Scheduled Commit

data/2403.11703.json

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+{"paper_url": "https://huggingface.co/papers/2403.11703", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models](https://huggingface.co/papers/2403.03003) (2024)\n* [InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding](https://huggingface.co/papers/2403.01487) (2024)\n* [Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-Referring](https://huggingface.co/papers/2403.09333) (2024)\n* [TextMonkey: An OCR-Free Large Multimodal Model for Understanding Document](https://huggingface.co/papers/2403.04473) (2024)\n* [MouSi: Poly-Visual-Expert Vision-Language Models](https://huggingface.co/papers/2401.17221) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.11781.json

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+{"paper_url": "https://huggingface.co/papers/2403.11781", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations](https://huggingface.co/papers/2403.06951) (2024)\n* [DreamMatcher: Appearance Matching Self-Attention for Semantically-Consistent Text-to-Image Personalization](https://huggingface.co/papers/2402.09812) (2024)\n* [SeFi-IDE: Semantic-Fidelity Identity Embedding for Personalized Diffusion-Based Generation](https://huggingface.co/papers/2402.00631) (2024)\n* [OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models](https://huggingface.co/papers/2403.10983) (2024)\n* [Magic-Me: Identity-Specific Video Customized Diffusion](https://huggingface.co/papers/2402.09368) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.11901.json

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+{"paper_url": "https://huggingface.co/papers/2403.11901", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory](https://huggingface.co/papers/2402.13449) (2024)\n* [MEMORYLLM: Towards Self-Updatable Large Language Models](https://huggingface.co/papers/2402.04624) (2024)\n* [MemoryPrompt: A Light Wrapper to Improve Context Tracking in Pre-trained Language Models](https://huggingface.co/papers/2402.15268) (2024)\n* [Online Adaptation of Language Models with a Memory of Amortized Contexts](https://huggingface.co/papers/2403.04317) (2024)\n* [Long-Context Language Modeling with Parallel Context Encoding](https://huggingface.co/papers/2402.16617) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12008.json

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+{"paper_url": "https://huggingface.co/papers/2403.12008", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [Envision3D: One Image to 3D with Anchor Views Interpolation](https://huggingface.co/papers/2403.08902) (2024)\n* [SPAD : Spatially Aware Multiview Diffusers](https://huggingface.co/papers/2402.05235) (2024)\n* [CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization](https://huggingface.co/papers/2402.17214) (2024)\n* [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://huggingface.co/papers/2403.10395) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12015.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.12015", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [SDXL-Lightning: Progressive Adversarial Diffusion Distillation](https://huggingface.co/papers/2402.13929) (2024)\n* [SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation](https://huggingface.co/papers/2403.01505) (2024)\n* [AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning](https://huggingface.co/papers/2402.00769) (2024)\n* [ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models](https://huggingface.co/papers/2403.02084) (2024)\n* [Image Synthesis with Graph Conditioning: CLIP-Guided Diffusion Models for Scene Graphs](https://huggingface.co/papers/2401.14111) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12019.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.12019", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://huggingface.co/papers/2403.10395) (2024)\n* [SPAD : Spatially Aware Multiview Diffusers](https://huggingface.co/papers/2402.05235) (2024)\n* [3DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priors](https://huggingface.co/papers/2403.02234) (2024)\n* [Denoising Diffusion via Image-Based Rendering](https://huggingface.co/papers/2402.03445) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12032.json

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+{"paper_url": "https://huggingface.co/papers/2403.12032", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation](https://huggingface.co/papers/2402.08682) (2024)\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [2L3: Lifting Imperfect Generated 2D Images into Accurate 3D](https://huggingface.co/papers/2401.15841) (2024)\n* [CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization](https://huggingface.co/papers/2402.17214) (2024)\n* [Retrieval-Augmented Score Distillation for Text-to-3D Generation](https://huggingface.co/papers/2402.02972) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12034.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.12034", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](https://huggingface.co/papers/2402.05054) (2024)\n* [IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation](https://huggingface.co/papers/2402.08682) (2024)\n* [Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting](https://huggingface.co/papers/2403.09981) (2024)\n* [Envision3D: One Image to 3D with Anchor Views Interpolation](https://huggingface.co/papers/2403.08902) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12173.json

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+{"paper_url": "https://huggingface.co/papers/2403.12173", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research](https://huggingface.co/papers/2402.00159) (2024)\n* [A Survey of Pre-trained Language Models for Processing Scientific Text](https://huggingface.co/papers/2401.17824) (2024)\n* [Fine-grained Contract NER using instruction based model](https://huggingface.co/papers/2401.13545) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12365.json

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+{"paper_url": "https://huggingface.co/papers/2403.12365", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Motion-aware 3D Gaussian Splatting for Efficient Dynamic Scene Reconstruction](https://huggingface.co/papers/2403.11447) (2024)\n* [4D Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes](https://huggingface.co/papers/2402.03307) (2024)\n* [Recent Advances in 3D Gaussian Splatting](https://huggingface.co/papers/2403.11134) (2024)\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting](https://huggingface.co/papers/2402.10259) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12409.json

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+{"paper_url": "https://huggingface.co/papers/2403.12409", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting](https://huggingface.co/papers/2403.09981) (2024)\n* [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://huggingface.co/papers/2403.10395) (2024)\n* [CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model](https://huggingface.co/papers/2403.05034) (2024)\n* [GALA: Generating Animatable Layered Assets from a Single Scan](https://huggingface.co/papers/2401.12979) (2024)\n* [SPAD : Spatially Aware Multiview Diffusers](https://huggingface.co/papers/2402.05235) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12596.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.12596", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning](https://huggingface.co/papers/2403.09028) (2024)\n* [Distilling Mathematical Reasoning Capabilities into Small Language Models](https://huggingface.co/papers/2401.11864) (2024)\n* [ScreenAI: A Vision-Language Model for UI and Infographics Understanding](https://huggingface.co/papers/2402.04615) (2024)\n* [ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization](https://huggingface.co/papers/2403.11236) (2024)\n* [PaLM2-VAdapter: Progressively Aligned Language Model Makes a Strong Vision-language Adapter](https://huggingface.co/papers/2402.10896) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12706.json

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+{"paper_url": "https://huggingface.co/papers/2403.12706", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [SDXL-Lightning: Progressive Adversarial Diffusion Distillation](https://huggingface.co/papers/2402.13929) (2024)\n* [AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning](https://huggingface.co/papers/2402.00769) (2024)\n* [Animated Stickers: Bringing Stickers to Life with Video Diffusion](https://huggingface.co/papers/2402.06088) (2024)\n* [Video Editing via Factorized Diffusion Distillation](https://huggingface.co/papers/2403.09334) (2024)\n* [AtomoVideo: High Fidelity Image-to-Video Generation](https://huggingface.co/papers/2403.01800) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12881.json

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+{"paper_url": "https://huggingface.co/papers/2403.12881", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning](https://huggingface.co/papers/2402.15506) (2024)\n* [KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents](https://huggingface.co/papers/2403.03101) (2024)\n* [Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as Agents](https://huggingface.co/papers/2402.11651) (2024)\n* [LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration](https://huggingface.co/papers/2402.11550) (2024)\n* [Exploring Self-supervised Logic-enhanced Training for Large Language Models](https://huggingface.co/papers/2305.13718) (2023)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12895.json

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+{"paper_url": "https://huggingface.co/papers/2403.12895", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [TextMonkey: An OCR-Free Large Multimodal Model for Understanding Document](https://huggingface.co/papers/2403.04473) (2024)\n* [Enhancing Visual Document Understanding with Contrastive Learning in Large Visual-Language Models](https://huggingface.co/papers/2402.19014) (2024)\n* [Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding](https://huggingface.co/papers/2402.18262) (2024)\n* [InstructDoc: A Dataset for Zero-Shot Generalization of Visual Document Understanding with Instructions](https://huggingface.co/papers/2401.13313) (2024)\n* [Multi-modal Instruction Tuned LLMs with Fine-grained Visual Perception](https://huggingface.co/papers/2403.02969) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12906.json

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+{"paper_url": "https://huggingface.co/papers/2403.12906", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization](https://huggingface.co/papers/2402.17214) (2024)\n* [ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models](https://huggingface.co/papers/2403.01807) (2024)\n* [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://huggingface.co/papers/2403.10395) (2024)\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [Template-Free Single-View 3D Human Digitalization with Diffusion-Guided LRM](https://huggingface.co/papers/2401.12175) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12943.json

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+{"paper_url": "https://huggingface.co/papers/2403.12943", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [RT-H: Action Hierarchies Using Language](https://huggingface.co/papers/2403.01823) (2024)\n* [Large-Scale Actionless Video Pre-Training via Discrete Diffusion for Efficient Policy Learning](https://huggingface.co/papers/2402.14407) (2024)\n* [Spatiotemporal Predictive Pre-training for Robotic Motor Control](https://huggingface.co/papers/2403.05304) (2024)\n* [Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting](https://huggingface.co/papers/2402.19249) (2024)\n* [Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation](https://huggingface.co/papers/2402.19432) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12957.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.12957", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting](https://huggingface.co/papers/2403.09981) (2024)\n* [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](https://huggingface.co/papers/2402.05054) (2024)\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [Hyper-3DG: Text-to-3D Gaussian Generation via Hypergraph](https://huggingface.co/papers/2403.09236) (2024)\n* [Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting](https://huggingface.co/papers/2402.15870) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12962.json

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+{"paper_url": "https://huggingface.co/papers/2403.12962", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Human Video Translation via Query Warping](https://huggingface.co/papers/2402.12099) (2024)\n* [UniEdit: A Unified Tuning-Free Framework for Video Motion and Appearance Editing](https://huggingface.co/papers/2402.13185) (2024)\n* [Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling](https://huggingface.co/papers/2401.15977) (2024)\n* [Pix2Gif: Motion-Guided Diffusion for GIF Generation](https://huggingface.co/papers/2403.04634) (2024)\n* [FastVideoEdit: Leveraging Consistency Models for Efficient Text-to-Video Editing](https://huggingface.co/papers/2403.06269) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12963.json

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+{"paper_url": "https://huggingface.co/papers/2403.12963", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation](https://huggingface.co/papers/2402.10491) (2024)\n* [ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models](https://huggingface.co/papers/2403.02084) (2024)\n* [CasSR: Activating Image Power for Real-World Image Super-Resolution](https://huggingface.co/papers/2403.11451) (2024)\n* [Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder](https://huggingface.co/papers/2403.10255) (2024)\n* [Cross-view Masked Diffusion Transformers for Person Image Synthesis](https://huggingface.co/papers/2402.01516) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.12968.json

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+{"paper_url": "https://huggingface.co/papers/2403.12968", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Learning to Compress Prompt in Natural Language Formats](https://huggingface.co/papers/2402.18700) (2024)\n* [Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression](https://huggingface.co/papers/2402.16058) (2024)\n* [PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning](https://huggingface.co/papers/2402.12842) (2024)\n* [BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models](https://huggingface.co/papers/2402.11573) (2024)\n* [Identifying Factual Inconsistency in Summaries: Towards Effective Utilization of Large Language Model](https://huggingface.co/papers/2402.12821) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}