{"total":56,"rows":[{"id":"2509.08827","title":"A Survey of Reinforcement Learning for Large Reasoning Models","created":"2025-09-10","cited_by_count":180,"area":"lr"},{"id":"2508.10751","title":"Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models","created":"2025-08-14","cited_by_count":138,"area":"lr"},{"id":"2511.07317","title":"RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments","created":"2025-11-10","cited_by_count":50,"area":null},{"id":"2505.23590","title":"Jigsaw-R1: A Study of Rule-based Visual Reinforcement Learning with Jigsaw Puzzles","created":"2025-05-29","cited_by_count":36,"area":"lr"},{"id":"2509.20357","title":"Language Models that Think, Chat Better","created":"2025-09-24","cited_by_count":24,"area":"lr"},{"id":"2602.14093","title":"GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training","created":"2026-02-15","cited_by_count":18,"area":"agents"},{"id":"2510.01304","title":"Agentic Jigsaw Interaction Learning for Enhancing Visual Perception and Reasoning in Vision-Language Models","created":"2025-10-01","cited_by_count":11,"area":"lr"},{"id":"2510.16476","title":"NP-Engine: Empowering Optimization Reasoning in Large Language Models with Verifiable Synthetic NP Problems","created":"2025-10-18","cited_by_count":11,"area":"lr"},{"id":"2602.01058","title":"Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning","created":"2026-02-01","cited_by_count":11,"area":"lr"},{"id":"2506.15211","title":"ProtoReasoning: Prototypes as the Foundation for Generalizable Reasoning in LLMs","created":"2025-06-18","cited_by_count":9,"area":"lr"},{"id":"2510.26658","title":"The Era of Agentic Organization: Learning to Organize with Language Models","created":"2025-10-30","cited_by_count":7,"area":"agents"},{"id":"2508.21188","title":"Mirage or Method? How Model-Task Alignment Induces Divergent RL Conclusions","created":"2025-08-28","cited_by_count":6,"area":null},{"id":"2509.04059","title":"Towards an AI Musician: Synthesizing Sheet Music Problems for Musical Reasoning","created":"2025-09-04","cited_by_count":6,"area":"lr"},{"id":"2511.15703","title":"Think Visually, Reason Textually: Vision-Language Synergy in ARC","created":"2025-11-19","cited_by_count":6,"area":null},{"id":"2601.22642","title":"Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification","created":"2026-01-30","cited_by_count":5,"area":"lr"},{"id":"2602.01365","title":"When Domains Interact: Asymmetric and Order-Sensitive Cross-Domain Effects in Reinforcement Learning for Reasoning","created":"2026-02-01","cited_by_count":5,"area":"lr"},{"id":"2603.02119","title":"Pencil Puzzle Bench: A Benchmark for Multi-Step Verifiable Reasoning","created":"2026-03-02","cited_by_count":5,"area":"lr"},{"id":"2508.04280","title":"Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success","created":"2025-08-06","cited_by_count":4,"area":"mllm"},{"id":"2510.08540","title":"MM-HELIX: Boosting Multimodal Long-Chain Reflective Reasoning with Holistic Platform and Adaptive Hybrid Policy Optimization","created":"2025-10-09","cited_by_count":4,"area":"lr"},{"id":"2511.14900","title":"Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models","created":"2025-11-18","cited_by_count":4,"area":"mllm"},{"id":"2604.11446","title":"Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration","created":"2026-04-13","cited_by_count":4,"area":null},{"id":"2512.12633","title":"DiG: Differential Grounding for Enhancing Fine-Grained Perception in Multimodal Large Language Model","created":"2025-12-14","cited_by_count":3,"area":"lr"},{"id":"2512.21194","title":"VisRes Bench: On Evaluating the Visual Reasoning Capabilities of VLMs","created":"2025-12-24","cited_by_count":3,"area":"lr"},{"id":"2603.12133","title":"TopoBench: Benchmarking LLMs on Hard Topological Reasoning","created":"2026-03-12","cited_by_count":3,"area":"lr"},{"id":"2607.25308","title":"CAST: Game Solvers as Turn-Level Teachers for LLM Agents","created":"2026-07-28","cited_by_count":3,"area":"agents"},{"id":"2510.01581","title":"Think Right: Learning to Mitigate Under-Over Thinking via Adaptive, Attentive Compression","created":"2025-10-02","cited_by_count":2,"area":"lr"},{"id":"2510.08872","title":"GTAlign: Game-Theoretic Alignment of LLM Assistants for Social Welfare","created":"2025-10-10","cited_by_count":2,"area":null},{"id":"2511.20814","title":"SPHINX: A Synthetic Environment for Visual Perception and Reasoning","created":"2025-11-25","cited_by_count":2,"area":"lr"},{"id":"2606.05976","title":"The Self-Correction Illusion: Role Relabeling Gates Explicit Error Flagging in Large Language Models","created":"2026-06-04","cited_by_count":2,"area":"lr"},{"id":"2601.07238","title":"Group Pattern Selection Optimization: Let LRMs Pick the Right Pattern for Reasoning","created":"2026-01-12","cited_by_count":1,"area":"lr"},{"id":"2601.16480","title":"TL-GRPO: Turn-Level RL for Reasoning-Guided Iterative Optimization","created":"2026-01-23","cited_by_count":1,"area":"lr"},{"id":"2602.10224","title":"Internalizing Meta-Experience into Memory for Guided Reinforcement Learning in Large Language Models","created":"2026-02-10","cited_by_count":1,"area":"lr"},{"id":"2605.06638","title":"Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key","created":"2026-05-07","cited_by_count":1,"area":"lr"},{"id":"2605.12667","title":"ODRPO: Ordinal Decompositions of Discrete Rewards for Robust Policy Optimization","created":"2026-05-12","cited_by_count":1,"area":"alignment"},{"id":"2607.19790","title":"Trace: A Taxonomy-Guided Environment for Multidomain Visual Reasoning","created":"2026-07-22","cited_by_count":1,"area":"lr"},{"id":"2609.35641","title":"Verifiable Visual Rewards Transfer from Synthetic Scenes to Natural Prompts","created":"2026-09-28","cited_by_count":1,"area":"mllm"},{"id":"2510.03394","title":"Studying the Korean Word-Chain Game with RLVR: Mitigating Reward Conflicts via Curriculum Learning","created":"2025-10-03","cited_by_count":0,"area":"lr"},{"id":"2511.18384","title":"NSTR: Neural Spectral Transport Representation for Space-Varying Frequency Fields","created":"2025-11-23","cited_by_count":0,"area":null},{"id":"2511.18387","title":"Scaling Implicit Fields via Hypernetwork-Driven Multiscale Coordinate Transformations","created":"2025-11-23","cited_by_count":0,"area":null},{"id":"2601.06431","title":"LsrIF: Enhancing Logic-Structured Instruction Following of Large Language Models","created":"2026-01-10","cited_by_count":0,"area":null},{"id":"2602.18812","title":"GenPlanner: From Noise to Plans -- Emergent Reasoning in Flow Matching and Diffusion Models","created":"2026-02-21","cited_by_count":0,"area":"diffusion"},{"id":"2604.17312","title":"A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions","created":"2026-04-19","cited_by_count":0,"area":"lr"},{"id":"2605.08498","title":"MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMs","created":"2026-05-08","cited_by_count":0,"area":"lr"},{"id":"2605.08905","title":"Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMs","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2606.05464","title":"Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces","created":"2026-06-03","cited_by_count":0,"area":"lr"},{"id":"2609.27166","title":"Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models","created":"2026-09-22","cited_by_count":0,"area":"lr"},{"id":"2609.29421","title":"Rufus-Air: An Open LLM Post-Training Recipe","created":"2026-09-24","cited_by_count":0,"area":"alignment"},{"id":"2609.30936","title":"Self-Play Search Distillation for Large Language Model Reasoning","created":"2026-09-25","cited_by_count":0,"area":"lr"},{"id":"2609.32208","title":"Witness: Discovery, Deciphering, and Epiphany in Interactive Puzzle Environments","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2609.33780","title":"Selecting Diverse SFT Traces Improves Post-RL Generalization","created":"2026-09-27","cited_by_count":0,"area":"lr"},{"id":"2609.35426","title":"Frontier Learning: Training LLM Reasoners at the Edge of Capability","created":"2026-09-28","cited_by_count":0,"area":"lr"},{"id":"2609.38409","title":"ArgGYM: A Procedural, Engine-Verified Benchmark for Structured Defeasible Reasoning","created":"2026-09-29","cited_by_count":0,"area":"lr"},{"id":"2609.38806","title":"Blackboard Intelligence Can Surpass Autoregressive on Globally Constrained Problems","created":"2026-09-30","cited_by_count":0,"area":"diffusion"},{"id":"2610.14402","title":"SAT-RL: Training Language Models for Logical Reasoning with Symbolic Solvers","created":"2026-10-09","cited_by_count":0,"area":"lr"},{"id":"2610.18868","title":"Tev: Scaling Long-Horizon Agentic Environments with Dense Progress Rewards","created":"2026-10-13","cited_by_count":0,"area":"agents"},{"id":"2610.19062","title":"RLPE: Teaching LLMs to Prompt with Reinforcement Learning","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}