Scheduled Commit

data/2601.13097.json

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+{"paper_url": "https://huggingface.co/papers/2601.13097", "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* [TAM-Eval: Evaluating LLMs for Automated Unit Test Maintenance](https://huggingface.co/papers/2601.18241) (2026)\n* [TerraFormer: Automated Infrastructure-as-Code with LLMs Fine-Tuned via Policy-Guided Verifier Feedback](https://huggingface.co/papers/2601.08734) (2026)\n* [GRPO with State Mutations: Improving LLM-Based Hardware Test Plan Generation](https://huggingface.co/papers/2601.07593) (2026)\n* [M2G-Eval: Enhancing and Evaluating Multi-granularity Multilingual Code Generation](https://huggingface.co/papers/2512.22628) (2025)\n* [SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories](https://huggingface.co/papers/2601.13713) (2026)\n* [Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization](https://huggingface.co/papers/2601.04582) (2026)\n* [Parameter-Efficient Multi-Task Fine-Tuning in Code-Related Tasks](https://huggingface.co/papers/2601.15094) (2026)\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/2601.15394.json

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+{"paper_url": "https://huggingface.co/papers/2601.15394", "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* [Unintended Memorization of Sensitive Information in Fine-Tuned Language Models](https://huggingface.co/papers/2601.17480) (2026)\n* [Distilling the Essence: Efficient Reasoning Distillation via Sequence Truncation](https://huggingface.co/papers/2512.21002) (2025)\n* [Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models](https://huggingface.co/papers/2601.18734) (2026)\n* [CTIGuardian: A Few-Shot Framework for Mitigating Privacy Leakage in Fine-Tuned LLMs](https://huggingface.co/papers/2512.12914) (2025)\n* [In-Context Probing for Membership Inference in Fine-Tuned Language Models](https://huggingface.co/papers/2512.16292) (2025)\n* [On the Effectiveness of Membership Inference in Targeted Data Extraction from Large Language Models](https://huggingface.co/papers/2512.13352) (2025)\n* [Stable On-Policy Distillation through Adaptive Target Reformulation](https://huggingface.co/papers/2601.07155) (2026)\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/2601.15625.json

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+{"paper_url": "https://huggingface.co/papers/2601.15625", "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* [CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning](https://huggingface.co/papers/2601.15141) (2026)\n* [From Failure to Mastery: Generating Hard Samples for Tool-use Agents](https://huggingface.co/papers/2601.01498) (2026)\n* [Teaching LLMs to Learn Tool Trialing and Execution through Environment Interaction](https://huggingface.co/papers/2601.12762) (2026)\n* [Close the Loop: Synthesizing Infinite Tool-Use Data via Multi-Agent Role-Playing](https://huggingface.co/papers/2512.23611) (2025)\n* [AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent](https://huggingface.co/papers/2512.20745) (2025)\n* [AWPO: Enhancing Tool-Use of Large Language Models through Explicit Integration of Reasoning Rewards](https://huggingface.co/papers/2512.19126) (2025)\n* [MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching](https://huggingface.co/papers/2601.10712) (2026)\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/2601.18241.json

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+{"paper_url": "https://huggingface.co/papers/2601.18241", "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* [RM -RF: Reward Model for Run-Free Unit Test Evaluation](https://huggingface.co/papers/2601.13097) (2026)\n* [ABC-Bench: Benchmarking Agentic Backend Coding in Real-World Development](https://huggingface.co/papers/2601.11077) (2026)\n* [How well LLM-based test generation techniques perform with newer LLM versions?](https://huggingface.co/papers/2601.09695) (2026)\n* [Fixturize: Bridging the Fixture Gap in Test Generation](https://huggingface.co/papers/2601.06615) (2026)\n* [SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios](https://huggingface.co/papers/2512.18470) (2025)\n* [SWE-Bench++: A Framework for the Scalable Generation of Software Engineering Benchmarks from Open-Source Repositories](https://huggingface.co/papers/2512.17419) (2025)\n* [Multi-Docker-Eval: A 'Shovel of the Gold Rush' Benchmark on Automatic Environment Building for Software Engineering](https://huggingface.co/papers/2512.06915) (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/2601.20218.json

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+{"paper_url": "https://huggingface.co/papers/2601.20218", "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* [Anchoring Values in Temporal and Group Dimensions for Flow Matching Model Alignment](https://huggingface.co/papers/2512.12387) (2025)\n* [TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment](https://huggingface.co/papers/2601.05729) (2026)\n* [TreeGRPO: Tree-Advantage GRPO for Online RL Post-Training of Diffusion Models](https://huggingface.co/papers/2512.08153) (2025)\n* [FlowSE-GRPO: Training Flow Matching Speech Enhancement via Online Reinforcement Learning](https://huggingface.co/papers/2601.16483) (2026)\n* [E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models](https://huggingface.co/papers/2601.00423) (2026)\n* [SuperFlow: Training Flow Matching Models with RL on the Fly](https://huggingface.co/papers/2512.17951) (2025)\n* [HyperAlign: Hypernetwork for Efficient Test-Time Alignment of Diffusion Models](https://huggingface.co/papers/2601.15968) (2026)\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/2601.20732.json

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+{"paper_url": "https://huggingface.co/papers/2601.20732", "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* [MagicGUI-RMS: A Multi-Agent Reward Model System for Self-Evolving GUI Agents via Automated Feedback Reflux](https://huggingface.co/papers/2601.13060) (2026)\n* [MAGNET: Towards Adaptive GUI Agents with Memory-Driven Knowledge Evolution](https://huggingface.co/papers/2601.19199) (2026)\n* [MobileDreamer: Generative Sketch World Model for GUI Agent](https://huggingface.co/papers/2601.04035) (2026)\n* [OmegaUse: Building a General-Purpose GUI Agent for Autonomous Task Execution](https://huggingface.co/papers/2601.20380) (2026)\n* [GAIA: A Data Flywheel System for Training GUI Test-Time Scaling Critic Models](https://huggingface.co/papers/2601.18197) (2026)\n* [Training One Model to Master Cross-Level Agentic Actions via Reinforcement Learning](https://huggingface.co/papers/2512.09706) (2025)\n* [EvoCUA: Evolving Computer Use Agents via Learning from Scalable Synthetic Experience](https://huggingface.co/papers/2601.15876) (2026)\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/2601.21192.json

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+{"paper_url": "https://huggingface.co/papers/2601.21192", "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* [SemPA: Improving Sentence Embeddings of Large Language Models through Semantic Preference Alignment](https://huggingface.co/papers/2601.05075) (2026)\n* [Learn Before Represent: Bridging Generative and Contrastive Learning for Domain-Specific LLM Embeddings](https://huggingface.co/papers/2601.11124) (2026)\n* [Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs](https://huggingface.co/papers/2512.17206) (2025)\n* [Generative Giants, Retrieval Weaklings: Why do Multimodal Large Language Models Fail at Multimodal Retrieval?](https://huggingface.co/papers/2512.19115) (2025)\n* [Closing the Modality Reasoning Gap for Speech Large Language Models](https://huggingface.co/papers/2601.05543) (2026)\n* [Next-Embedding Prediction Makes Strong Vision Learners](https://huggingface.co/papers/2512.16922) (2025)\n* [ECR: Manifold-Guided Semantic Cues for Compact Language Models](https://huggingface.co/papers/2601.00543) (2026)\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/2601.21358.json

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+{"paper_url": "https://huggingface.co/papers/2601.21358", "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* [Forest Before Trees: Latent Superposition for Efficient Visual Reasoning](https://huggingface.co/papers/2601.06803) (2026)\n* [Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning](https://huggingface.co/papers/2601.14750) (2026)\n* [Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs](https://huggingface.co/papers/2512.17206) (2025)\n* [Efficient Paths and Dense Rewards: Probabilistic Flow Reasoning for Large Language Models](https://huggingface.co/papers/2601.09260) (2026)\n* [Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge](https://huggingface.co/papers/2601.08808) (2026)\n* [LaViT: Aligning Latent Visual Thoughts for Multi-modal Reasoning](https://huggingface.co/papers/2601.10129) (2026)\n* [iCLP: Large Language Model Reasoning with Implicit Cognition Latent Planning](https://huggingface.co/papers/2512.24014) (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/2601.21419.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21419", "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* [PILD: Physics-Informed Learning via Diffusion](https://huggingface.co/papers/2601.21284) (2026)\n* [Control Variate Score Matching for Diffusion Models](https://huggingface.co/papers/2512.20003) (2025)\n* [Residual Prior Diffusion: A Probabilistic Framework Integrating Coarse Latent Priors with Diffusion Models](https://huggingface.co/papers/2512.21593) (2025)\n* [Recursive Flow: A Generative Framework for MIMO Channel Estimation](https://huggingface.co/papers/2601.15767) (2026)\n* [Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance](https://huggingface.co/papers/2601.08379) (2026)\n* [Parallel Diffusion Solver via Residual Dirichlet Policy Optimization](https://huggingface.co/papers/2512.22796) (2025)\n* [Lazy Diffusion: Mitigating spectral collapse in generative diffusion-based stable autoregressive emulation of turbulent flows](https://huggingface.co/papers/2512.09572) (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/2601.21468.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21468", "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* [AgentOCR: Reimagining Agent History via Optical Self-Compression](https://huggingface.co/papers/2601.04786) (2026)\n* [Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management](https://huggingface.co/papers/2601.08435) (2026)\n* [AtomMem : Learnable Dynamic Agentic Memory with Atomic Memory Operation](https://huggingface.co/papers/2601.08323) (2026)\n* [Implicit Graph, Explicit Retrieval: Towards Efficient and Interpretable Long-horizon Memory for Large Language Models](https://huggingface.co/papers/2601.03417) (2026)\n* [E-mem: Multi-agent based Episodic Context Reconstruction for LLM Agent Memory](https://huggingface.co/papers/2601.21714) (2026)\n* [VTC-R1: Vision-Text Compression for Efficient Long-Context Reasoning](https://huggingface.co/papers/2601.22069) (2026)\n* [LongVideoAgent: Multi-Agent Reasoning with Long Videos](https://huggingface.co/papers/2512.20618) (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/2601.21525.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21525", "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* [KV-Embedding: Training-free Text Embedding via Internal KV Re-routing in Decoder-only LLMs](https://huggingface.co/papers/2601.01046) (2026)\n* [Sequence Repetition Enhances Token Embeddings and Improves Sequence Labeling with Decoder-only Language Models](https://huggingface.co/papers/2601.17585) (2026)\n* [CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding](https://huggingface.co/papers/2601.21262) (2026)\n* [ReinPool: Reinforcement Learning Pooling Multi-Vector Embeddings for Retrieval System](https://huggingface.co/papers/2601.07125) (2026)\n* [Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings](https://huggingface.co/papers/2512.12167) (2025)\n* [BERT-JEPA: Reorganizing CLS Embeddings for Language-Invariant Semantics](https://huggingface.co/papers/2601.00366) (2026)\n* [Next-Embedding Prediction Makes Strong Vision Learners](https://huggingface.co/papers/2512.16922) (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/2601.21526.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21526", "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* [Confucius Code Agent: Scalable Agent Scaffolding for Real-World Codebases](https://huggingface.co/papers/2512.10398) (2025)\n* [Deploy-Master: Automating the Deployment of 50,000+ Agent-Ready Scientific Tools in One Day](https://huggingface.co/papers/2601.03513) (2026)\n* [R-LAM: Reproducibility-Constrained Large Action Models for Scientific Workflow Automation](https://huggingface.co/papers/2601.09749) (2026)\n* [Everything is Context: Agentic File System Abstraction for Context Engineering](https://huggingface.co/papers/2512.05470) (2025)\n* [Repository Intelligence Graph: Deterministic Architectural Map for LLM Code Assistants](https://huggingface.co/papers/2601.10112) (2026)\n* [AgentDevel: Reframing Self-Evolving LLM Agents as Release Engineering](https://huggingface.co/papers/2601.04620) (2026)\n* [NEMO: Execution-Aware Optimization Modeling via Autonomous Coding Agents](https://huggingface.co/papers/2601.21372) (2026)\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/2601.21558.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21558", "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* [AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent](https://huggingface.co/papers/2512.20745) (2025)\n* [Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User Intents](https://huggingface.co/papers/2601.20144) (2026)\n* [ToolGym: an Open-world Tool-using Environment for Scalable Agent Testing and Data Curation](https://huggingface.co/papers/2601.06328) (2026)\n* [Close the Loop: Synthesizing Infinite Tool-Use Data via Multi-Agent Role-Playing](https://huggingface.co/papers/2512.23611) (2025)\n* [AutoForge: Automated Environment Synthesis for Agentic Reinforcement Learning](https://huggingface.co/papers/2512.22857) (2025)\n* [Jenius Agent: Towards Experience-Driven Accuracy Optimization in Real-World Scenarios](https://huggingface.co/papers/2601.01857) (2026)\n* [From Failure to Mastery: Generating Hard Samples for Tool-use Agents](https://huggingface.co/papers/2601.01498) (2026)\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/2601.21666.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21666", "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* [JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluation](https://huggingface.co/papers/2512.12772) (2025)\n* [A Benchmark and Agentic Framework for Omni-Modal Reasoning and Tool Use in Long Videos](https://huggingface.co/papers/2512.16978) (2025)\n* [FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs](https://huggingface.co/papers/2601.13836) (2026)\n* [AMUSE: Audio-Visual Benchmark and Alignment Framework for Agentic Multi-Speaker Understanding](https://huggingface.co/papers/2512.16250) (2025)\n* [Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning](https://huggingface.co/papers/2601.06943) (2026)\n* [QMAVIS: Long Video-Audio Understanding using Fusion of Large Multimodal Models](https://huggingface.co/papers/2601.06573) (2026)\n* [VNU-Bench: A Benchmarking Dataset for Multi-Source Multimodal News Video Understanding](https://huggingface.co/papers/2601.03434) (2026)\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/2601.21709.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21709", "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* [Attention Needs to Focus: A Unified Perspective on Attention Allocation](https://huggingface.co/papers/2601.00919) (2026)\n* [Demystifying the Slash Pattern in Attention: The Role of RoPE](https://huggingface.co/papers/2601.08297) (2026)\n* [RePo: Language Models with Context Re-Positioning](https://huggingface.co/papers/2512.14391) (2025)\n* [On the Existence and Behaviour of Secondary Attention Sinks](https://huggingface.co/papers/2512.22213) (2025)\n* [Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs](https://huggingface.co/papers/2512.07525) (2025)\n* [S$^3$-Attention:Attention-Aligned Endogenous Retrieval for Memory-Bounded Long-Context Inference](https://huggingface.co/papers/2601.17702) (2026)\n* [Attention Projection Mixing with Exogenous Anchors](https://huggingface.co/papers/2601.08131) (2026)\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/2601.21716.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21716", "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* [MoCha:End-to-End Video Character Replacement without Structural Guidance](https://huggingface.co/papers/2601.08587) (2026)\n* [SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations](https://huggingface.co/papers/2512.05905) (2025)\n* [CoDance: An Unbind-Rebind Paradigm for Robust Multi-Subject Animation](https://huggingface.co/papers/2601.11096) (2026)\n* [STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits](https://huggingface.co/papers/2512.13247) (2025)\n* [ContextAnyone: Context-Aware Diffusion for Character-Consistent Text-to-Video Generation](https://huggingface.co/papers/2512.07328) (2025)\n* [LongVie 2: Multimodal Controllable Ultra-Long Video World Model](https://huggingface.co/papers/2512.13604) (2025)\n* [V-Warper: Appearance-Consistent Video Diffusion Personalization via Value Warping](https://huggingface.co/papers/2512.12375) (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/2601.21957.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21957", "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* [LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model for State-of-the-Art OCR](https://huggingface.co/papers/2601.14251) (2026)\n* [UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters](https://huggingface.co/papers/2512.21095) (2025)\n* [STEP3-VL-10B Technical Report](https://huggingface.co/papers/2601.09668) (2026)\n* [DOCR-Inspector: Fine-Grained and Automated Evaluation of Document Parsing with VLM](https://huggingface.co/papers/2512.10619) (2025)\n* [Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking](https://huggingface.co/papers/2601.04720) (2026)\n* [GutenOCR: A Grounded Vision-Language Front-End for Documents](https://huggingface.co/papers/2601.14490) (2026)\n* [DeepSeek-OCR 2: Visual Causal Flow](https://huggingface.co/papers/2601.20552) (2026)\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/2601.21998.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.21998", "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* [mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs](https://huggingface.co/papers/2512.15692) (2025)\n* [Vidarc: Embodied Video Diffusion Model for Closed-loop Control](https://huggingface.co/papers/2512.17661) (2025)\n* [CLAP: Contrastive Latent Action Pretraining for Learning Vision-Language-Action Models from Human Videos](https://huggingface.co/papers/2601.04061) (2026)\n* [HiF-VLA: Hindsight, Insight and Foresight through Motion Representation for Vision-Language-Action Models](https://huggingface.co/papers/2512.09928) (2025)\n* [See Once, Then Act: Vision-Language-Action Model with Task Learning from One-Shot Video Demonstrations](https://huggingface.co/papers/2512.07582) (2025)\n* [Robotic VLA Benefits from Joint Learning with Motion Image Diffusion](https://huggingface.co/papers/2512.18007) (2025)\n* [InternVLA-A1: Unifying Understanding, Generation and Action for Robotic Manipulation](https://huggingface.co/papers/2601.02456) (2026)\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/2601.22032.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22032", "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* [LADY: Linear Attention for Autonomous Driving Efficiency without Transformers](https://huggingface.co/papers/2512.15038) (2025)\n* [LatentVLA: Efficient Vision-Language Models for Autonomous Driving via Latent Action Prediction](https://huggingface.co/papers/2601.05611) (2026)\n* [DriveLaW:Unifying Planning and Video Generation in a Latent Driving World](https://huggingface.co/papers/2512.23421) (2025)\n* [Driving on Registers](https://huggingface.co/papers/2601.05083) (2026)\n* [WorldRFT: Latent World Model Planning with Reinforcement Fine-Tuning for Autonomous Driving](https://huggingface.co/papers/2512.19133) (2025)\n* [SGDrive: Scene-to-Goal Hierarchical World Cognition for Autonomous Driving](https://huggingface.co/papers/2601.05640) (2026)\n* [Generative Scenario Rollouts for End-to-End Autonomous Driving](https://huggingface.co/papers/2601.11475) (2026)\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/2601.22108.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22108", "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* [Next-Embedding Prediction Makes Strong Vision Learners](https://huggingface.co/papers/2512.16922) (2025)\n* [Revisiting Multi-Task Visual Representation Learning](https://huggingface.co/papers/2601.13886) (2026)\n* [Finetune-Informed Pretraining Boosts Downstream Performance](https://huggingface.co/papers/2601.20884) (2026)\n* [Training-Trajectory-Aware Token Selection](https://huggingface.co/papers/2601.10348) (2026)\n* [DOS: Distilling Observable Softmaps of Zipfian Prototypes for Self-Supervised Point Representation](https://huggingface.co/papers/2512.11465) (2025)\n* [Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://huggingface.co/papers/2601.04992) (2026)\n* [Positive-Unlabeled Reinforcement Learning Distillation for On-Premise Small Models](https://huggingface.co/papers/2601.20687) (2026)\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/2601.22141.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22141", "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* [The Quest for Winning Tickets in Low-Rank Adapters](https://huggingface.co/papers/2512.22495) (2025)\n* [Winning the Lottery by Preserving Network Training Dynamics with Concrete Ticket Search](https://huggingface.co/papers/2512.07142) (2025)\n* [Mixture-of-Experts with Gradient Conflict-Driven Subspace Topology Pruning for Emergent Modularity](https://huggingface.co/papers/2512.20291) (2025)\n* [Scalable Heterogeneous Graph Learning via Heterogeneous-aware Orthogonal Prototype Experts](https://huggingface.co/papers/2601.05537) (2026)\n* [Simplifying Multi-Task Architectures Through Task-Specific Normalization](https://huggingface.co/papers/2512.20420) (2025)\n* [AgenticPruner: MAC-Constrained Neural Network Compression via LLM-Driven Strategy Search](https://huggingface.co/papers/2601.12272) (2026)\n* [CosineGate: Semantic Dynamic Routing via Cosine Incompatibility in Residual Networks](https://huggingface.co/papers/2512.22206) (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/2601.22491.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22491", "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* [MagicGUI-RMS: A Multi-Agent Reward Model System for Self-Evolving GUI Agents via Automated Feedback Reflux](https://huggingface.co/papers/2601.13060) (2026)\n* [Exploring Reasoning Reward Model for Agents](https://huggingface.co/papers/2601.22154) (2026)\n* [Enhancing Agentic RL with Progressive Reward Shaping and Value-based Sampling Policy Optimization](https://huggingface.co/papers/2512.07478) (2025)\n* [Spark: Strategic Policy-Aware Exploration via Dynamic Branching for Long-Horizon Agentic Learning](https://huggingface.co/papers/2601.20209) (2026)\n* [ProRAG: Process-Supervised Reinforcement Learning for Retrieval-Augmented Generation](https://huggingface.co/papers/2601.21912) (2026)\n* [ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking](https://huggingface.co/papers/2601.06487) (2026)\n* [Training One Model to Master Cross-Level Agentic Actions via Reinforcement Learning](https://huggingface.co/papers/2512.09706) (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/2601.22628.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22628", "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* [V-Zero: Self-Improving Multimodal Reasoning with Zero Annotation](https://huggingface.co/papers/2601.10094) (2026)\n* [DARC: Decoupled Asymmetric Reasoning Curriculum for LLM Evolution](https://huggingface.co/papers/2601.13761) (2026)\n* [Dr. Zero: Self-Evolving Search Agents without Training Data](https://huggingface.co/papers/2601.07055) (2026)\n* [Knowing the Answer Isn't Enough: Fixing Reasoning Path Failures in LVLMs](https://huggingface.co/papers/2512.06258) (2025)\n* [Structured Reasoning for Large Language Models](https://huggingface.co/papers/2601.07180) (2026)\n* [Dual-Phase LLM Reasoning: Self-Evolved Mathematical Frameworks](https://huggingface.co/papers/2601.05616) (2026)\n* [From Atoms to Chains: Divergence-Guided Reasoning Curriculum for Unlabeled LLM Domain Adaptation](https://huggingface.co/papers/2601.19588) (2026)\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/2601.22642.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22642", "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* [LogicReward: Incentivizing LLM Reasoning via Step-Wise Logical Supervision](https://huggingface.co/papers/2512.18196) (2025)\n* [Structured Reasoning for Large Language Models](https://huggingface.co/papers/2601.07180) (2026)\n* [Milestones over Outcome: Unlocking Geometric Reasoning with Sub-Goal Verifiable Reward](https://huggingface.co/papers/2601.05073) (2026)\n* [P2S: Probabilistic Process Supervision for General-Domain Reasoning Question Answering](https://huggingface.co/papers/2601.20649) (2026)\n* [VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning](https://huggingface.co/papers/2601.20055) (2026)\n* [LRAS: Advanced Legal Reasoning with Agentic Search](https://huggingface.co/papers/2601.07296) (2026)\n* [ConMax: Confidence-Maximizing Compression for Efficient Chain-of-Thought Reasoning](https://huggingface.co/papers/2601.04973) (2026)\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/2601.22664.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22664", "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* [RM-Distiller: Exploiting Generative LLM for Reward Model Distillation](https://huggingface.co/papers/2601.14032) (2026)\n* [Factored Causal Representation Learning for Robust Reward Modeling in RLHF](https://huggingface.co/papers/2601.21350) (2026)\n* [When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models](https://huggingface.co/papers/2512.06343) (2025)\n* [IRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models](https://huggingface.co/papers/2601.00677) (2026)\n* [Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance](https://huggingface.co/papers/2512.23461) (2025)\n* [Reward Modeling from Natural Language Human Feedback](https://huggingface.co/papers/2601.07349) (2026)\n* [Rewarding Creativity: A Human-Aligned Generative Reward Model for Reinforcement Learning in Storytelling](https://huggingface.co/papers/2601.07149) (2026)\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/2601.22666.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22666", "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* [MulCLIP: A Multi-level Alignment Framework for Enhancing Fine-grained Long-context CLIP](https://huggingface.co/papers/2512.07128) (2025)\n* [\u03b2-CLIP: Text-Conditioned Contrastive Learning for Multi-Granular Vision-Language Alignment](https://huggingface.co/papers/2512.12678) (2025)\n* [ABE-CLIP: Training-Free Attribute Binding Enhancement for Compositional Image-Text Matching](https://huggingface.co/papers/2512.17178) (2025)\n* [ITSELF: Attention Guided Fine-Grained Alignment for Vision-Language Retrieval](https://huggingface.co/papers/2601.01024) (2026)\n* [CLIP-Joint-Detect: End-to-End Joint Training of Object Detectors with Contrastive Vision-Language Supervision](https://huggingface.co/papers/2512.22969) (2025)\n* [Revisiting Multi-Task Visual Representation Learning](https://huggingface.co/papers/2601.13886) (2026)\n* [Prompt-Based Continual Compositional Zero-Shot Learning](https://huggingface.co/papers/2512.09172) (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/2601.22680.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22680", "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* [DuetSVG: Unified Multimodal SVG Generation with Internal Visual Guidance](https://huggingface.co/papers/2512.10894) (2025)\n* [Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization](https://huggingface.co/papers/2512.10955) (2025)\n* [CRAFT: Continuous Reasoning and Agentic Feedback Tuning for Multimodal Text-to-Image Generation](https://huggingface.co/papers/2512.20362) (2025)\n* [VisionDirector: Vision-Language Guided Closed-Loop Refinement for Generative Image Synthesis](https://huggingface.co/papers/2512.19243) (2025)\n* [Bring My Cup! Personalizing Vision-Language-Action Models with Visual Attentive Prompting](https://huggingface.co/papers/2512.20014) (2025)\n* [AgentComp: From Agentic Reasoning to Compositional Mastery in Text-to-Image Models](https://huggingface.co/papers/2512.09081) (2025)\n* [REVEALER: Reinforcement-Guided Visual Reasoning for Element-Level Text-Image Alignment Evaluation](https://huggingface.co/papers/2512.23169) (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/2601.22813.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22813", "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* [ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs](https://huggingface.co/papers/2601.07475) (2026)\n* [ECO: Quantized Training without Full-Precision Master Weights](https://huggingface.co/papers/2601.22101) (2026)\n* [SQ-format: A Unified Sparse-Quantized Hardware-friendly Data Format for LLMs](https://huggingface.co/papers/2512.05409) (2025)\n* [LLMQ: Efficient Lower-Precision Pretraining for Consumer GPUs](https://huggingface.co/papers/2512.15306) (2025)\n* [Benchmarking Post-Training Quantization of Large Language Models under Microscaling Floating Point Formats](https://huggingface.co/papers/2601.09555) (2026)\n* [SASQ: Static Activation Scaling for Quantization-Aware Training in Large Language Models](https://huggingface.co/papers/2512.14481) (2025)\n* [FPGA Co-Design for Efficient N:M Sparse and Quantized Model Inference](https://huggingface.co/papers/2512.24713) (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/2601.22837.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22837", "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* [Improving Flexible Image Tokenizers for Autoregressive Image Generation](https://huggingface.co/papers/2601.01535) (2026)\n* [DPAR: Dynamic Patchification for Efficient Autoregressive Visual Generation](https://huggingface.co/papers/2512.21867) (2025)\n* [Soft Tail-dropping for Adaptive Visual Tokenization](https://huggingface.co/papers/2601.14246) (2026)\n* [ResTok: Learning Hierarchical Residuals in 1D Visual Tokenizers for Autoregressive Image Generation](https://huggingface.co/papers/2601.03955) (2026)\n* [SFTok: Bridging the Performance Gap in Discrete Tokenizers](https://huggingface.co/papers/2512.16910) (2025)\n* [NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation](https://huggingface.co/papers/2601.02204) (2026)\n* [One Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation](https://huggingface.co/papers/2512.07829) (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/2601.22904.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22904", "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* [One Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation](https://huggingface.co/papers/2512.07829) (2025)\n* [Both Semantics and Reconstruction Matter: Making Representation Encoders Ready for Text-to-Image Generation and Editing](https://huggingface.co/papers/2512.17909) (2025)\n* [VAE-REPA: Variational Autoencoder Representation Alignment for Efficient Diffusion Training](https://huggingface.co/papers/2601.17830) (2026)\n* [RecTok: Reconstruction Distillation along Rectified Flow](https://huggingface.co/papers/2512.13421) (2025)\n* [RePack: Representation Packing of Vision Foundation Model Features Enhances Diffusion Transformer](https://huggingface.co/papers/2512.12083) (2025)\n* [REGLUE Your Latents with Global and Local Semantics for Entangled Diffusion](https://huggingface.co/papers/2512.16636) (2025)\n* [Distribution Matching Variational AutoEncoder](https://huggingface.co/papers/2512.07778) (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/2601.22975.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.22975", "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* [DARL: Encouraging Diverse Answers for General Reasoning without Verifiers](https://huggingface.co/papers/2601.14700) (2026)\n* [ReasonTabQA: A Comprehensive Benchmark for Table Question Answering from Real World Industrial Scenarios](https://huggingface.co/papers/2601.07280) (2026)\n* [WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://huggingface.co/papers/2601.05567) (2026)\n* [P2S: Probabilistic Process Supervision for General-Domain Reasoning Question Answering](https://huggingface.co/papers/2601.20649) (2026)\n* [Aletheia: What Makes RLVR For Code Verifiers Tick?](https://huggingface.co/papers/2601.12186) (2026)\n* [JustRL: Scaling a 1.5B LLM with a Simple RL Recipe](https://huggingface.co/papers/2512.16649) (2025)\n* [DARC: Decoupled Asymmetric Reasoning Curriculum for LLM Evolution](https://huggingface.co/papers/2601.13761) (2026)\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/2601.23134.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.23134", "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* [Attention-Informed Surrogates for Navigating Power-Performance Trade-offs in HPC](https://huggingface.co/papers/2601.15399) (2026)\n* [HiDVFS: A Hierarchical Multi-Agent DVFS Scheduler for OpenMP DAG Workloads](https://huggingface.co/papers/2601.06425) (2026)\n* [EARL: Energy-Aware Optimization of Liquid State Machines for Pervasive AI](https://huggingface.co/papers/2601.05205) (2026)\n* [Kareus: Joint Reduction of Dynamic and Static Energy in Large Model Training](https://huggingface.co/papers/2601.17654) (2026)\n* [ZeroDVFS: Zero-Shot LLM-Guided Core and Frequency Allocation for Embedded Platforms](https://huggingface.co/papers/2601.08166) (2026)\n* [GraphPerf-RT: A Graph-Driven Performance Model for Hardware-Aware Scheduling of OpenMP Codes](https://huggingface.co/papers/2512.12091) (2025)\n* [EWSJF: An Adaptive Scheduler with Hybrid Partitioning for Mixed-Workload LLM Inference](https://huggingface.co/papers/2601.21758) (2026)\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/2601.23143.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.23143", "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* [STAR-S: Improving Safety Alignment through Self-Taught Reasoning on Safety Rules](https://huggingface.co/papers/2601.03537) (2026)\n* [ConMax: Confidence-Maximizing Compression for Efficient Chain-of-Thought Reasoning](https://huggingface.co/papers/2601.04973) (2026)\n* [Think-Reflect-Revise: A Policy-Guided Reflective Framework for Safety Alignment in Large Vision Language Models](https://huggingface.co/papers/2512.07141) (2025)\n* [Teaching Large Reasoning Models Effective Reflection](https://huggingface.co/papers/2601.12720) (2026)\n* [Reasoning over Precedents Alongside Statutes: Case-Augmented Deliberative Alignment for LLM Safety](https://huggingface.co/papers/2601.08000) (2026)\n* [How Does Prefix Matter in Reasoning Model Tuning?](https://huggingface.co/papers/2601.01624) (2026)\n* [TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety Alignment](https://huggingface.co/papers/2601.18292) (2026)\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/2601.23161.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.23161", "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* [dLLM-ASR: A Faster Diffusion LLM-based Framework for Speech Recognition](https://huggingface.co/papers/2601.17902) (2026)\n* [Fun-Audio-Chat Technical Report](https://huggingface.co/papers/2512.20156) (2025)\n* [FastSLM: Hierarchical Frame Q-Former for Effective Speech Modality Adaptation](https://huggingface.co/papers/2601.06199) (2026)\n* [MiMo-Audio: Audio Language Models are Few-Shot Learners](https://huggingface.co/papers/2512.23808) (2025)\n* [AzeroS: Extending LLM to Speech with Self-Generated Instruction-Free Tuning](https://huggingface.co/papers/2601.06086) (2025)\n* [SDAR-VL: Stable and Efficient Block-wise Diffusion for Vision-Language Understanding](https://huggingface.co/papers/2512.14068) (2025)\n* [AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation](https://huggingface.co/papers/2601.17761) (2026)\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/2601.23184.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.23184", "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* [Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning](https://huggingface.co/papers/2601.14750) (2026)\n* [Latent Chain-of-Thought as Planning: Decoupling Reasoning from Verbalization](https://huggingface.co/papers/2601.21358) (2026)\n* [Forest Before Trees: Latent Superposition for Efficient Visual Reasoning](https://huggingface.co/papers/2601.06803) (2026)\n* [Chain-of-Thought Compression Should Not Be Blind: V-Skip for Efficient Multimodal Reasoning via Dual-Path Anchoring](https://huggingface.co/papers/2601.13879) (2026)\n* [Interleaved Latent Visual Reasoning with Selective Perceptual Modeling](https://huggingface.co/papers/2512.05665) (2025)\n* [LaViT: Aligning Latent Visual Thoughts for Multi-modal Reasoning](https://huggingface.co/papers/2601.10129) (2026)\n* [Sketch-in-Latents: Eliciting Unified Reasoning in MLLMs](https://huggingface.co/papers/2512.16584) (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/2601.23188.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2601.23188", "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* [AI Meets Brain: Memory Systems from Cognitive Neuroscience to Autonomous Agents](https://huggingface.co/papers/2512.23343) (2025)\n* [BMAM: Brain-inspired Multi-Agent Memory Framework](https://huggingface.co/papers/2601.20465) (2026)\n* [Learning Hierarchical Procedural Memory for LLM Agents through Bayesian Selection and Contrastive Refinement](https://huggingface.co/papers/2512.18950) (2025)\n* [Agentic Uncertainty Quantification](https://huggingface.co/papers/2601.15703) (2026)\n* [HiMem: Hierarchical Long-Term Memory for LLM Long-Horizon Agents](https://huggingface.co/papers/2601.06377) (2026)\n* [Memory Matters More: Event-Centric Memory as a Logic Map for Agent Searching and Reasoning](https://huggingface.co/papers/2601.04726) (2026)\n* [Learning How to Remember: A Meta-Cognitive Management Method for Structured and Transferable Agent Memory](https://huggingface.co/papers/2601.07470) (2026)\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/2601.23228.json

@@ -0,0 +1 @@
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data/2601.23265.json

@@ -0,0 +1 @@
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