{"total":106,"rows":[{"id":"2503.09516","title":"Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning","created":"2025-03-12","cited_by_count":1444,"area":"lr"},{"id":"2412.21187","title":"Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs","created":"2024-12-30","cited_by_count":570,"area":"lr"},{"id":"2408.15240","title":"Generative Verifiers: Reward Modeling as Next-Token Prediction","created":"2024-08-27","cited_by_count":480,"area":"lr"},{"id":"2505.05410","title":"Reasoning Models Don't Always Say What They Think","created":"2025-05-08","cited_by_count":415,"area":"lr"},{"id":"2406.03816","title":"ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search","created":"2024-06-06","cited_by_count":344,"area":"lr"},{"id":"2411.10442","title":"Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization","created":"2024-11-15","cited_by_count":239,"area":"lr"},{"id":"2503.10291","title":"VisualPRM: An Effective Process Reward Model for Multimodal Reasoning","created":"2025-03-13","cited_by_count":139,"area":"lr"},{"id":"2410.16198","title":"Improve Vision Language Model Chain-of-thought Reasoning","created":"2024-10-21","cited_by_count":136,"area":"lr"},{"id":"2501.13926","title":"Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step","created":"2025-01-23","cited_by_count":131,"area":"lr"},{"id":"2406.14532","title":"RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold","created":"2024-06-20","cited_by_count":99,"area":"lr"},{"id":"2406.09136","title":"Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs","created":"2024-06-13","cited_by_count":96,"area":"lr"},{"id":"2501.05707","title":"Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains","created":"2025-01-10","cited_by_count":95,"area":"lr"},{"id":"2502.13124","title":"NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions","created":"2025-02-18","cited_by_count":84,"area":"lr"},{"id":"2411.19943","title":"Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM's Reasoning Capability","created":"2024-11-29","cited_by_count":83,"area":"lr"},{"id":"2501.18099","title":"Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge","created":"2025-01-30","cited_by_count":78,"area":"lr"},{"id":"2411.16646","title":"Self-Generated Critiques Boost Reward Modeling for Language Models","created":"2024-11-25","cited_by_count":71,"area":"lr"},{"id":"2502.19613","title":"Self-rewarding correction for mathematical reasoning","created":"2025-02-26","cited_by_count":70,"area":"lr"},{"id":"2505.21444","title":"Can Large Reasoning Models Self-Train?","created":"2025-05-27","cited_by_count":68,"area":"lr"},{"id":"2409.02392","title":"Building Math Agents with Multi-Turn Iterative Preference Learning","created":"2024-09-04","cited_by_count":66,"area":"lr"},{"id":"2408.16737","title":"Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling","created":"2024-08-29","cited_by_count":61,"area":"lr"},{"id":"2412.16145","title":"Offline Reinforcement Learning for LLM Multi-Step Reasoning","created":"2024-12-20","cited_by_count":54,"area":"lr"},{"id":"2506.08446","title":"A Survey on Large Language Models for Mathematical Reasoning","created":"2025-06-10","cited_by_count":52,"area":"lr"},{"id":"2505.20347","title":"SeRL: Self-Play Reinforcement Learning for Large Language Models with Limited Data","created":"2025-05-25","cited_by_count":51,"area":"lr"},{"id":"2411.04109","title":"Self-Consistency Preference Optimization","created":"2024-11-06","cited_by_count":50,"area":"lr"},{"id":"2506.08745","title":"Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning","created":"2025-06-10","cited_by_count":46,"area":"lr"},{"id":"2410.10630","title":"Thinking LLMs: General Instruction Following with Thought Generation","created":"2024-10-14","cited_by_count":45,"area":"lr"},{"id":"2502.04780","title":"SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning","created":"2025-02-07","cited_by_count":44,"area":"lr"},{"id":"2412.11006","title":"Entropy-Regularized Process Reward Model","created":"2024-12-15","cited_by_count":38,"area":"lr"},{"id":"2412.17451","title":"Diving into Self-Evolving Training for Multimodal Reasoning","created":"2024-12-23","cited_by_count":32,"area":"lr"},{"id":"2506.21656","title":"Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs","created":"2025-06-26","cited_by_count":32,"area":"lr"},{"id":"2410.08105","title":"What Makes Large Language Models Reason in (Multi-Turn) Code Generation?","created":"2024-10-10","cited_by_count":29,"area":"lr"},{"id":"2410.15595","title":"A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications","created":"2024-10-21","cited_by_count":27,"area":"lr"},{"id":"2506.08379","title":"Reinforce LLM Reasoning through Multi-Agent Reflection","created":"2025-06-10","cited_by_count":27,"area":"lr"},{"id":"2512.16912","title":"Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward","created":"2025-12-18","cited_by_count":27,"area":"lr"},{"id":"2412.17256","title":"B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners","created":"2024-12-23","cited_by_count":26,"area":"lr"},{"id":"2502.00963","title":"PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs","created":"2025-02-03","cited_by_count":23,"area":"lr"},{"id":"2506.04405","title":"MedAgentGym: A Scalable Agentic Training Environment for Code-Centric Reasoning in Biomedical Data Science","created":"2025-06-04","cited_by_count":23,"area":"lr"},{"id":"2507.00971","title":"Reasoning as an Adaptive Defense for Safety","created":"2025-07-01","cited_by_count":23,"area":"lr"},{"id":"2502.11250","title":"Uncertainty-Aware Step-wise Verification with Generative Reward Models","created":"2025-02-16","cited_by_count":22,"area":"lr"},{"id":"2504.04915","title":"Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration","created":"2025-04-07","cited_by_count":20,"area":"lr"},{"id":"2505.11595","title":"Stepwise Guided Policy Optimization: Coloring your Incorrect Reasoning in GRPO","created":"2025-05-16","cited_by_count":19,"area":"lr"},{"id":"2504.15362","title":"LongPerceptualThoughts: Distilling System-2 Reasoning for System-1 Perception","created":"2025-04-21","cited_by_count":16,"area":"lr"},{"id":"2506.09532","title":"Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models","created":"2025-06-11","cited_by_count":16,"area":"lr"},{"id":"2406.12050","title":"Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning","created":"2024-06-17","cited_by_count":15,"area":"lr"},{"id":"2502.20548","title":"$Q\\sharp$: Provably Optimal Distributional RL for LLM Post-Training","created":"2025-02-27","cited_by_count":15,"area":"lr"},{"id":"2504.13828","title":"Generative AI Act II: Test Time Scaling Drives Cognition Engineering","created":"2025-04-18","cited_by_count":15,"area":"lr"},{"id":"2506.09820","title":"CoRT: Code-integrated Reasoning within Thinking","created":"2025-06-11","cited_by_count":15,"area":"lr"},{"id":"2502.08922","title":"Self-Consistency of the Internal Reward Models Improves Self-Rewarding Language Models","created":"2025-02-13","cited_by_count":13,"area":"lr"},{"id":"2507.02834","title":"ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning","created":"2025-07-03","cited_by_count":13,"area":"lr"},{"id":"2410.22304","title":"Flow-DPO: Improving LLM Mathematical Reasoning through Online Multi-Agent Learning","created":"2024-10-29","cited_by_count":12,"area":"lr"},{"id":"2605.05040","title":"Preference-Based Self-Distillation: Beyond KL Matching via Reward Regularization","created":"2026-05-06","cited_by_count":12,"area":"lr"},{"id":"2509.24393","title":"Towards Safe Reasoning in Large Reasoning Models via Corrective Intervention","created":"2025-09-29","cited_by_count":11,"area":"lr"},{"id":"2512.22255","title":"Shape of Thought: When Distribution Matters More than Correctness in Reasoning Tasks","created":"2025-12-24","cited_by_count":11,"area":"lr"},{"id":"2501.18858","title":"BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning","created":"2025-01-31","cited_by_count":10,"area":"lr"},{"id":"2503.23219","title":"Aurelia: Test-time Reasoning Distillation in Audio-Visual LLMs","created":"2025-03-29","cited_by_count":9,"area":"lr"},{"id":"2504.05294","title":"Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations","created":"2025-04-07","cited_by_count":9,"area":"lr"},{"id":"2505.16176","title":"Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning","created":"2025-05-22","cited_by_count":8,"area":"lr"},{"id":"2506.01475","title":"PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimization","created":"2025-06-02","cited_by_count":8,"area":"lr"},{"id":"2510.01925","title":"Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey","created":"2025-10-02","cited_by_count":8,"area":"lr"},{"id":"2511.05385","title":"TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework","created":"2025-11-07","cited_by_count":7,"area":"lr"},{"id":"2511.21667","title":"Escaping the Verifier: Learning to Reason via Demonstrations","created":"2025-11-26","cited_by_count":7,"area":"lr"},{"id":"2406.16061","title":"PORT: Preference Optimization on Reasoning Traces","created":"2024-06-23","cited_by_count":6,"area":"lr"},{"id":"2410.10858","title":"Reasoning Paths Optimization: Learning to Reason and Explore From Diverse Paths","created":"2024-10-07","cited_by_count":6,"area":"lr"},{"id":"2411.06387","title":"Self-Training Meets Consistency: Improving LLMs' Reasoning with Consistency-Driven Rationale Evaluation","created":"2024-11-10","cited_by_count":6,"area":"lr"},{"id":"2505.16322","title":"AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners","created":"2025-05-22","cited_by_count":6,"area":"lr"},{"id":"2606.29150","title":"Flow Reasoning Models: Turning Flows Into Efficient Recurrent Reasoners","created":"2026-06-28","cited_by_count":6,"area":"lr"},{"id":"2406.14629","title":"Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study","created":"2024-06-20","cited_by_count":5,"area":"lr"},{"id":"2503.23913","title":"Entropy-Based Adaptive Weighting for Self-Training","created":"2025-03-31","cited_by_count":5,"area":"lr"},{"id":"2504.20157","title":"Toward Evaluative Thinking: Meta Policy Optimization with Evolving Reward Models","created":"2025-04-28","cited_by_count":5,"area":"lr"},{"id":"2410.09528","title":"Boosting Deductive Reasoning with Step Signals In RLHF","created":"2024-10-12","cited_by_count":4,"area":"lr"},{"id":"2504.11364","title":"Offline Learning and Forgetting for Reasoning with Large Language Models","created":"2025-04-15","cited_by_count":4,"area":"lr"},{"id":"2504.18080","title":"Stabilizing Reasoning in Medical LLMs with Continued Pretraining and Reasoning Preference Optimization","created":"2025-04-25","cited_by_count":4,"area":"lr"},{"id":"2606.21090","title":"Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training","created":"2026-06-17","cited_by_count":4,"area":"lr"},{"id":"2411.19039","title":"Mars-PO: Multi-Agent Reasoning System Preference Optimization","created":"2024-11-28","cited_by_count":3,"area":"lr"},{"id":"2509.25176","title":"SIRI: Scaling Iterative Reinforcement Learning with Interleaved Compression","created":"2025-09-29","cited_by_count":3,"area":"lr"},{"id":"2601.13806","title":"Knowledge Graph-Assisted LLM Post-Training for Enhanced Legal Reasoning","created":"2026-01-20","cited_by_count":3,"area":"lr"},{"id":"2603.01683","title":"Surgical Post-Training: Proximal On-Policy Distillation for Reasoning with Knowledge Retention","created":"2026-03-02","cited_by_count":3,"area":"lr"},{"id":"2604.00261","title":"Can Large Language Models Self-Correct in Medical Question Answering? An Exploratory Study","created":"2026-03-31","cited_by_count":3,"area":"lr"},{"id":"2605.01248","title":"$S^3$-R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data","created":"2026-05-02","cited_by_count":3,"area":"lr"},{"id":"2605.10937","title":"Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping","created":"2026-05-11","cited_by_count":3,"area":"lr"},{"id":"2412.04291","title":"Evolutionary Pre-Prompt Optimization for Mathematical Reasoning","created":"2024-12-05","cited_by_count":2,"area":"lr"},{"id":"2412.08024","title":"TinyThinker: Distilling Reasoning through Coarse-to-Fine Knowledge Internalization with Self-Reflection","created":"2024-12-11","cited_by_count":2,"area":"lr"},{"id":"2412.08393","title":"Learning to Reason via Self-Iterative Process Feedback for Small Language Models","created":"2024-12-11","cited_by_count":2,"area":"lr"},{"id":"2503.07903","title":"Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks?","created":"2025-03-10","cited_by_count":2,"area":"lr"},{"id":"2505.23540","title":"Probability-Consistent Preference Optimization for Enhanced LLM Reasoning","created":"2025-05-29","cited_by_count":2,"area":"lr"},{"id":"2507.02984","title":"From Answers to Rationales: Self-Aligning Multimodal Reasoning with Answer-Oriented Chain-of-Thought","created":"2025-07-01","cited_by_count":2,"area":"lr"},{"id":"2605.17003","title":"Learning-Zone Energy: Online Data Selection for Efficient RL Post-Training","created":"2026-05-16","cited_by_count":2,"area":"lr"},{"id":"2607.03426","title":"Amortising Bayesian Experimental Design for Sequential Information Gathering in LLMs","created":"2026-07-03","cited_by_count":2,"area":"lr"},{"id":"2608.12957","title":"I-SDPO: Instance-Level Adaptive Self-Distillation Policy Optimization","created":"2026-08-13","cited_by_count":2,"area":"lr"},{"id":"2410.08037","title":"Composite Learning Units: Generalized Learning Beyond Parameter Updates to Transform LLMs into Adaptive Reasoners","created":"2024-10-09","cited_by_count":1,"area":"lr"},{"id":"2412.10566","title":"EVLM: Self-Reflective Multimodal Reasoning for Cross-Dimensional Visual Editing","created":"2024-12-13","cited_by_count":1,"area":"lr"},{"id":"2506.00189","title":"Control-R: Towards controllable test-time scaling","created":"2025-05-30","cited_by_count":1,"area":"lr"},{"id":"2509.19893","title":"Future Policy Approximation for Offline Reinforcement Learning in LLM Reasoning","created":"2025-09-24","cited_by_count":1,"area":"lr"},{"id":"2601.14716","title":"PCL-Reasoner-V1.5: Advancing Math Reasoning with Offline Reinforcement Learning","created":"2026-01-21","cited_by_count":1,"area":"lr"},{"id":"2602.19519","title":"Ada-RS: Adaptive Rejection Sampling for Selective Thinking","created":"2026-02-23","cited_by_count":1,"area":"lr"},{"id":"2603.19310","title":"MemReward: Graph-Based Experience Memory for LLM Reward Prediction with Limited Labels","created":"2026-03-13","cited_by_count":1,"area":"lr"},{"id":"2605.04078","title":"Validity-Calibrated Reasoning Distillation","created":"2026-04-14","cited_by_count":1,"area":"lr"},{"id":"2606.22158","title":"Improving Reasoning in Vision-Language Models via Perception Verified Self-Training","created":"2026-06-20","cited_by_count":1,"area":"lr"},{"id":"2608.09271","title":"SoftmaxGRPO: Learning to Reason using Softmax Advantage Group Estimation","created":"2026-08-10","cited_by_count":1,"area":"lr"},{"id":"2509.24207","title":"Humanline: Online Alignment as Perceptual Loss","created":"2025-09-29","cited_by_count":0,"area":"lr"}],"next_cursor":"100"}