{"total":30,"rows":[{"id":"2409.12917","title":"Training Language Models to Self-Correct via Reinforcement Learning","created":"2024-09-19","cited_by_count":426,"area":"lr"},{"id":"2503.09567","title":"Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models","created":"2025-03-12","cited_by_count":384,"area":"lr"},{"id":"2412.06559","title":"ProcessBench: Identifying Process Errors in Mathematical Reasoning","created":"2024-12-09","cited_by_count":292,"area":"lr"},{"id":"2504.16891","title":"AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset","created":"2025-04-23","cited_by_count":174,"area":"lr"},{"id":"2504.11343","title":"A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce","created":"2025-04-15","cited_by_count":145,"area":"lr"},{"id":"2503.15478","title":"SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks","created":"2025-03-19","cited_by_count":118,"area":"lr"},{"id":"2505.01441","title":"Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning","created":"2025-04-28","cited_by_count":110,"area":"lr"},{"id":"2502.18439","title":"MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning","created":"2025-02-25","cited_by_count":86,"area":"lr"},{"id":"2502.19613","title":"Self-rewarding correction for mathematical reasoning","created":"2025-02-26","cited_by_count":70,"area":"lr"},{"id":"2412.11936","title":"A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges","created":"2024-12-16","cited_by_count":55,"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":"2412.11006","title":"Entropy-Regularized Process Reward Model","created":"2024-12-15","cited_by_count":38,"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":"2410.15595","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":"2503.18132","title":"MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection","created":"2025-03-23","cited_by_count":24,"area":"lr"},{"id":"2502.11520","title":"AURORA:Automated Training Framework of Universal Process Reward Models via Ensemble Prompting and Reverse Verification","created":"2025-02-17","cited_by_count":23,"area":"lr"},{"id":"2410.09302","title":"Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization","created":"2024-10-11","cited_by_count":22,"area":"lr"},{"id":"2501.10799","title":"Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback","created":"2025-01-18","cited_by_count":22,"area":"lr"},{"id":"2506.07235","title":"Multi-Step Visual Reasoning with Visual Tokens Scaling and Verification","created":"2025-06-08","cited_by_count":21,"area":"lr"},{"id":"2510.23038","title":"Incentivizing Agentic Reasoning in LLM Judges via Tool-Integrated Reinforcement Learning","created":"2025-10-27","cited_by_count":17,"area":"lr"},{"id":"2410.07627","title":"Automatic Curriculum Expert Iteration for Reliable LLM Reasoning","created":"2024-10-10","cited_by_count":16,"area":"lr"},{"id":"2507.14295","title":"A Simple \"Try Again\" Can Elicit Multi-Turn LLM Reasoning","created":"2025-07-18","cited_by_count":11,"area":"lr"},{"id":"2506.03541","title":"Debate, Reflect, and Distill: Multi-Agent Feedback with Tree-Structured Preference Optimization for Efficient Language Model Enhancement","created":"2025-06-04","cited_by_count":10,"area":"lr"},{"id":"2603.04783","title":"Breaking Contextual Inertia: Reinforcement Learning with Single-Turn Anchors for Stable Multi-Turn Interaction","created":"2026-03-05","cited_by_count":9,"area":"lr"},{"id":"2502.05867","title":"Self-Training Large Language Models for Tool-Use Without Demonstrations","created":"2025-02-09","cited_by_count":7,"area":"lr"},{"id":"2509.12434","title":"Building Coding Agents via Entropy-Enhanced Multi-Turn Preference Optimization","created":"2025-09-15","cited_by_count":6,"area":"lr"},{"id":"2412.17397","title":"Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning","created":"2024-12-23","cited_by_count":4,"area":"lr"},{"id":"2511.21638","title":"Iterative GRPO: Batch-Online Multi-Turn RL via Single-Turn RLHF","created":"2025-11-26","cited_by_count":3,"area":"lr"},{"id":"2606.18910","title":"REVES: REvision and VErification--Augmented Training for Test-Time Scaling","created":"2026-06-17","cited_by_count":0,"area":"lr"}],"next_cursor":null}