Scheduled Commit

data/2412.03123.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.03123", "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* [WaterPark: A Robustness Assessment of Language Model Watermarking](https://huggingface.co/papers/2411.13425) (2024)\n* [Revisiting the Robustness of Watermarking to Paraphrasing Attacks](https://huggingface.co/papers/2411.05277) (2024)\n* [CredID: Credible Multi-Bit Watermark for Large Language Models Identification](https://huggingface.co/papers/2412.03107) (2024)\n* [$B^4$: A Black-Box Scrubbing Attack on LLM Watermarks](https://huggingface.co/papers/2411.01222) (2024)\n* [A Watermark for Order-Agnostic Language Models](https://huggingface.co/papers/2410.13805) (2024)\n* [De-mark: Watermark Removal in Large Language Models](https://huggingface.co/papers/2410.13808) (2024)\n* [Provably Robust Watermarks for Open-Source Language Models](https://huggingface.co/papers/2410.18861) (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/2412.04144.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.04144", "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* [MoD: A Distribution-Based Approach for Merging Large Language Models](https://huggingface.co/papers/2411.00406) (2024)\n* [ATM: Improving Model Merging by Alternating Tuning and Merging](https://huggingface.co/papers/2411.03055) (2024)\n* [The Non-Local Model Merging Problem: Permutation Symmetries and Variance Collapse](https://huggingface.co/papers/2410.12766) (2024)\n* [Agent Skill Acquisition for Large Language Models via CycleQD](https://huggingface.co/papers/2410.14735) (2024)\n* [Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging](https://huggingface.co/papers/2410.21804) (2024)\n* [Unconstrained Model Merging for Enhanced LLM Reasoning](https://huggingface.co/papers/2410.13699) (2024)\n* [Model merging with SVD to tie the Knots](https://huggingface.co/papers/2410.19735) (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/2412.04432.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.04432", "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* [Mimir: Improving Video Diffusion Models for Precise Text Understanding](https://huggingface.co/papers/2412.03085) (2024)\n* [Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction](https://huggingface.co/papers/2411.14762) (2024)\n* [DiCoDe: Diffusion-Compressed Deep Tokens for Autoregressive Video Generation with Language Models](https://huggingface.co/papers/2412.04446) (2024)\n* [LinVT: Empower Your Image-level Large Language Model to Understand Videos](https://huggingface.co/papers/2412.05185) (2024)\n* [Espresso: High Compression For Rich Extraction From Videos for Your Vision-Language Model](https://huggingface.co/papers/2412.04729) (2024)\n* [Long Video Diffusion Generation with Segmented Cross-Attention and Content-Rich Video Data Curation](https://huggingface.co/papers/2412.01316) (2024)\n* [VideoRepair: Improving Text-to-Video Generation via Misalignment Evaluation and Localized Refinement](https://huggingface.co/papers/2411.15115) (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/2412.04470.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.04470", "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* [ModeDreamer: Mode Guiding Score Distillation for Text-to-3D Generation using Reference Image Prompts](https://huggingface.co/papers/2411.18135) (2024)\n* [DreamCraft3D++: Efficient Hierarchical 3D Generation with Multi-Plane Reconstruction Model](https://huggingface.co/papers/2410.12928) (2024)\n* [MVLight: Relightable Text-to-3D Generation via Light-conditioned Multi-View Diffusion](https://huggingface.co/papers/2411.11475) (2024)\n* [SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis](https://huggingface.co/papers/2411.16443) (2024)\n* [Sharp-It: A Multi-view to Multi-view Diffusion Model for 3D Synthesis and Manipulation](https://huggingface.co/papers/2412.02631) (2024)\n* [Tencent Hunyuan3D-1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation](https://huggingface.co/papers/2411.02293) (2024)\n* [Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation](https://huggingface.co/papers/2411.14384) (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/2412.05355.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.05355", "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* [MotionFlow: Attention-Driven Motion Transfer in Video Diffusion Models](https://huggingface.co/papers/2412.05275) (2024)\n* [Trajectory Attention for Fine-grained Video Motion Control](https://huggingface.co/papers/2411.19324) (2024)\n* [Optical-Flow Guided Prompt Optimization for Coherent Video Generation](https://huggingface.co/papers/2411.15540) (2024)\n* [Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution](https://huggingface.co/papers/2411.12072) (2024)\n* [MIDI: Multi-Instance Diffusion for Single Image to 3D Scene Generation](https://huggingface.co/papers/2412.03558) (2024)\n* [MoTrans: Customized Motion Transfer with Text-driven Video Diffusion Models](https://huggingface.co/papers/2412.01343) (2024)\n* [FrameBridge: Improving Image-to-Video Generation with Bridge Models](https://huggingface.co/papers/2410.15371) (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/2412.05718.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.05718", "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* [Real-World Offline Reinforcement Learning from Vision Language Model Feedback](https://huggingface.co/papers/2411.05273) (2024)\n* [Proto Successor Measure: Representing the Space of All Possible Solutions of Reinforcement Learning](https://huggingface.co/papers/2411.19418) (2024)\n* [Few-shot In-Context Preference Learning Using Large Language Models](https://huggingface.co/papers/2410.17233) (2024)\n* [Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning](https://huggingface.co/papers/2412.05515) (2024)\n* [PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement](https://huggingface.co/papers/2411.17764) (2024)\n* [ACING: Actor-Critic for Instruction Learning in Black-Box Large Language Models](https://huggingface.co/papers/2411.12736) (2024)\n* [R3HF: Reward Redistribution for Enhancing Reinforcement Learning from Human Feedback](https://huggingface.co/papers/2411.08302) (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/2412.05939.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.05939", "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* [Grounding Descriptions in Images informs Zero-Shot Visual Recognition](https://huggingface.co/papers/2412.04429) (2024)\n* [Grounding-IQA: Multimodal Language Grounding Model for Image Quality Assessment](https://huggingface.co/papers/2411.17237) (2024)\n* [CompCap: Improving Multimodal Large Language Models with Composite Captions](https://huggingface.co/papers/2412.05243) (2024)\n* [BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions](https://huggingface.co/papers/2411.07461) (2024)\n* [Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation](https://huggingface.co/papers/2411.05316) (2024)\n* [Retrieval-Augmented Personalization for Multimodal Large Language Models](https://huggingface.co/papers/2410.13360) (2024)\n* [LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation](https://huggingface.co/papers/2411.09301) (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/2412.06464.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.06464", "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* [Taipan: Efficient and Expressive State Space Language Models with Selective Attention](https://huggingface.co/papers/2410.18572) (2024)\n* [Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers](https://huggingface.co/papers/2411.12118) (2024)\n* [Hymba: A Hybrid-head Architecture for Small Language Models](https://huggingface.co/papers/2411.13676) (2024)\n* [The Evolution of RWKV: Advancements in Efficient Language Modeling](https://huggingface.co/papers/2411.02795) (2024)\n* [Birdie: Advancing State Space Models with Reward-Driven Objectives and Curricula](https://huggingface.co/papers/2411.01030) (2024)\n* [KV Shifting Attention Enhances Language Modeling](https://huggingface.co/papers/2411.19574) (2024)\n* [Revealing and Mitigating the Local Pattern Shortcuts of Mamba](https://huggingface.co/papers/2410.15678) (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/2412.06531.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.06531", "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* [A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedback](https://huggingface.co/papers/2411.13410) (2024)\n* [The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning](https://huggingface.co/papers/2411.10175) (2024)\n* [Comprehensive Survey of Reinforcement Learning: From Algorithms to Practical Challenges](https://huggingface.co/papers/2411.18892) (2024)\n* [RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm](https://huggingface.co/papers/2411.08392) (2024)\n* [Integrating Reinforcement Learning with Foundation Models for Autonomous Robotics: Methods and Perspectives](https://huggingface.co/papers/2410.16411) (2024)\n* [Learning Memory Mechanisms for Decision Making through Demonstrations](https://huggingface.co/papers/2411.07954) (2024)\n* [Guiding Reinforcement Learning Using Uncertainty-Aware Large Language Models](https://huggingface.co/papers/2411.14457) (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/2412.06559.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.06559", "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* [Enhancing Mathematical Reasoning in LLMs by Stepwise Correction](https://huggingface.co/papers/2410.12934) (2024)\n* [Not All Votes Count! Programs as Verifiers Improve Self-Consistency of Language Models for Math Reasoning](https://huggingface.co/papers/2410.12608) (2024)\n* [Preference Optimization for Reasoning with Pseudo Feedback](https://huggingface.co/papers/2411.16345) (2024)\n* [Guiding Through Complexity: What Makes Good Supervision for Hard Reasoning Tasks?](https://huggingface.co/papers/2410.20533) (2024)\n* [A Comparative Study on Reasoning Patterns of OpenAI's o1 Model](https://huggingface.co/papers/2410.13639) (2024)\n* [ReasonAgain: Using Extractable Symbolic Programs to Evaluate Mathematical Reasoning](https://huggingface.co/papers/2410.19056) (2024)\n* [Embedding Self-Correction as an Inherent Ability in Large Language Models for Enhanced Mathematical Reasoning](https://huggingface.co/papers/2410.10735) (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/2412.06699.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2412.06699", "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* [MVGenMaster: Scaling Multi-View Generation from Any Image via 3D Priors Enhanced Diffusion Model](https://huggingface.co/papers/2411.16157) (2024)\n* [GenXD: Generating Any 3D and 4D Scenes](https://huggingface.co/papers/2411.02319) (2024)\n* [World-consistent Video Diffusion with Explicit 3D Modeling](https://huggingface.co/papers/2412.01821) (2024)\n* [NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images](https://huggingface.co/papers/2412.03517) (2024)\n* [3DGS-Enhancer: Enhancing Unbounded 3D Gaussian Splatting with View-consistent 2D Diffusion Priors](https://huggingface.co/papers/2410.16266) (2024)\n* [MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views](https://huggingface.co/papers/2411.04924) (2024)\n* [SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis](https://huggingface.co/papers/2411.16443) (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`"}