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ArXiv ML Papers
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1,275.798602
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ArXiv ML Papers
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857.142377
all-MiniLM-L6-v2
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ArXiv ML Papers
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all-MiniLM-L6-v2
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ArXiv ML Papers
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ArXiv ML Papers
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1,012.478548
all-MiniLM-L6-v2
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0.746527
ArXiv ML Papers
ZeroShotTM
45
20
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1,028.527274
all-MiniLM-L6-v2
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0.134271
0.74595
ArXiv ML Papers
ZeroShotTM
46
20
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1,002.356594
all-MiniLM-L6-v2
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ArXiv ML Papers
ZeroShotTM
43
30
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1,141.844126
all-MiniLM-L6-v2
0.746667
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0.747085
ArXiv ML Papers
ZeroShotTM
44
30
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1,051.120682
all-MiniLM-L6-v2
0.776667
-0.02817
0.130445
0.768253
ArXiv ML Papers
ZeroShotTM
45
30
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1,156.536222
all-MiniLM-L6-v2
0.786667
-0.048736
0.135058
0.759984
ArXiv ML Papers
ZeroShotTM
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978.73439
all-MiniLM-L6-v2
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0.780063
ArXiv ML Papers
ZeroShotTM
44
50
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1,174.040942
all-MiniLM-L6-v2
0.698
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0.130783
0.775953
ArXiv ML Papers
ZeroShotTM
45
50
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1,066.117967
all-MiniLM-L6-v2
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0.783174
ArXiv ML Papers
ZeroShotTM
46
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1,220.778715
all-MiniLM-L6-v2
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ArXiv ML Papers
ECRTM
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4,127.300286
all-MiniLM-L6-v2
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ArXiv ML Papers
ECRTM
44
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4,688.849451
all-MiniLM-L6-v2
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ArXiv ML Papers
ECRTM
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4,159.961052
all-MiniLM-L6-v2
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ArXiv ML Papers
ECRTM
46
10
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4,646.624485
all-MiniLM-L6-v2
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0.923685
ArXiv ML Papers
ECRTM
43
20
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21,789.126004
all-MiniLM-L6-v2
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ArXiv ML Papers
ECRTM
44
20
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21,816.13647
all-MiniLM-L6-v2
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0.144156
0.920937
ArXiv ML Papers
ECRTM
45
20
[ [ "channels", "explanations", "coding", "channel", "explanation", "quantum", "calibration", "concepts", "eeg", "transmission" ], [ "ml", "social", "fairness", "subjects", "questions", "researchers", "research", "health", "human", "individuals" ], [ "kernel", "label", "delta", "fairness", "frac", "kernels", "nearest", "neighbor", "regression", "theoretic" ], [ "monte", "variational", "mcmc", "variables", "autoregressive", "posterior", "forecasting", "forecasts", "forecast", "likelihood" ], [ "net", "feature", "3d", "audio", "cnn", "enhancement", "videos", "frame", "spatial", "video" ], [ "health", "cancer", "disease", "covid", "patients", "ct", "patient", "19", "diagnosis", "day" ], [ "sqrt", "epsilon", "communication", "regret", "bandit", "varepsilon", "delta", "log", "distributed", "frac" ], [ "attacks", "platforms", "detection", "service", "attack", "malware", "iot", "detect", "software", "bias" ], [ "graph", "link", "gnns", "graphs", "node", "nodes", "protein", "embeddings", "matrix", "gnn" ], [ "concepts", "recurrent", "pac", "probabilistic", "operate", "bayesian", "hierarchical", "turn", "forecast", "relations" ], [ "rl", "robot", "reinforcement", "reward", "action", "agent", "policy", "policies", "agents", "actions" ], [ "pooling", "width", "layer", "relu", "activation", "depth", "regime", "initialization", "mathbb", "neuron" ], [ "sentence", "language", "word", "speech", "text", "sentences", "audio", "languages", "words", "speaker" ], [ "subspace", "signals", "cluster", "clustering", "teacher", "student", "clusters", "ranking", "filter", "nas" ], [ "machines", "quantum", "science", "metric", "scientific", "distance", "queries", "informed", "dl", "physics" ], [ "quantization", "bit", "hardware", "consumption", "accelerators", "pruning", "memory", "scaling", "convolution", "nas" ], [ "convex", "convergence", "proximal", "variational", "stochastic", "momentum", "accelerated", "gradient", "descent", "variance" ], [ "contrastive", "image", "segmentation", "images", "supervision", "cell", "object", "unlabeled", "labeled", "supervised" ], [ "perturbation", "federated", "perturbations", "attacks", "defense", "privacy", "adversarial", "attack", "private", "vulnerable" ], [ "survey", "media", "games", "pipelines", "directions", "gans", "clinical", "review", "taxonomy", "library" ] ]
21,868.923991
all-MiniLM-L6-v2
0.94
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0.152332
0.9172
ArXiv ML Papers
ECRTM
46
20
[ [ "clustering", "subspace", "subspaces", "mathbb", "clusters", "kernel", "laplacian", "recovery", "semi", "regression" ], [ "labeled", "cell", "unlabeled", "contrastive", "segmentation", "supervised", "supervision", "images", "annotation", "augmentation" ], [ "tilde", "regret", "epsilon", "sqrt", "varepsilon", "bandit", "communication", "bounds", "log", "frac" ], [ "defense", "attacks", "adversarial", "perturbations", "attack", "privacy", "perturbation", "attacker", "vulnerable", "private" ], [ "nas", "gnns", "pruning", "quantization", "scaling", "pruned", "gnn", "convolution", "com", "github" ], [ "style", "generative", "student", "variables", "latent", "generator", "vae", "teacher", "auxiliary", "autoencoder" ], [ "width", "equations", "dynamical", "boundary", "theory", "activation", "physics", "relu", "informed", "equation" ], [ "metric", "classifier", "label", "calibration", "channels", "channel", "eeg", "decision", "screening", "candidate" ], [ "language", "languages", "word", "speech", "sentence", "transformer", "speaker", "english", "bleu", "corpus" ], [ "recurrent", "solvers", "kernels", "correlated", "resolution", "games", "compositional", "meta", "sum", "principled" ], [ "attacks", "attack", "iot", "vehicle", "service", "traffic", "detect", "vehicles", "driving", "detection" ], [ "patients", "causal", "series", "forecast", "treatment", "patient", "forecasts", "missing", "forecasting", "records" ], [ "agent", "action", "policies", "policy", "reinforcement", "reward", "rl", "robot", "actions", "agents" ], [ "3d", "video", "segmentation", "frame", "net", "convolution", "frames", "audio", "videos", "cnn" ], [ "computing", "federated", "quantum", "decentralized", "transmission", "server", "bandwidth", "iteration", "devices", "centralized" ], [ "survey", "researchers", "research", "scientific", "ml", "review", "questions", "software", "challenges", "development" ], [ "graphs", "link", "graph", "nodes", "embeddings", "topic", "recommendation", "embedding", "metric", "vertex" ], [ "variational", "carlo", "bayesian", "posterior", "approximations", "monte", "flows", "flow", "normalizing", "estimators" ], [ "cancer", "day", "covid", "forest", "19", "patients", "weather", "ct", "was", "were" ], [ "items", "traffic", "media", "transfer", "recommendation", "incremental", "taxonomy", "pipelines", "recommender", "temporal" ] ]
22,149.969739
all-MiniLM-L6-v2
0.96
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0.140342
0.907562
ArXiv ML Papers
ECRTM
43
30
[ [ "attack", "attacks", "defense", "perturbations", "vulnerable", "adversarial", "attacker", "perturbation", "vulnerability", "poisoning" ], [ "series", "anomaly", "signals", "speech", "delay", "music", "audio", "temporal", "event", "aggregation" ], [ "equations", "mutual", "divergence", "variables", "logistic", "vae", "regression", "kernel", "operator", "boundary" ], [ "quantum", "regime", "exponentially", "exponential", "polynomial", "relu", "calibration", "bounds", "classifiers", "confidence" ], [ "treatment", "social", "practices", "explanation", "eye", "interventions", "patients", "intelligence", "explain", "effects" ], [ "language", "alignment", "speech", "languages", "speaker", "voice", "character", "source", "text", "bert" ], [ "contrastive", "shot", "reasoning", "unlabeled", "supervision", "supervised", "distillation", "event", "self", "forgetting" ], [ "diversity", "augmentation", "diffusion", "resolution", "english", "translation", "centric", "shape", "normalization", "bleu" ], [ "vehicles", "19", "ct", "driving", "covid", "sensors", "day", "traffic", "95", "vehicle" ], [ "tensor", "completion", "matrix", "rank", "subspace", "alternating", "norm", "projections", "kernel", "entries" ], [ "policy", "rl", "policies", "robot", "agent", "reinforcement", "action", "reward", "planning", "imitation" ], [ "informed", "rl", "review", "equations", "games", "scientific", "cooperative", "physics", "players", "protein" ], [ "graph", "graphs", "gnns", "node", "edges", "gnn", "passing", "message", "link", "nodes" ], [ "posterior", "variables", "bayesian", "monte", "uncertainty", "carlo", "variational", "distributions", "autoregressive", "chain" ], [ "decentralized", "private", "communication", "privacy", "server", "devices", "federated", "distributed", "centralized", "central" ], [ "protein", "forecast", "relations", "video", "forecasting", "net", "demand", "lstm", "spatial", "interactions" ], [ "recommender", "media", "user", "channel", "recommendation", "coding", "items", "item", "music", "adaptation" ], [ "word", "sentences", "words", "gender", "language", "signals", "bias", "text", "eeg", "fairness" ], [ "sqrt", "regret", "bandit", "communication", "epsilon", "agent", "agents", "bandits", "log", "distributed" ], [ "bounds", "frac", "delta", "bound", "varepsilon", "tight", "pac", "arm", "fairness", "omega" ], [ "iot", "student", "attacks", "attack", "teacher", "detection", "nas", "feedback", "ranking", "outlier" ], [ "manifold", "geometric", "pooling", "vertex", "graphs", "subspaces", "topological", "objects", "geometry", "graph" ], [ "object", "detector", "segmentation", "ct", "classifier", "whole", "cancer", "eeg", "filter", "brain" ], [ "games", "kernels", "compositional", "sum", "gaussian", "converges", "correlated", "solvers", "meta", "kernel" ], [ "clinical", "sound", "industry", "ml", "software", "engineering", "review", "researchers", "library", "challenges" ], [ "metric", "questions", "documents", "ml", "distance", "social", "queries", "stream", "granularity", "recommendations" ], [ "counterfactual", "explanations", "explainable", "boosting", "concepts", "explanation", "explaining", "base", "black", "genetic" ], [ "scaling", "pruning", "bit", "convolution", "activation", "quantization", "accelerators", "gpus", "hardware", "pruned" ], [ "gans", "gan", "robot", "images", "camera", "image", "shift", "resolution", "augmentation", "transformations" ], [ "accelerated", "convergence", "descent", "max", "stochastic", "epsilon", "convex", "proximal", "min", "nonconvex" ] ]
21,010.94308
all-MiniLM-L6-v2
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0.133445
0.924199
ArXiv ML Papers
ECRTM
44
30
[ [ "shift", "biases", "unbiased", "camera", "bias", "grained", "million", "scaling", "strategies", "changes" ], [ "completion", "series", "rank", "matrix", "tensor", "nonnegative", "subspace", "clustering", "anomaly", "alternating" ], [ "words", "sentences", "health", "word", "language", "gender", "eeg", "nlp", "brain", "embeddings" ], [ "metric", "query", "reports", "distance", "documents", "neighbor", "nearest", "queries", "trees", "kernel" ], [ "nodes", "link", "gnn", "gnns", "graph", "graphs", "node", "embeddings", "vertex", "neighborhood" ], [ "tensor", "dl", "medical", "domain", "scientific", "traffic", "discriminative", "tensors", "transfer", "imaging" ], [ "transport", "factorization", "concepts", "produced", "pipelines", "broader", "exactly", "taxonomy", "media", "rapidly" ], [ "segmentation", "net", "audio", "enhancement", "speech", "cnn", "video", "eeg", "3d", "face" ], [ "driving", "split", "boost", "boosting", "base", "mcmc", "coverage", "descent", "imbalance", "accuracies" ], [ "reinforcement", "rl", "policy", "reward", "agent", "action", "robot", "policies", "actions", "environment" ], [ "autoencoders", "variational", "vae", "generative", "variables", "posterior", "latent", "monte", "autoencoder", "carlo" ], [ "decentralized", "devices", "channel", "federated", "communication", "transmission", "centralized", "server", "bandwidth", "wireless" ], [ "generator", "capacity", "composed", "regarding", "predictor", "the", "engineering", "test", "reveal", "effect" ], [ "activation", "pruned", "pooling", "initialization", "relu", "layer", "width", "pruning", "neuron", "teacher" ], [ "fidelity", "side", "equations", "imaging", "transmission", "spatiotemporal", "treatment", "cnn", "patient", "effects" ], [ "convex", "descent", "epsilon", "convergence", "proximal", "stochastic", "gradient", "min", "max", "accelerated" ], [ "forecasting", "demand", "transformers", "lstm", "recurrent", "net", "attention", "dependencies", "rnns", "temporal" ], [ "day", "weather", "patients", "forest", "19", "covid", "ct", "screening", "cancer", "health" ], [ "robot", "contrastive", "images", "gans", "gan", "supervised", "object", "objects", "labeled", "scene" ], [ "explanation", "probabilistic", "programming", "concepts", "explainable", "explanations", "counterfactual", "black", "explaining", "rules" ], [ "sentence", "style", "languages", "language", "speech", "speaker", "text", "bleu", "bert", "character" ], [ "research", "social", "software", "development", "survey", "researchers", "industry", "ml", "media", "challenges" ], [ "tilde", "sqrt", "varepsilon", "bandit", "epsilon", "regret", "bandits", "log", "bound", "ucb" ], [ "fairness", "left", "arm", "recovery", "delta", "laplacian", "equation", "frac", "graphs", "game" ], [ "calibration", "lasso", "label", "classifier", "quantum", "fairness", "classifiers", "mathbb", "confidence", "fair" ], [ "pruning", "nas", "hardware", "quantization", "split", "imagenet", "cell", "scaling", "segmentation", "github" ], [ "bayesian", "estimator", "posterior", "covariates", "bounds", "bound", "pac", "treatment", "interval", "mutual" ], [ "adversarial", "attacks", "attacker", "attack", "perturbations", "defense", "perturbation", "vulnerable", "box", "defend" ], [ "vehicles", "iot", "attacks", "attack", "traffic", "vehicle", "service", "driving", "detect", "platforms" ], [ "kernel", "inverse", "physics", "flows", "temperature", "informed", "quantum", "kernels", "normalizing", "flow" ] ]
121.898181
all-MiniLM-L6-v2
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0.134444
0.917003
ArXiv ML Papers
ECRTM
45
30
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121.165248
all-MiniLM-L6-v2
0.933333
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0.134941
0.918399
ArXiv ML Papers
ECRTM
46
30
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117.883204
all-MiniLM-L6-v2
0.906667
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0.135218
0.91787
ArXiv ML Papers
ECRTM
43
40
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95.518122
all-MiniLM-L6-v2
0.93
-0.199357
0.12476
0.924882
ArXiv ML Papers
ECRTM
44
40
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139.658376
all-MiniLM-L6-v2
0.885
-0.201981
0.127813
0.915715
ArXiv ML Papers
ECRTM
45
40
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129.142575
all-MiniLM-L6-v2
0.96
-0.192391
0.13562
0.923463
ArXiv ML Papers
ECRTM
46
40
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139.110896
all-MiniLM-L6-v2
0.9625
-0.212002
0.130715
0.927364
ArXiv ML Papers
ECRTM
43
50
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106.329468
all-MiniLM-L6-v2
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ArXiv ML Papers
ECRTM
44
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94.302951
all-MiniLM-L6-v2
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0.129265
0.925652
ArXiv ML Papers
ECRTM
45
50
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91.016291
all-MiniLM-L6-v2
0.97
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0.120231
0.926986
ArXiv ML Papers
ECRTM
46
50
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94.262968
all-MiniLM-L6-v2
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0.928781
BBC News
BERTopic
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878.928533
all-MiniLM-L6-v2
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0.603049
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10
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902.157574
all-MiniLM-L6-v2
0.5
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0.256275
0.610833
BBC News
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45
10
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881.797756
all-MiniLM-L6-v2
0.5
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0.256275
0.601131
BBC News
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46
10
[ [ "the", "of", "for", "is", "and", "that", "in", "to", "it", "said" ], [ "to", "for", "he", "of", "the", "in", "his", "we", "but", "and" ], [ "in", "of", "the", "was", "and", "his", "but", "open", "to", "for" ], [ "doping", "of", "drugs", "to", "the", "and", "greek", "for", "athens", "in" ], [ "indoor", "to", "in", "of", "she", "the", "her", "and", "race", "world" ] ]
836.7507
all-MiniLM-L6-v2
0.5
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0.256275
0.607718
BBC News
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43
20
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885.883228
all-MiniLM-L6-v2
0.5
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0.256275
0.612158
BBC News
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20
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856.648137
all-MiniLM-L6-v2
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0.256275
0.60994
BBC News
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20
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891.810742
all-MiniLM-L6-v2
0.5
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0.256275
0.604801
BBC News
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20
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870.464814
all-MiniLM-L6-v2
0.5
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0.256275
0.607233
BBC News
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30
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837.507406
all-MiniLM-L6-v2
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0.256275
0.610622
BBC News
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30
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629.620124
all-MiniLM-L6-v2
0.5
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0.256275
0.611601
BBC News
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30
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783.705856
all-MiniLM-L6-v2
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0.256275
0.599727
BBC News
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30
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743.55428
all-MiniLM-L6-v2
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0.256275
0.605389
BBC News
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40
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0.609603
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40
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all-MiniLM-L6-v2
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0.256275
0.605696
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40
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0.256275
0.603034
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40
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all-MiniLM-L6-v2
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0.256275
0.612705
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50
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0.256275
0.607666
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50
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0.256275
0.602802
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45
50
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795.812462
all-MiniLM-L6-v2
0.5
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0.256275
0.607512
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0.611343
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1.788574
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0.269654
0.570532
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10
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2.07404
all-MiniLM-L6-v2
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0.565647
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10
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0.269654
0.56901
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10
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2.463064
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0.269654
0.567671
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20
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2.887159
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0.000025
0.2376
0.583025
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20
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2.894762
all-MiniLM-L6-v2
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0.239007
0.584071
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45
20
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2.937413
all-MiniLM-L6-v2
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0.003874
0.244736
0.579699
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NMF
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7.060382
all-MiniLM-L6-v2
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BBC News
LDA
43
10
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7.357541
all-MiniLM-L6-v2
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