{"total":65,"rows":[{"id":"2501.07301","title":"The Lessons of Developing Process Reward Models in Mathematical Reasoning","created":"2025-01-13","cited_by_count":415,"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":"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":"2503.10460","title":"Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond","created":"2025-03-13","cited_by_count":175,"area":"lr"},{"id":"2502.21321","title":"LLM Post-Training: A Deep Dive into Reasoning Large Language Models","created":"2025-02-28","cited_by_count":135,"area":"lr"},{"id":"2504.05812","title":"Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization","created":"2025-04-08","cited_by_count":128,"area":"lr"},{"id":"2406.04151","title":"AgentGym: Evolving Large Language Model-based Agents across Diverse Environments","created":"2024-06-06","cited_by_count":120,"area":"agents"},{"id":"2505.14970","title":"Self-Evolving Curriculum for LLM Reasoning","created":"2025-05-20","cited_by_count":112,"area":"lr"},{"id":"2511.08325","title":"AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progress","created":"2025-11-11","cited_by_count":77,"area":"lr"},{"id":"2509.08755","title":"AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning","created":"2025-09-10","cited_by_count":72,"area":"agents"},{"id":"2505.16984","title":"UFT: Unifying Supervised and Reinforcement Fine-Tuning","created":"2025-05-22","cited_by_count":59,"area":"lr"},{"id":"2411.18478","title":"Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS","created":"2024-11-27","cited_by_count":54,"area":"lr"},{"id":"2509.18970","title":"LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions","created":"2025-09-23","cited_by_count":50,"area":"agents"},{"id":"2510.18927","title":"BAPO: Stabilizing Off-Policy Reinforcement Learning for LLMs via Balanced Policy Optimization with Adaptive Clipping","created":"2025-10-21","cited_by_count":47,"area":null},{"id":"2504.09710","title":"DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-training","created":"2025-04-13","cited_by_count":46,"area":"lr"},{"id":"2507.13266","title":"QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation","created":"2025-07-17","cited_by_count":44,"area":"lr"},{"id":"2509.19803","title":"VCRL: Variance-based Curriculum Reinforcement Learning for Large Language Models","created":"2025-09-24","cited_by_count":36,"area":"lr"},{"id":"2407.00782","title":"Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning","created":"2024-06-30","cited_by_count":35,"area":"lr"},{"id":"2410.18798","title":"Distill Visual Chart Reasoning Ability from LLMs to MLLMs","created":"2024-10-24","cited_by_count":31,"area":"lr"},{"id":"2409.09345","title":"Enhancing Decision-Making for LLM Agents via Step-Level Q-Value Models","created":"2024-09-14","cited_by_count":28,"area":"agents"},{"id":"2602.02488","title":"RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System","created":"2026-02-02","cited_by_count":24,"area":"agents"},{"id":"2408.06318","title":"Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example","created":"2024-08-12","cited_by_count":22,"area":"agents"},{"id":"2503.17439","title":"LEMMA: Learning from Errors for MatheMatical Advancement in LLMs","created":"2025-03-21","cited_by_count":21,"area":"lr"},{"id":"2403.02178","title":"Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models","created":"2024-03-04","cited_by_count":20,"area":"lr"},{"id":"2506.18110","title":"RL for Reasoning by Adaptively Revealing Rationales","created":"2025-06-22","cited_by_count":16,"area":null},{"id":"2405.06680","title":"Exploring the Compositional Deficiency of Large Language Models in Mathematical Reasoning","created":"2024-05-05","cited_by_count":15,"area":"lr"},{"id":"2505.19653","title":"Token-Importance Guided Direct Preference Optimization","created":"2025-05-26","cited_by_count":14,"area":"alignment"},{"id":"2411.00750","title":"Mitigating Tail Narrowing in LLM Self-Improvement via Socratic-Guided Sampling","created":"2024-11-01","cited_by_count":13,"area":"synth"},{"id":"2409.17472","title":"Autoregressive Multi-trait Essay Scoring via Reinforcement Learning with Scoring-aware Multiple Rewards","created":"2024-09-26","cited_by_count":12,"area":"alignment"},{"id":"2507.14449","title":"IRGPT: Understanding Real-world Infrared Image with Bi-cross-modal Curriculum on Large-scale Benchmark","created":"2025-07-19","cited_by_count":12,"area":"mllm"},{"id":"2506.03570","title":"FreePRM: Training Process Reward Models Without Ground Truth Process Labels","created":"2025-06-04","cited_by_count":11,"area":"lr"},{"id":"2510.19099","title":"What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning","created":"2025-10-21","cited_by_count":11,"area":"lr"},{"id":"2606.00564","title":"Decomposed On-Policy Distillation for Vision-Language Reasoning: Steering Gradients for Visual Grounding","created":"2026-05-30","cited_by_count":10,"area":"lr"},{"id":"2507.15865","title":"From Reasoning to Super-Intelligence: A Search-Theoretic Perspective","created":"2025-07-13","cited_by_count":9,"area":"lr"},{"id":"2509.25758","title":"Thinking Sparks!: Emergent Attention Heads in Reasoning Models During Post Training","created":"2025-09-30","cited_by_count":8,"area":"lr"},{"id":"2508.07809","title":"EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning","created":"2025-08-11","cited_by_count":7,"area":"lr"},{"id":"2602.21992","title":"PanoEnv: Exploring 3D Spatial Intelligence in Panoramic Environments with Reinforcement Learning","created":"2026-02-25","cited_by_count":7,"area":null},{"id":"2512.16917","title":"Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning","created":"2025-12-18","cited_by_count":6,"area":"lr"},{"id":"2503.01490","title":"Improving Retrospective Language Agents via Joint Policy Gradient Optimization","created":"2025-03-03","cited_by_count":4,"area":"lr"},{"id":"2602.14868","title":"Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning","created":"2026-02-16","cited_by_count":4,"area":"lr"},{"id":"2604.11446","title":"Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration","created":"2026-04-13","cited_by_count":4,"area":null},{"id":"2512.17636","title":"Trust-Region Adaptive Policy Optimization","created":"2025-12-19","cited_by_count":3,"area":"lr"},{"id":"2603.24202","title":"A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula","created":"2026-03-25","cited_by_count":3,"area":"synth"},{"id":"2607.07674","title":"Max Out GRPO Signal: Adaptive Trace Prefix Control for Hard Reasoning Problems","created":"2026-07-08","cited_by_count":3,"area":null},{"id":"2505.22311","title":"From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications","created":"2025-05-28","cited_by_count":2,"area":"agents"},{"id":"2606.21943","title":"Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning","created":"2026-06-20","cited_by_count":2,"area":"lr"},{"id":"2503.04530","title":"SOLAR: Scalable Optimization of Large-scale Architecture for Reasoning","created":"2025-03-06","cited_by_count":1,"area":"lr"},{"id":"2510.20653","title":"Finding the Sweet Spot: Trading Quality, Cost, and Speed During Inference-Time LLM Reflection","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2602.15449","title":"TAROT: Test-driven and Capability-adaptive Curriculum Reinforcement Fine-tuning for Code Generation with Large Language Models","created":"2026-02-17","cited_by_count":1,"area":null},{"id":"2502.17498","title":"Improving Value-based Process Verifier via Structural Prior Injection","created":"2025-02-21","cited_by_count":0,"area":"lr"},{"id":"2508.08688","title":"STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision","created":"2025-08-12","cited_by_count":0,"area":"lr"},{"id":"2510.25310","title":"Parrot: A Training Pipeline Enhances Both Program CoT and Natural Language CoT for Reasoning","created":"2025-10-29","cited_by_count":0,"area":"lr"},{"id":"2510.26474","title":"Counteracting Matthew Effect in Self-Improvement of LVLMs through Head-Tail Re-balancing","created":"2025-10-30","cited_by_count":0,"area":"lr"},{"id":"2602.05890","title":"DFPO: Scaling Value Modeling via Distributional Flow towards Robust and Generalizable LLM Post-Training","created":"2026-02-05","cited_by_count":0,"area":null},{"id":"2604.07747","title":"Mitigating Distribution Sharpening in Math RLVR via Distribution-Aligned Hint Synthesis and Backward Hint Annealing","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2605.00433","title":"Improving LLM Code Generation via Requirement-Aware Curriculum Reinforcement Learning","created":"2026-05-01","cited_by_count":0,"area":null},{"id":"2605.10863","title":"DGPO: Beyond Pairwise Preferences with Directional Consistent Groupwise Optimization","created":"2026-05-11","cited_by_count":0,"area":"alignment"},{"id":"2605.20256","title":"FBOS-RL: Feedback-Driven Bi-Objective Synergistic Reinforcement Learning","created":"2026-05-18","cited_by_count":0,"area":"lr"},{"id":"2608.25936","title":"One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation","created":"2026-08-26","cited_by_count":0,"area":"lr"},{"id":"2609.13997","title":"Unlocking the Unsolvable: Teacher-Guided Curriculum for Data-Efficient RLVR","created":"2026-09-12","cited_by_count":0,"area":"lr"},{"id":"2609.22247","title":"CHART: A Harness-Rotation Curriculum for Harness-Robust Search Agents","created":"2026-09-05","cited_by_count":0,"area":null},{"id":"2609.33655","title":"Towards Eliminating Catastrophic Forgetting in the Curriculum Learning of Math Reasoning Tasks","created":"2026-09-27","cited_by_count":0,"area":"lr"},{"id":"2610.11128","title":"Balancing Reference Guidance and Free Generation in Trajectory Rollouts for Reasoning RL","created":"2026-10-08","cited_by_count":0,"area":"lr"},{"id":"2610.15888","title":"Variance-Optimal State Resampling for Reinforcement Learning with Verifiable Rewards","created":"2026-10-11","cited_by_count":0,"area":"lr"},{"id":"2610.19349","title":"Where to Start, How to Move: Analyzing Curricula under GRPO for Long-Horizon LLM Agents","created":"2026-10-14","cited_by_count":0,"area":"lr"}],"next_cursor":null}