -7.93712139e-02 -3.09124980e-02 -3.86373669e-01 -7.74835587e-01 -1.16491115e+00 -5.33531785e-01 -3.82013232e-01 3.44146453e-02 1.17772102e+00 7.81068146e-01 -1.04922824e-01 -3.19464467e-02 5.03757060e-01 -8.21841240e-01 1.27785400e-01 -1.05974722e+00 -6.73970461e-01 2.11541638e-01 8.42817008e-01 -5.78805566e-01 -1.11856389e+00 4.91431832e-01]	[14.308297157287598, 5.003406524658203]
b9f20393-93a8-451e-b96e-7496008a733a	update-3-0-to-puma-the-porous-microstructure	null	null	https://www.sciencedirect.com/science/article/pii/S235271102100090X	https://www.sciencedirect.com/science/article/pii/S235271102100090X/pdfft?isDTMRedir=true&download=true	Update 3.0 to “PuMA: The Porous Microstructure Analysis software”	A major update of the Porous Microstructure Analysis (PuMA) software is presented. PuMA is a framework for computing effective material properties and response based on material microstructures. Version 3.0 of the software extends the PuMA capabilities to include computation of anisotropic conductivity, elasticity, permeability, per-voxel material or fiber orientation estimation, as well as expanded computational material generation capabilities. Version 3.0 also introduces pumapy, a Python version of the PuMA software.	['Nagi N. Mansour', 'Arnaud Borner', 'Francesco Panerai', 'John M. Thornton', 'Federico Semeraro', 'Joseph C. Ferguson']	2021-07-19	null	null	null	softwarex-2021-7	['physical-simulations']	['miscellaneous']	[-2.09254563e-01 -1.01345658e-01 6.15277171e-01 1.43385813e-01 -2.98559159e-01 -1.86590314e-01 3.12641889e-01 1.69534400e-01 -1.59753069e-01 9.53308523e-01 3.14507693e-01 -2.53557891e-01 -4.94733363e-01 -1.44374526e+00 -5.38227975e-01 -1.00640690e+00 -4.57334310e-01 6.05003834e-01 1.08149040e+00 1.30527630e-01 6.55413210e-01 8.26987267e-01 -1.12867677e+00 3.71281773e-01 4.38083500e-01 1.50106275e+00 1.85639307e-01 9.48289454e-01 2.14306995e-01 6.62919104e-01 2.02155575e-01 5.08216441e-01 -2.56207079e-01 6.22731984e-01 -1.40179396e+00 -2.95076489e-01 -5.22988625e-02 -5.22875249e-01 1.05248116e-01 3.83805871e-01 4.39500004e-01 4.46598500e-01 1.09433424e+00 -6.24625385e-01 -7.98433542e-01 7.15701044e-01 -1.79381073e-01 4.41467255e-01 5.88642895e-01 8.82892385e-02 3.39578241e-01 -1.15820324e+00 6.67762756e-01 1.29060662e+00 9.61604297e-01 2.98289627e-01 -1.32870638e+00 -2.59131696e-02 -6.08883202e-01 1.18305916e-02 -1.13617265e+00 -3.15211743e-01 5.18592179e-01 -6.36772871e-01 1.50920379e+00 6.48441792e-01 6.85449541e-01 6.23113155e-01 9.68345344e-01 2.58846253e-01 1.38856733e+00 -3.74777429e-02 7.74405003e-01 -2.63112634e-01 2.13398978e-01 3.52181911e-01 3.65705460e-01 1.67351782e-01 -2.21288159e-01 -5.80307305e-01 1.21433461e+00 -7.82561302e-01 1.23963259e-01 -2.07754597e-01 -1.04337680e+00 3.11596364e-01 6.55313162e-03 1.13918282e-01 -7.25343645e-01 3.42148513e-01 3.64492029e-01 -1.20925196e-01 5.28628290e-01 5.74235916e-01 -3.84354353e-01 -3.42206955e-01 -5.18108785e-01 7.83244073e-01 1.07605326e+00 5.57326078e-01 5.15546322e-01 3.12075108e-01 -5.50855398e-02 8.86595428e-01 7.72033036e-01 7.60454476e-01 9.77327228e-02 -1.63977873e+00 -2.58780748e-01 -1.37064099e-01 3.41998488e-01 -9.05165195e-01 -5.65413475e-01 3.16457003e-02 -2.77386695e-01 3.64373922e-01 8.91507044e-02 1.46135032e-01 -7.16968060e-01 4.78140682e-01 7.74419010e-01 -1.21691721e-02 1.45918764e-02 6.21770620e-01 1.13891697e+00 4.18736339e-01 3.73628944e-01 9.38008055e-02 9.41928387e-01 -8.31006527e-01 -3.38803768e-01 1.77968681e-01 3.53285074e-01 -1.05667341e+00 7.54660368e-01 4.34599549e-01 -1.62684202e+00 1.25427499e-01 -8.50019753e-01 1.33619890e-01 -6.35269284e-01 -9.49639142e-01 7.69454539e-01 5.73648214e-01 -1.04950130e+00 9.18021500e-01 -1.37060797e+00 -1.05470508e-01 3.42250794e-01 3.65266919e-01 -3.73081446e-01 -7.23853111e-02 -9.48277771e-01 1.00590670e+00 2.28209183e-01 -7.62606338e-02 -6.99962914e-01 -1.36002028e+00 -8.04223835e-01 -2.20883116e-01 -2.59290487e-01 -8.90674412e-01 1.14891386e+00 3.75242561e-01 -2.03814960e+00 4.29588556e-01 4.00211364e-01 -7.17800111e-04 3.92084360e-01 -1.83814809e-01 -3.23475420e-01 7.77912319e-01 2.83923388e-01 3.36090513e-02 1.61302164e-01 -1.45935285e+00 2.20982909e-01 9.57942232e-02 -3.23666334e-01 -2.07076386e-01 1.26239344e-01 4.31471132e-02 2.24760637e-01 -6.33328736e-01 2.39312932e-01 -3.05826604e-01 -4.63278919e-01 9.87140760e-02 -5.27837336e-01 5.06270193e-02 9.44132030e-01 -9.03247833e-01 8.29053819e-01 -1.62119901e+00 -2.24571601e-01 8.26311111e-01 1.67410970e-01 -3.29580694e-01 1.92526981e-01 5.92921436e-01 4.50564981e-01 1.43214494e-01 -8.42311561e-01 8.99405405e-02 -5.07292710e-02 -1.60894319e-01 1.93193913e-01 5.09382725e-01 -2.28816554e-01 4.32646275e-01 -8.92497838e-01 -4.96798128e-01 4.37429786e-01 5.27547359e-01 -7.21786201e-01 -2.90743023e-01 1.28108725e-01 4.15790468e-01 -7.02978551e-01 1.35748923e+00 1.50725043e+00 -1.24431169e-02 -3.46504927e-01 -1.81504846e-01 -5.09992182e-01 7.56660327e-02 -1.28885281e+00 9.67434466e-01 -6.78660393e-01 -1.87399268e-01 1.05236232e+00 -6.43017828e-01 6.13516688e-01 5.94764471e-01 1.18154657e+00 -4.63527828e-01 5.76119386e-02 7.93457687e-01 -3.81929308e-01 -7.44160175e-01 4.79130983e-01 -2.63011485e-01 5.25021136e-01 5.71259081e-01 -9.54704210e-02 -1.05164158e+00 2.58080930e-01 1.59062311e-01 1.25239432e+00 2.57491559e-01 -1.57888293e-01 -1.35219622e+00 5.19270301e-01 9.24033746e-02 4.15869653e-02 4.93635088e-01 1.57315528e-03 3.50245476e-01 -1.55385628e-01 -5.51033802e-02 -1.36746597e+00 -1.88476646e+00 -1.15139472e+00 5.12116730e-01 3.60198259e-01 -3.52473825e-01 -7.44168937e-01 4.81939405e-01 6.23212516e-01 2.83717245e-01 -7.72881329e-01 1.85289189e-01 -2.81157702e-01 -1.14480543e+00 7.43665472e-02 8.19758713e-01 6.07172549e-01 -1.41012609e+00 -5.97646892e-01 6.39932215e-01 3.76034349e-01 -1.09367645e+00 2.18254194e-01 -3.88710290e-01 -1.13354695e+00 -1.06832540e+00 -3.41653943e-01 -5.01297534e-01 2.57956237e-01 -4.05001611e-01 1.16944790e+00 3.52169156e-01 -2.92900890e-01 9.20401394e-01 -3.11682940e-01 -1.07220970e-01 -5.52995145e-01 -2.76711822e-01 2.50087589e-01 -5.95066130e-01 -3.76893014e-01 -9.91545200e-01 -8.99995327e-01 2.52085358e-01 -1.17438281e+00 4.90045361e-02 7.69701824e-02 2.72008032e-01 8.87045622e-01 4.14620966e-01 7.75171280e-01 -8.30054343e-01 8.05535972e-01 -7.84740627e-01 -7.59764388e-02 -1.43930137e-01 -4.80987042e-01 -4.70202297e-01 2.96011418e-01 -2.05175117e-01 -1.39578974e+00 -6.38473868e-01 -8.00713599e-01 4.59130883e-01 -2.22982481e-01 9.19429600e-01 8.20056126e-02 -5.77033460e-01 2.22878531e-01 -1.46962598e-01 1.20123535e-01 -5.70695400e-01 -1.21121921e-01 5.61656833e-01 5.93978643e-01 -1.57686126e+00 2.84430385e-01 8.37269783e-01 1.90694734e-01 -1.14371395e+00 -3.21343578e-02 -4.11414027e-01 -4.30753320e-01 -6.07182384e-01 5.59443176e-01 -5.91763109e-02 -8.44325244e-01 1.02291358e+00 -5.84689319e-01 -1.17307913e+00 -3.74980062e-01 7.63418138e-01 -7.02275932e-01 3.75047296e-01 -1.27213752e+00 -5.29955208e-01 -8.64530027e-01 -1.40831721e+00 7.78149784e-01 1.56243324e-01 -3.90053719e-01 -1.54910374e+00 2.81622529e-01 2.12044522e-01 1.35717452e+00 4.87716198e-01 6.24373078e-01 1.98227704e-01 -1.56725988e-01 -1.12884164e-01 -1.04547359e-01 3.19359720e-01 -8.39747116e-02 5.96782029e-01 -8.70169461e-01 -1.58612892e-01 -3.21329199e-02 -6.37177154e-02 5.20642221e-01 1.04260564e+00 1.15288162e+00 -1.42423540e-01 -4.90234584e-01 5.04187703e-01 1.71233714e+00 9.68746655e-03 8.60315859e-01 8.46091747e-01 2.88836569e-01 3.86251599e-01 1.54640064e-01 6.67344570e-01 -1.69850066e-01 1.35133639e-01 5.53910971e-01 8.22743624e-02 -1.49394825e-01 6.39108837e-01 1.12363957e-01 9.11100864e-01 -5.94607413e-01 3.55475038e-01 -8.40799034e-01 3.39830667e-01 -1.01708293e+00 -9.72773135e-01 -6.36323631e-01 1.85534668e+00 8.26113403e-01 2.44617853e-02 -1.68521836e-01 3.62831354e-01 3.28943431e-01 -4.77367848e-01 -2.79182673e-01 -7.51945019e-01 -1.53885052e-01 8.56555760e-01 7.49269903e-01 8.60204041e-01 -7.69823790e-01 5.46664953e-01 8.66493225e+00 4.92399931e-01 -1.00105655e+00 1.48149267e-01 1.76764086e-01 4.67993468e-01 -5.06293297e-01 -1.17559195e-01 -2.60390490e-01 5.45981705e-01 9.56947565e-01 -2.26778742e-02 5.13699293e-01 5.00240743e-01 4.78333622e-01 -9.41824436e-01 -2.69643873e-01 -1.25231698e-01 -6.27757370e-01 -1.67097473e+00 -2.31210783e-01 1.78802907e-01 3.33173782e-01 3.25595349e-01 -2.65816838e-01 -9.80231464e-02 3.20759863e-01 -6.30114317e-01 9.20592606e-01 9.26755607e-01 6.58815265e-01 -1.92498013e-01 8.48422229e-01 -4.18831974e-01 -1.32389128e+00 1.63647249e-01 -5.18678129e-01 -1.88210681e-01 8.48219633e-01 1.15253818e+00 -5.93882501e-01 5.02598822e-01 1.50181925e+00 5.47767878e-01 -5.09188831e-01 1.55670488e+00 5.82761943e-01 8.20099115e-01 -9.69557822e-01 4.00679737e-01 -2.22026154e-01 -4.21104580e-01 7.16680944e-01 1.17124104e+00 2.33616590e-01 1.00350738e-01 -1.60436302e-01 1.03366137e+00 6.27926052e-01 1.95899308e-01 -1.51873142e-01 2.68134922e-01 7.66438425e-01 1.07687342e+00 -1.32232320e+00 -4.52903599e-01 -1.45733938e-01 2.19321087e-01 -2.21790612e-01 4.18212652e-01 -4.70384032e-01 -3.61098140e-01 3.52705002e-01 5.83638370e-01 -1.67818189e-01 -3.40935320e-01 -8.11999023e-01 -3.91843557e-01 -4.22312409e-01 1.34593070e-01 1.98003531e-01 -1.17335165e+00 -1.80390358e+00 -6.83253109e-02 5.16003191e-01 -3.56873006e-01 6.30093396e-01 -1.23288250e+00 -8.69029999e-01 5.41741848e-01 -8.55935395e-01 -1.08533514e+00 -1.34259298e-01 2.79764146e-01 -5.99860698e-02 3.96111816e-01 1.10006571e+00 4.09221619e-01 -4.21966165e-01 -3.73161316e-01 3.09880167e-01 -3.26098233e-01 2.91786462e-01 -1.36997890e+00 1.56313255e-01 3.37985128e-01 -1.51107967e+00 5.72732985e-01 1.08994973e+00 -1.02338564e+00 -1.35871124e+00 -4.89455223e-01 2.42886576e-03 -1.03223026e-01 1.17663550e+00 2.11087942e-01 -1.20466530e+00 4.90433425e-01 1.43572643e-01 9.51318443e-02 6.04901195e-01 -1.97834566e-01 3.67786437e-01 2.98580021e-01 -1.60276973e+00 2.51797318e-01 5.13033688e-01 -2.04007104e-01 -1.96479365e-01 1.89155564e-01 2.65139729e-01 -6.22631490e-01 -2.13240075e+00 9.13569868e-01 1.04929841e+00 -6.97517574e-01 1.44811285e+00 1.30080208e-01 3.34108442e-01 -1.18183374e-01 -2.14758277e-01 -7.71684706e-01 -7.06029654e-01 -1.58705100e-01 -4.72834826e-01 9.58156288e-01 3.32704842e-01 -9.79829609e-01 5.40060282e-01 1.13632572e+00 -8.47180367e-01 -9.39416230e-01 -1.05812156e+00 -5.96923351e-01 7.74146736e-01 -3.42579037e-01 7.00507581e-01 7.06538200e-01 2.81434447e-01 -5.59076190e-01 5.65770566e-01 8.30346569e-02 6.73995674e-01 -1.88467696e-01 -1.13044150e-01 -1.36977863e+00 -1.65566429e-01 -6.14072978e-01 -7.06684068e-02 -1.28975764e-01 -2.95232147e-01 -6.37907326e-01 8.74733329e-02 -2.14768767e+00 4.44198512e-02 -1.03773737e+00 -1.24214537e-01 2.11395219e-01 3.08433145e-01 4.04806644e-01 -7.42838085e-01 2.10622430e-01 2.59180695e-01 3.33985835e-01 1.69464171e+00 -1.22224860e-01 -2.67122597e-01 -1.06249154e-01 -1.61013886e-01 2.88000077e-01 1.26244450e+00 3.56596485e-02 -5.70555031e-02 -3.56558710e-01 2.62529343e-01 -2.58188635e-01 6.10421658e-01 -1.35355890e+00 -2.73591220e-01 -4.39153552e-01 4.10064727e-01 -4.98818278e-01 3.19453329e-01 -6.90683782e-01 6.09416425e-01 4.71371323e-01 1.85569301e-01 1.12521857e-01 4.88846987e-01 2.24534795e-03 3.06011826e-01 -2.58112401e-01 1.05709147e+00 -3.26554179e-01 -3.91084433e-01 1.72820821e-01 -1.15621328e+00 -3.23304772e-01 8.06227505e-01 -6.65716827e-01 -7.73362100e-01 4.77927595e-01 -1.10449839e+00 -4.16628569e-02 9.14719582e-01 -4.75353688e-01 6.99146509e-01 -1.19019020e+00 -3.82700950e-01 -5.01883738e-02 -5.49892485e-01 3.86771083e-01 8.59057009e-01 1.34728181e+00 -1.75294459e+00 1.66612893e-01 -5.91680586e-01 -3.03329051e-01 -5.25901496e-01 3.31811458e-01 6.24718547e-01 -3.72683890e-02 -7.77517378e-01 8.73754025e-01 -3.26974988e-01 -3.49475294e-01 -7.73909271e-01 -3.33409876e-01 -3.50745171e-02 -7.80762196e-01 3.79679441e-01 1.37509727e+00 5.77851832e-01 -6.40968263e-01 -4.40798134e-01 5.70629001e-01 5.24513364e-01 -3.43299776e-01 1.65582097e+00 -3.00570279e-01 -8.89007747e-01 4.08483595e-01 5.68488419e-01 3.01914126e-01 -1.06278217e+00 4.35571343e-01 -1.32313073e-01 -8.73754621e-02 3.40629846e-01 -9.04983342e-01 -1.04572332e+00 4.52969819e-01 6.47877976e-02 2.79922396e-01 6.71156108e-01 6.82778284e-02 1.10056126e+00 -2.16482282e-01 3.44999790e-01 -1.62875891e+00 -1.96105435e-01 4.59281594e-01 1.03146815e+00 -2.70677328e-01 7.34909296e-01 -9.46724117e-01 1.60769880e-01 1.10420477e+00 7.30003357e-01 -2.74660945e-01 1.84981823e+00 9.97992516e-01 2.36121309e-03 -5.21469355e-01 -2.94727951e-01 7.16233552e-01 -2.30980620e-01 8.04739177e-01 6.85889900e-01 3.72745425e-01 -3.16880196e-01 5.21507204e-01 -3.13404441e-01 -2.20939592e-01 6.86705530e-01 1.75314915e+00 -5.39382160e-01 -9.26466882e-01 -8.89769375e-01 7.54995406e-01 -6.32936776e-01 -6.03315271e-02 2.08068952e-01 3.63783747e-01 -2.94002086e-01 8.18385780e-01 2.27862433e-01 -6.64212331e-02 6.12780638e-02 -5.12466550e-01 6.49410784e-01 -5.10191262e-01 -2.93464690e-01 -2.39218622e-02 3.71262789e-01 -3.73798609e-01 -8.59147549e-01 -7.05339372e-01 -1.76578486e+00 -6.49025977e-01 -3.08723629e-01 3.16372484e-01 5.47688067e-01 7.67363071e-01 6.30677193e-02 4.11180109e-01 -1.79623291e-02 -1.46567822e+00 2.96085745e-01 -1.34579229e+00 -1.39476871e+00 -3.01136579e-02 -2.05789849e-01 -1.30673218e+00 -2.63755649e-01 9.23276842e-02]	[6.393115997314453, 3.335890293121338]
041ca111-b997-4b38-9779-e862e4a9f361	meaformer-multi-modal-entity-alignment	2212.14454	null	https://arxiv.org/abs/2212.14454v3	https://arxiv.org/pdf/2212.14454v3.pdf	MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid	As an important variant of entity alignment (EA), multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) with relevant images attached. We noticed that current MMEA algorithms all globally adopt the KG-level modality fusion strategies for multi-modal entity representation but ignore the variation in modality preferences for individual entities, hurting the robustness to potential noise involved in modalities (e.g., blurry images and relations). In this paper, we present MEAformer, a multi-modal entity alignment transformer approach for meta modality hybrid, which dynamically predicts the mutual correlation coefficients among modalities for entity-level feature aggregation. A modal-aware hard entity replay strategy is further proposed for addressing vague entity details. Experimental results show that our model not only achieves SOTA performance on multiple training scenarios including supervised, unsupervised, iterative, and low resource, but also has a comparable number of parameters, optimistic speed, and good interpretability. Our code and data are available at https://github.com/zjukg/MEAformer.	['Yuxia Geng', 'Yichi Zhang', 'Huajun Chen', 'Wenting Song', 'Jeff Z. Pan', 'Yufeng Huang', 'Yin Fang', 'Lingbing Guo', 'Wen Zhang', 'Jiaoyan Chen', 'Zhuo Chen']	2022-12-29	null	null	null	null	['multi-modal-entity-alignment', 'entity-alignment', 'entity-alignment']	['knowledge-base', 'knowledge-base', 'natural-language-processing']	[-7.40770474e-02 2.87303776e-01 -2.62606084e-01 -2.43298799e-01 -1.09410059e+00 -6.84009373e-01 4.98242170e-01 3.79034251e-01 -6.56762868e-02 6.88125789e-01 4.60842162e-01 2.89370418e-01 -4.32460874e-01 -6.73384786e-01 -5.25820315e-01 -5.90784490e-01 6.35143230e-03 4.94411200e-01 1.60512462e-01 9.82825682e-02 -2.05827191e-01 1.88180432e-01 -1.49434829e+00 4.86577153e-01 9.14278924e-01 9.98465002e-01 7.48305693e-02 5.50902843e-01 -6.79676086e-02 1.02882373e+00 -1.21358238e-01 -9.82502401e-01 1.20078452e-01 -5.60270548e-02 -1.08137035e+00 6.48300126e-02 5.85118771e-01 1.07049355e-02 -3.92516285e-01 1.18503857e+00 7.74596334e-01 8.37962776e-02 5.09610713e-01 -1.61916006e+00 -7.94696510e-01 9.49562788e-01 -7.08367348e-01 1.96283311e-02 6.19815052e-01 -2.30298206e-01 1.07281160e+00 -1.24730289e+00 9.24030840e-01 1.00719774e+00 7.67744958e-01 3.14979821e-01 -9.46166694e-01 -4.47344750e-01 1.85991991e-02 4.85516429e-01 -1.81736505e+00 -5.44233203e-01 5.51374555e-01 -1.44881725e-01 6.29188359e-01 6.23461962e-01 3.22431445e-01 8.80499780e-01 -2.88048368e-02 9.99003768e-01 1.14771390e+00 -5.46891928e-01 -1.12945698e-01 2.21821442e-01 7.36376420e-02 7.63737857e-01 3.39583904e-01 -4.56780493e-01 -8.00783336e-01 -3.38130265e-01 4.13340360e-01 -1.45842537e-01 -4.17948067e-01 -4.49965358e-01 -1.75673819e+00 2.41587743e-01 4.35635805e-01 3.18219155e-01 -5.85159898e-01 -1.86486349e-01 2.16643214e-01 1.48306906e-01 7.70967677e-02 3.51530284e-01 -4.59565938e-01 1.84234753e-01 -6.50599062e-01 -9.56243798e-02 6.08386278e-01 1.30485857e+00 8.82344842e-01 -4.80503798e-01 -2.58459538e-01 8.18525791e-01 3.71851444e-01 6.50784612e-01 3.46501857e-01 -1.11595309e+00 5.53714037e-01 8.65588129e-01 1.27744013e-02 -1.18807185e+00 -6.17888868e-01 -2.70225793e-01 -1.13600886e+00 -4.68690664e-01 5.08773215e-02 -1.00409493e-01 -8.33350539e-01 1.84756374e+00 6.73663259e-01 3.33316386e-01 3.56049895e-01 8.86749983e-01 1.46343565e+00 1.48139223e-01 5.08096874e-01 -2.84328818e-01 1.88245344e+00 -9.61776555e-01 -9.67573762e-01 -4.87392731e-02 4.93140280e-01 -9.07027781e-01 5.49341798e-01 -1.17910787e-01 -1.26338744e+00 -2.59161204e-01 -6.64585829e-01 -1.78574473e-01 -8.42183173e-01 2.05957159e-01 7.95172393e-01 5.38141608e-01 -1.15053606e+00 8.87203142e-02 -5.44454217e-01 -6.12597287e-01 2.59895831e-01 3.24336410e-01 -9.17997122e-01 -1.08302176e-01 -1.47916424e+00 1.02465069e+00 8.48938286e-01 7.59762973e-02 -1.68106288e-01 -6.93020344e-01 -8.69783282e-01 -4.40203547e-02 6.26303196e-01 -1.26909840e+00 8.45469713e-01 -7.38203228e-01 -8.95356894e-01 9.45717514e-01 -3.35949749e-01 -1.59049749e-01 2.06227124e-01 -1.51664183e-01 -1.00099564e+00 2.47128963e-01 1.33706659e-01 7.94264555e-01 5.33831060e-01 -1.57505417e+00 -8.07942748e-01 -3.34156305e-01 9.69634801e-02 8.02579522e-01 -2.73437142e-01 -8.07874277e-02 -9.11486745e-01 -5.05682766e-01 3.51171166e-01 -8.68496239e-01 3.89705934e-02 -3.83810222e-01 -5.22517323e-01 -1.07569426e-01 5.60723126e-01 -7.75256097e-01 1.54187500e+00 -2.07479525e+00 3.79203051e-01 5.30098319e-01 4.27576065e-01 -1.73348740e-01 4.85052392e-02 4.94315386e-01 -1.81468260e-02 3.67349908e-02 -1.96390033e-01 -4.17463899e-01 2.41518822e-02 1.99957013e-01 3.83953974e-02 1.43514782e-01 -9.59396362e-02 1.27545071e+00 -1.00238323e+00 -1.10811245e+00 1.31552756e-01 3.88067633e-01 2.45120842e-03 -5.39542772e-02 1.72315612e-01 3.17089260e-01 -3.39150131e-01 1.28635311e+00 7.79247761e-01 -7.95358300e-01 4.57844734e-01 -1.06369090e+00 3.29469442e-01 -4.20000046e-01 -1.62691152e+00 1.90256977e+00 -1.05330527e-01 2.42079273e-01 -3.24158818e-02 -3.87980074e-01 2.88048625e-01 5.52889705e-01 7.88684547e-01 -5.48548520e-01 7.63455853e-02 2.86618292e-01 -3.56385291e-01 -4.61625934e-01 1.06773901e+00 3.27221543e-01 -3.75463873e-01 1.65923133e-01 3.68947566e-01 4.08007801e-01 2.54953027e-01 6.65147185e-01 8.56867731e-01 2.00662576e-02 6.11824393e-01 1.39125481e-01 5.30339837e-01 8.27573091e-02 4.64364439e-01 7.32543230e-01 -5.56490980e-02 5.45301318e-01 -1.15895286e-01 3.60089075e-03 -7.50928760e-01 -1.26647413e+00 -1.39616296e-01 9.38189983e-01 8.26337159e-01 -7.24110007e-01 -4.22686189e-01 -6.02061868e-01 -3.58812287e-02 4.64622200e-01 -5.37061036e-01 -2.47865263e-02 -2.15892866e-01 -9.13754821e-01 7.47378588e-01 4.37602252e-01 6.68111324e-01 -6.77706182e-01 -4.92737256e-02 -5.29312715e-02 -7.81310439e-01 -1.39477158e+00 -3.27401817e-01 -1.96745425e-01 -5.67122757e-01 -1.16459262e+00 -6.56571567e-01 -6.43393695e-01 9.07502472e-01 1.98631406e-01 1.24120605e+00 -9.12582576e-02 6.06763214e-02 1.08925402e+00 -4.28697199e-01 -1.33767307e-01 -1.10699698e-01 1.43446043e-01 8.30150694e-02 2.94135123e-01 4.61486071e-01 -4.88283247e-01 -6.70306385e-01 4.11254734e-01 -9.50698972e-01 3.06090415e-01 9.17052269e-01 7.44816065e-01 9.35011625e-01 5.77809848e-02 4.67906833e-01 -9.44727361e-01 5.05897045e-01 -6.75413370e-01 4.40400615e-02 1.11643457e+00 -8.30655873e-01 -7.83834159e-02 5.07398844e-02 -3.34031522e-01 -1.34615195e+00 1.78571921e-02 4.56601322e-01 -4.32531297e-01 -2.84525335e-01 7.46461868e-01 -2.58350343e-01 -1.54342130e-01 4.22420800e-01 1.95067227e-01 -4.70501304e-01 -2.75305301e-01 8.16918910e-01 5.65814495e-01 9.42649722e-01 -5.74559510e-01 9.10633147e-01 4.37533081e-01 5.47210649e-02 -2.80237645e-01 -7.49339700e-01 -6.64754868e-01 -6.69584394e-01 -4.78980213e-01 7.22754598e-01 -1.40349877e+00 -4.62410063e-01 5.52118957e-01 -7.54564941e-01 3.92365336e-01 -2.65182883e-01 4.81380343e-01 -3.10396016e-01 5.18454909e-01 -4.18306142e-01 -5.05705416e-01 -4.83644366e-01 -6.27141953e-01 1.10616052e+00 7.54226744e-01 -9.91076306e-02 -1.07338023e+00 -9.94460359e-02 6.97801054e-01 2.79003769e-01 2.79382735e-01 5.33788919e-01 -6.55842900e-01 -7.92444825e-01 -1.88788027e-01 -3.83333951e-01 -2.86626488e-01 2.82341182e-01 -1.81320429e-01 -9.27516878e-01 -1.41011283e-01 -6.63932264e-01 -1.84942484e-01 5.78884125e-01 1.98835969e-01 8.34989607e-01 -2.63265431e-01 -5.44801950e-01 3.98487240e-01 1.40276003e+00 -2.97604531e-01 6.59355998e-01 3.20705980e-01 9.83797371e-01 3.97375464e-01 9.37480569e-01 3.04119468e-01 1.14071631e+00 5.72072804e-01 2.33211398e-01 -2.94414639e-01 -2.90900797e-01 -1.32676885e-01 7.88501725e-02 1.03281355e+00 -3.61797422e-01 -4.56695527e-01 -7.97938168e-01 8.52904975e-01 -2.31528473e+00 -1.13021696e+00 -1.68968856e-01 2.04707599e+00 8.53343844e-01 -4.49374795e-01 3.36069725e-02 -3.33556175e-01 8.85358632e-01 -1.17699973e-01 -4.24458981e-01 2.68132627e-01 -8.28962743e-01 -2.30353892e-01 6.46507740e-01 1.94325671e-01 -1.27006066e+00 7.47926712e-01 5.38410521e+00 9.60882545e-01 -5.38355052e-01 3.50997031e-01 3.30041289e-01 7.85934851e-02 -4.73486036e-01 2.88852807e-02 -5.87927699e-01 3.34096074e-01 5.65808177e-01 -3.53446692e-01 2.85557747e-01 4.82910991e-01 -4.03041154e-01 -2.98398197e-01 -7.93619037e-01 1.15066612e+00 1.30228505e-01 -1.36435199e+00 1.62620142e-01 -1.43461064e-01 9.16712165e-01 4.06746082e-02 -6.19030595e-02 1.29195124e-01 2.99045742e-01 -7.15232015e-01 6.14471614e-01 9.48463380e-01 7.94954896e-01 -5.81195056e-01 9.66976762e-01 3.78357098e-02 -1.65827489e+00 5.97399063e-02 6.73317537e-02 7.47748554e-01 3.75833422e-01 4.66830701e-01 -6.27380908e-01 1.49090469e+00 8.20824862e-01 5.51853180e-01 -1.03694582e+00 1.02941692e+00 1.14033490e-01 -3.72868665e-02 -5.36870301e-01 5.31388223e-01 -3.30919683e-01 1.26418456e-01 6.88537180e-01 1.24101949e+00 4.29863334e-01 3.02585870e-01 4.52827998e-02 2.33646274e-01 -3.37771028e-01 1.71203136e-01 -3.45490098e-01 4.52910364e-02 9.76555347e-01 1.64179862e+00 -5.91176450e-01 -4.54792768e-01 -5.65553129e-01 1.06044495e+00 2.69688368e-01 3.46708208e-01 -8.59732330e-01 -5.28350025e-02 2.70398796e-01 -3.47834140e-01 1.51057035e-01 1.95869863e-01 -2.07676634e-01 -1.53317225e+00 1.24384843e-01 -7.28076935e-01 1.19887185e+00 -1.08847427e+00 -1.50715506e+00 4.66838598e-01 3.12681377e-01 -1.48931992e+00 -1.05125442e-01 -2.11931869e-01 -8.52985978e-02 6.02886915e-01 -1.43271244e+00 -1.81815612e+00 -4.84777331e-01 1.06217706e+00 -1.18172243e-02 -7.62127116e-02 9.80269611e-01 5.95073998e-01 -5.39524615e-01 8.66902053e-01 -1.41178712e-01 1.11417420e-01 1.05625093e+00 -1.39572322e+00 -2.29721308e-01 9.19474423e-01 2.42330730e-01 7.61348128e-01 5.53103209e-01 -7.43624330e-01 -1.56254554e+00 -1.07973099e+00 1.09411240e+00 -7.07616329e-01 6.42784297e-01 2.66007751e-01 -8.06520641e-01 8.03856373e-01 4.89975870e-01 2.14778502e-02 1.04154205e+00 2.41929203e-01 -3.52691352e-01 -7.20536336e-02 -1.34000146e+00 6.30026162e-01 1.15076315e+00 -6.28382087e-01 -4.93564039e-01 2.83582836e-01 3.86591375e-01 -8.75301421e-01 -1.70582795e+00 7.75798380e-01 5.87251961e-01 -6.37865365e-01 1.11496949e+00 -3.74541879e-01 -2.08425783e-02 -7.93229461e-01 -4.28905427e-01 -1.00278568e+00 -4.74839985e-01 -3.65540028e-01 -8.92476141e-01 1.62927151e+00 5.75287700e-01 -6.21741116e-01 3.11219156e-01 9.41543639e-01 1.56564504e-01 -5.31427622e-01 -8.87292802e-01 -3.91261578e-01 -7.23685443e-01 -3.80029194e-02 8.23355258e-01 1.47155201e+00 1.27299204e-01 2.81669617e-01 -5.37427664e-01 9.48873639e-01 7.72278726e-01 5.13194323e-01 5.33296108e-01 -9.90430713e-01 -1.52640685e-01 -2.52830088e-01 -4.94891137e-01 -6.15326524e-01 -1.50182158e-01 -9.12151337e-01 -5.07842720e-01 -1.69551682e+00 6.88426554e-01 -4.06988651e-01 -7.12684989e-01 7.18128383e-01 -3.99563134e-01 4.49244887e-01 2.20251232e-01 5.12555242e-01 -1.21567619e+00 1.91034988e-01 1.05662704e+00 -1.00654893e-01 2.05449946e-02 -3.29202950e-01 -8.55678201e-01 5.79439461e-01 6.60172939e-01 -2.53960788e-01 -3.58203053e-01 -3.49858910e-01 4.87483084e-01 2.15905793e-02 4.46473777e-01 -8.41077924e-01 7.98613548e-01 -1.72643483e-01 5.05439878e-01 -7.54508317e-01 3.60987812e-01 -1.15326250e+00 1.00824654e+00 -2.71147102e-01 -1.91542044e-01 1.81582302e-01 1.00215726e-01 5.70653558e-01 -4.73328948e-01 8.31037834e-02 2.76873887e-01 -1.02590211e-01 -1.35803723e+00 3.44623685e-01 2.00582474e-01 -6.48989305e-02 1.11105251e+00 -2.73040086e-01 -7.43572116e-01 -2.70379603e-01 -1.05170095e+00 6.95924044e-01 6.36944711e-01 4.45254236e-01 4.80441064e-01 -1.72170210e+00 -6.04273498e-01 -3.64816099e-01 5.62072873e-01 -2.48967670e-02 7.27278769e-01 1.26709509e+00 -3.86319216e-03 1.06968433e-01 -5.82126826e-02 -5.53352416e-01 -1.51676393e+00 3.86112899e-01 3.37069929e-01 -4.48895454e-01 -2.93392062e-01 7.18725562e-01 -1.77459478e-01 -4.73042011e-01 2.36341935e-02 3.58182877e-01 -2.45885655e-01 3.97417933e-01 3.61859590e-01 3.62856984e-01 7.54114389e-02 -1.18414426e+00 -7.10353494e-01 5.12813628e-01 -1.49483040e-01 1.72344774e-01 9.67962384e-01 -7.72460043e-01 -2.29315609e-01 3.69117141e-01 6.38533771e-01 2.00124785e-01 -5.70591748e-01 -6.62420988e-01 3.74082550e-02 -2.63370365e-01 1.13517949e-02 -1.20379412e+00 -1.06657624e+00 -1.36956662e-01 7.04955339e-01 2.73337364e-01 1.61159074e+00 4.23157096e-01 7.35346198e-01 2.52235234e-01 5.09383857e-01 -1.16526651e+00 -4.50999141e-01 6.61691204e-02 5.40513873e-01 -1.35981417e+00 4.06554699e-01 -6.30928516e-01 -1.02007711e+00 8.06857169e-01 6.58469975e-01 7.18282461e-01 5.33577144e-01 1.05134167e-01 1.49004519e-01 -5.66986859e-01 -6.40608966e-01 -5.14494956e-01 6.98099494e-01 5.23293018e-01 7.88144097e-02 2.48472527e-01 -6.30103052e-02 5.02307892e-01 9.91609320e-02 -8.38605389e-02 1.65733621e-01 9.29841757e-01 -6.67316988e-02 -1.07692277e+00 -5.11902750e-01 3.88079107e-01 -3.83371413e-01 -1.86937809e-01 -4.39123303e-01 7.86085248e-01 3.54107082e-01 8.24150145e-01 -2.01070189e-01 -4.31385010e-01 3.69089901e-01 1.47553340e-01 5.07544100e-01 -7.60825425e-02 -5.62271476e-01 -1.22969404e-01 3.64553094e-01 -4.38341677e-01 -1.22902834e+00 -7.80001581e-01 -1.08678520e+00 -3.71245444e-01 -5.75581491e-01 7.34068081e-02 2.32141435e-01 8.09199214e-01 9.03307974e-01 3.48635644e-01 4.56046194e-01 -3.88558805e-01 2.20730498e-01 -8.05418015e-01 -4.70427632e-01 6.49781525e-01 8.87067094e-02 -6.84119046e-01 -3.08696330e-02 3.44161987e-01]	[8.656244277954102, 7.677020072937012]