Scheduled Commit

data/2509.22067.json

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+{"paper_url": "https://huggingface.co/papers/2509.22067", "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* [Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection](https://huggingface.co/papers/2508.20766) (2025)\n* [LatentGuard: Controllable Latent Steering for Robust Refusal of Attacks and Reliable Response Generation](https://huggingface.co/papers/2509.19839) (2025)\n* [CorrSteer: Steering Improves Task Performance and Safety in LLMs through Correlation-based Sparse Autoencoder Feature Selection](https://huggingface.co/papers/2508.12535) (2025)\n* [Steering MoE LLMs via Expert (De)Activation](https://huggingface.co/papers/2509.09660) (2025)\n* [Mitigating Jailbreaks with Intent-Aware LLMs](https://huggingface.co/papers/2508.12072) (2025)\n* [Safety Alignment Should Be Made More Than Just A Few Attention Heads](https://huggingface.co/papers/2508.19697) (2025)\n* [ASGuard: Activation-Scaling Guard to Mitigate Targeted Jailbreaking Attack](https://huggingface.co/papers/2509.25843) (2025)\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/2509.22582.json

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+{"paper_url": "https://huggingface.co/papers/2509.22582", "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* [PerHalluEval: Persian Hallucination Evaluation Benchmark for Large Language Models](https://huggingface.co/papers/2509.21104) (2025)\n* [FineDialFact: A benchmark for Fine-grained Dialogue Fact Verification](https://huggingface.co/papers/2508.05782) (2025)\n* [Zero-knowledge LLM hallucination detection and mitigation through fine-grained cross-model consistency](https://huggingface.co/papers/2508.14314) (2025)\n* [Learning to Reason for Hallucination Span Detection](https://huggingface.co/papers/2510.02173) (2025)\n* [ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding](https://huggingface.co/papers/2509.17481) (2025)\n* [KnowDR-REC: A Benchmark for Referring Expression Comprehension with Real-World Knowledge](https://huggingface.co/papers/2508.14080) (2025)\n* [Self-Consistency as a Free Lunch: Reducing Hallucinations in Vision-Language Models via Self-Reflection](https://huggingface.co/papers/2509.23236) (2025)\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/2509.26313.json

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+{"paper_url": "https://huggingface.co/papers/2509.26313", "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* [On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification](https://huggingface.co/papers/2508.05629) (2025)\n* [Proximal Supervised Fine-Tuning](https://huggingface.co/papers/2508.17784) (2025)\n* [Anchored Supervised Fine-Tuning](https://huggingface.co/papers/2509.23753) (2025)\n* [On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting](https://huggingface.co/papers/2508.11408) (2025)\n* [Towards a Unified View of Large Language Model Post-Training](https://huggingface.co/papers/2509.04419) (2025)\n* [More Than One Teacher: Adaptive Multi-Guidance Policy Optimization for Diverse Exploration](https://huggingface.co/papers/2510.02227) (2025)\n* [CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning](https://huggingface.co/papers/2508.15868) (2025)\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/2509.26376.json

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+{"paper_url": "https://huggingface.co/papers/2509.26376", "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* [SoftCFG: Uncertainty-guided Stable Guidance for Visual Autoregressive Model](https://huggingface.co/papers/2510.00996) (2025)\n* [NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale](https://huggingface.co/papers/2508.10711) (2025)\n* [STAGE: Stable and Generalizable GRPO for Autoregressive Image Generation](https://huggingface.co/papers/2509.25027) (2025)\n* [Growing Visual Generative Capacity for Pre-Trained MLLMs](https://huggingface.co/papers/2510.01546) (2025)\n* [Group Critical-token Policy Optimization for Autoregressive Image Generation](https://huggingface.co/papers/2509.22485) (2025)\n* [AR-GRPO: Training Autoregressive Image Generation Models via Reinforcement Learning](https://huggingface.co/papers/2508.06924) (2025)\n* [AdaBlock-dLLM: Semantic-Aware Diffusion LLM Inference via Adaptive Block Size](https://huggingface.co/papers/2509.26432) (2025)\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/2510.00352.json

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+{"paper_url": "https://huggingface.co/papers/2510.00352", "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* [TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusion](https://huggingface.co/papers/2509.25171) (2025)\n* [SPREAD: Sampling-based Pareto front Refinement via Efficient Adaptive Diffusion](https://huggingface.co/papers/2509.21058) (2025)\n* [RAPID^3: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer](https://huggingface.co/papers/2509.22323) (2025)\n* [Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation](https://huggingface.co/papers/2508.16521) (2025)\n* [MetaDiT: Enabling Fine-grained Constraints in High-degree-of Freedom Metasurface Design](https://huggingface.co/papers/2508.05076) (2025)\n* [CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration](https://huggingface.co/papers/2509.17458) (2025)\n* [Test-Time Anchoring for Discrete Diffusion Posterior Sampling](https://huggingface.co/papers/2510.02291) (2025)\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/2510.00446.json

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+{"paper_url": "https://huggingface.co/papers/2510.00446", "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* [DSPC: Dual-Stage Progressive Compression Framework for Efficient Long-Context Reasoning](https://huggingface.co/papers/2509.13723) (2025)\n* [SCOPE: A Generative Approach for LLM Prompt Compression](https://huggingface.co/papers/2508.15813) (2025)\n* [Impact-driven Context Filtering For Cross-file Code Completion](https://huggingface.co/papers/2508.05970) (2025)\n* [UniGist: Towards General and Hardware-aligned Sequence-level Long Context Compression](https://huggingface.co/papers/2509.15763) (2025)\n* [PagedEviction: Structured Block-wise KV Cache Pruning for Efficient Large Language Model Inference](https://huggingface.co/papers/2509.04377) (2025)\n* [SynthCoder: A Synthetical Strategy to Tune LLMs for Code Completion](https://huggingface.co/papers/2508.15495) (2025)\n* [SlimInfer: Accelerating Long-Context LLM Inference via Dynamic Token Pruning](https://huggingface.co/papers/2508.06447) (2025)\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/2510.00523.json

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+{"paper_url": "https://huggingface.co/papers/2510.00523", "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* [Patch-as-Decodable-Token: Towards Unified Multi-Modal Vision Tasks in MLLMs](https://huggingface.co/papers/2510.01954) (2025)\n* [Vision-Free Retrieval: Rethinking Multimodal Search with Textual Scene Descriptions](https://huggingface.co/papers/2509.19203) (2025)\n* [X-SAM: From Segment Anything to Any Segmentation](https://huggingface.co/papers/2508.04655) (2025)\n* [Think Before You Segment: An Object-aware Reasoning Agent for Referring Audio-Visual Segmentation](https://huggingface.co/papers/2508.04418) (2025)\n* [Dual Prompt Learning for Adapting Vision-Language Models to Downstream Image-Text Retrieval](https://huggingface.co/papers/2508.04028) (2025)\n* [Text4Seg++: Advancing Image Segmentation via Generative Language Modeling](https://huggingface.co/papers/2509.06321) (2025)\n* [LENS: Learning to Segment Anything with Unified Reinforced Reasoning](https://huggingface.co/papers/2508.14153) (2025)\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/2510.00537.json

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+{"paper_url": "https://huggingface.co/papers/2510.00537", "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* [Model Merging Scaling Laws in Large Language Models](https://huggingface.co/papers/2509.24244) (2025)\n* [Share Your Attention: Transformer Weight Sharing via Matrix-based Dictionary Learning](https://huggingface.co/papers/2508.04581) (2025)\n* [Scaling with Collapse: Efficient and Predictable Training of LLM Families](https://huggingface.co/papers/2509.25087) (2025)\n* [Scaling Laws are Redundancy Laws](https://huggingface.co/papers/2509.20721) (2025)\n* [xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity](https://huggingface.co/papers/2510.02228) (2025)\n* [Investigating ReLoRA: Effects on the Learning Dynamics of Small Language Models](https://huggingface.co/papers/2509.12960) (2025)\n* [Scaling Laws for Task-Stratified Knowledge in Post-Training Quantized Large Language Models](https://huggingface.co/papers/2508.18609) (2025)\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/2510.01149.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.01149", "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* [MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction](https://huggingface.co/papers/2509.18095) (2025)\n* [Vision-Free Retrieval: Rethinking Multimodal Search with Textual Scene Descriptions](https://huggingface.co/papers/2509.19203) (2025)\n* [Training LLMs to be Better Text Embedders through Bidirectional Reconstruction](https://huggingface.co/papers/2509.03020) (2025)\n* [CMRAG: Co-modality-based visual document retrieval and question answering](https://huggingface.co/papers/2509.02123) (2025)\n* [SERVAL: Surprisingly Effective Zero-Shot Visual Document Retrieval Powered by Large Vision and Language Models](https://huggingface.co/papers/2509.15432) (2025)\n* [Zero-shot Multimodal Document Retrieval via Cross-modal Question Generation](https://huggingface.co/papers/2508.17079) (2025)\n* [DocPruner: A Storage-Efficient Framework for Multi-Vector Visual Document Retrieval via Adaptive Patch-Level Embedding Pruning](https://huggingface.co/papers/2509.23883) (2025)\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/2510.01241.json

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+{"paper_url": "https://huggingface.co/papers/2510.01241", "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* [EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving](https://huggingface.co/papers/2509.17677) (2025)\n* [An Investigation of Robustness of LLMs in Mathematical Reasoning: Benchmarking with Mathematically-Equivalent Transformation of Advanced Mathematical Problems](https://huggingface.co/papers/2508.08833) (2025)\n* [RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning](https://huggingface.co/papers/2509.07711) (2025)\n* [Look Before you Leap: Estimating LLM Benchmark Scores from Descriptions](https://huggingface.co/papers/2509.20645) (2025)\n* [MathSticks: A Benchmark for Visual Symbolic Compositional Reasoning with Matchstick Puzzles](https://huggingface.co/papers/2510.00483) (2025)\n* [InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information](https://huggingface.co/papers/2508.07630) (2025)\n* [MDK12-Bench: A Comprehensive Evaluation of Multimodal Large Language Models on Multidisciplinary Exams](https://huggingface.co/papers/2508.06851) (2025)\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/2510.01581.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.01581", "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* [Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking](https://huggingface.co/papers/2509.23392) (2025)\n* [Train Long, Think Short: Curriculum Learning for Efficient Reasoning](https://huggingface.co/papers/2508.08940) (2025)\n* [Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning](https://huggingface.co/papers/2508.09726) (2025)\n* [BudgetThinker: Empowering Budget-aware LLM Reasoning with Control Tokens](https://huggingface.co/papers/2508.17196) (2025)\n* [Less is More Tokens: Efficient Math Reasoning via Difficulty-Aware Chain-of-Thought Distillation](https://huggingface.co/papers/2509.05226) (2025)\n* [Promoting Efficient Reasoning with Verifiable Stepwise Reward](https://huggingface.co/papers/2508.10293) (2025)\n* [Aware First, Think Less: Dynamic Boundary Self-Awareness Drives Extreme Reasoning Efficiency in Large Language Models](https://huggingface.co/papers/2508.11582) (2025)\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/2510.01623.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.01623", "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* [HOID-R1: Reinforcement Learning for Open-World Human-Object Interaction Detection Reasoning with Multimodal Large Language Model](https://huggingface.co/papers/2508.11350) (2025)\n* [UAV-VL-R1: Generalizing Vision-Language Models via Supervised Fine-Tuning and Multi-Stage GRPO for UAV Visual Reasoning](https://huggingface.co/papers/2508.11196) (2025)\n* [AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving](https://huggingface.co/papers/2509.01944) (2025)\n* [Reinforcing Video Reasoning Segmentation to Think Before It Segments](https://huggingface.co/papers/2508.11538) (2025)\n* [Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation](https://huggingface.co/papers/2508.13998) (2025)\n* [Igniting VLMs toward the Embodied Space](https://huggingface.co/papers/2509.11766) (2025)\n* [Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey](https://huggingface.co/papers/2508.13073) (2025)\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/2510.01670.json

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+{"paper_url": "https://huggingface.co/papers/2510.01670", "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* [LM Agents May Fail to Act on Their Own Risk Knowledge](https://huggingface.co/papers/2508.13465) (2025)\n* [The Unreasonable Effectiveness of Scaling Agents for Computer Use](https://huggingface.co/papers/2510.02250) (2025)\n* [OpenCUA: Open Foundations for Computer-Use Agents](https://huggingface.co/papers/2508.09123) (2025)\n* [Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight](https://huggingface.co/papers/2509.10723) (2025)\n* [Say One Thing, Do Another? Diagnosing Reasoning-Execution Gaps in VLM-Powered Mobile-Use Agents](https://huggingface.co/papers/2510.02204) (2025)\n* [Reliable Weak-to-Strong Monitoring of LLM Agents](https://huggingface.co/papers/2508.19461) (2025)\n* [Plan Verification for LLM-Based Embodied Task Completion Agents](https://huggingface.co/papers/2509.02761) (2025)\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/2510.02240.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.02240", "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* [Perception Before Reasoning: Two-Stage Reinforcement Learning for Visual Reasoning in Vision-Language Models](https://huggingface.co/papers/2509.13031) (2025)\n* [Can GRPO Boost Complex Multimodal Table Understanding?](https://huggingface.co/papers/2509.16889) (2025)\n* [Agentic Jigsaw Interaction Learning for Enhancing Visual Perception and Reasoning in Vision-Language Models](https://huggingface.co/papers/2510.01304) (2025)\n* [Latent Visual Reasoning](https://huggingface.co/papers/2509.24251) (2025)\n* [Self-Rewarding Vision-Language Model via Reasoning Decomposition](https://huggingface.co/papers/2508.19652) (2025)\n* [Breaking the SFT Plateau: Multimodal Structured Reinforcement Learning for Chart-to-Code Generation](https://huggingface.co/papers/2508.13587) (2025)\n* [SIFThinker: Spatially-Aware Image Focus for Visual Reasoning](https://huggingface.co/papers/2508.06259) (2025)\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/2510.02259.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.02259", "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 Inter-Atomic Potentials without Explicit Equivariance](https://huggingface.co/papers/2510.00027) (2025)\n* [ADAPT: Lightweight, Long-Range Machine Learning Force Fields Without Graphs](https://huggingface.co/papers/2509.24115) (2025)\n* [Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining](https://huggingface.co/papers/2509.22468) (2025)\n* [Facet: highly efficient E(3)-equivariant networks for interatomic potentials](https://huggingface.co/papers/2509.08418) (2025)\n* [MCGM: Multi-stage Clustered Global Modeling for Long-range Interactions in Molecules](https://huggingface.co/papers/2509.22028) (2025)\n* [Benchmarking Pretrained Molecular Embedding Models For Molecular Representation Learning](https://huggingface.co/papers/2508.06199) (2025)\n* [FIRE-GNN: Force-informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties](https://huggingface.co/papers/2508.16012) (2025)\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/2510.02286.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.02286", "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* [MUSE: MCTS-Driven Red Teaming Framework for Enhanced Multi-Turn Dialogue Safety in Large Language Models](https://huggingface.co/papers/2509.14651) (2025)\n* [Automatic LLM Red Teaming](https://huggingface.co/papers/2508.04451) (2025)\n* [Active Attacks: Red-teaming LLMs via Adaptive Environments](https://huggingface.co/papers/2509.21947) (2025)\n* [LLaVAShield: Safeguarding Multimodal Multi-Turn Dialogues in Vision-Language Models](https://huggingface.co/papers/2509.25896) (2025)\n* [bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs](https://huggingface.co/papers/2509.19775) (2025)\n* [SafeBehavior: Simulating Human-Like Multistage Reasoning to Mitigate Jailbreak Attacks in Large Language Models](https://huggingface.co/papers/2509.26345) (2025)\n* [Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning](https://huggingface.co/papers/2508.20697) (2025)\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/2510.02294.json

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+{"paper_url": "https://huggingface.co/papers/2510.02294", "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* [Granite Embedding R2 Models](https://huggingface.co/papers/2508.21085) (2025)\n* [EmbeddingGemma: Powerful and Lightweight Text Representations](https://huggingface.co/papers/2509.20354) (2025)\n* [Training LLMs to be Better Text Embedders through Bidirectional Reconstruction](https://huggingface.co/papers/2509.03020) (2025)\n* [MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch](https://huggingface.co/papers/2509.12340) (2025)\n* [Conan-Embedding-v2: Training an LLM from Scratch for Text Embeddings](https://huggingface.co/papers/2509.12892) (2025)\n* [BiXSE: Improving Dense Retrieval via Probabilistic Graded Relevance Distillation](https://huggingface.co/papers/2508.06781) (2025)\n* [QZhou-Embedding Technical Report](https://huggingface.co/papers/2508.21632) (2025)\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/2510.02295.json

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+{"paper_url": "https://huggingface.co/papers/2510.02295", "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* [StreamMem: Query-Agnostic KV Cache Memory for Streaming Video Understanding](https://huggingface.co/papers/2508.15717) (2025)\n* [Dense Video Understanding with Gated Residual Tokenization](https://huggingface.co/papers/2509.14199) (2025)\n* [From Frames to Clips: Efficient Key Clip Selection for Long-Form Video Understanding](https://huggingface.co/papers/2510.02262) (2025)\n* [An Empirical Study on How Video-LLMs Answer Video Questions](https://huggingface.co/papers/2508.15360) (2025)\n* [Bidirectional Sparse Attention for Faster Video Diffusion Training](https://huggingface.co/papers/2509.01085) (2025)\n* [Video Panels for Long Video Understanding](https://huggingface.co/papers/2509.23724) (2025)\n* [VideoAnchor: Reinforcing Subspace-Structured Visual Cues for Coherent Visual-Spatial Reasoning](https://huggingface.co/papers/2509.25151) (2025)\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/2510.02306.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.02306", "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* [Inclusion Arena: An Open Platform for Evaluating Large Foundation Models with Real-World Apps](https://huggingface.co/papers/2508.11452) (2025)\n* [LLMsPark: A Benchmark for Evaluating Large Language Models in Strategic Gaming Contexts](https://huggingface.co/papers/2509.16610) (2025)\n* [Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings](https://huggingface.co/papers/2508.11847) (2025)\n* [REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking](https://huggingface.co/papers/2508.18379) (2025)\n* [User-centric Subjective Leaderboard by Customizable Reward Modeling](https://huggingface.co/papers/2508.09463) (2025)\n* [Model Consistency as a Cheap yet Predictive Proxy for LLM Elo Scores](https://huggingface.co/papers/2509.23510) (2025)\n* [Can Large Models Fool the Eye? A New Turing Test for Biological Animation](https://huggingface.co/papers/2508.06072) (2025)\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/2510.02315.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2510.02315", "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* [Training-Free Reward-Guided Image Editing via Trajectory Optimal Control](https://huggingface.co/papers/2509.25845) (2025)\n* [MaskAttn-SDXL: Controllable Region-Level Text-To-Image Generation](https://huggingface.co/papers/2509.15357) (2025)\n* [CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration](https://huggingface.co/papers/2509.17458) (2025)\n* [MultiCrafter: High-Fidelity Multi-Subject Generation via Spatially Disentangled Attention and Identity-Aware Reinforcement Learning](https://huggingface.co/papers/2509.21953) (2025)\n* [DisCo: Reinforcement with Diversity Constraints for Multi-Human Generation](https://huggingface.co/papers/2510.01399) (2025)\n* [Prompt-Guided Dual Latent Steering for Inversion Problems](https://huggingface.co/papers/2509.18619) (2025)\n* [WorldForge: Unlocking Emergent 3D/4D Generation in Video Diffusion Model via Training-Free Guidance](https://huggingface.co/papers/2509.15130) (2025)\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`"}