强化学习论文趋势 2023–2026

策略优化、离线 RL 与基于环境的决策学习

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 6,885 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

强化学习论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023484233297561,070
2024466304356641,190
2025784379405721,640
20267609111,0212932,985

代表论文

按年份和会议均匀挑选,方便快速看到每一届的样貌

全部强化学习论文

共 911 篇,第 10 / 19 页

  1. ICLR 2026Measuring and Mitigating Rapport Bias of Large Language Models under Multi-Agent Social Interactions
  2. ICLR 2026Measuring Audio's Impact on Correctness: Audio-Contribution-Aware Post-Training of Large Audio Language Models
  3. ICLR 2026Mechanistic Detection and Mitigation of Hallucination in Large Reasoning Models
  4. ICLR 2026MedAgentGym: A Scalable Agentic Training Environment for Code-Centric Reasoning in Biomedical Data Science
  5. ICLR 2026MedVR: Annotation-Free Medical Visual Reasoning via Agentic Reinforcement Learning
  6. ICLR 2026MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents
  7. ICLR 2026Memory-T1: Reinforcement Learning for Temporal Reasoning in Multi-session Agents
  8. ICLR 2026Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learning
  9. ICLR 2026MENLO: From Preferences to Proficiency – Evaluating and Modeling Native-like Quality Across 47 Languages
  10. ICLR 2026MergeMix: A Unified Augmentation Paradigm for Visual and Multi-Modal Understanding
  11. ICLR 2026Meta-RL Induces Exploration in Language Agents
  12. ICLR 2026MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse
  13. ICLR 2026Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models
  14. ICLR 2026Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search
  15. ICLR 2026Minimax Optimal Adversarial Reinforcement Learning
  16. ICLR 2026MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance
  17. ICLR 2026MIRACLE: Model-free Imitation and Reinforcement Learning for Adaptive Cut-Selection
  18. ICLR 2026Mirage or Method? How Model–Task Alignment Induces Divergent RL Conclusions
  19. ICLR 2026Mitigating Hallucination in Vision-Language Model with Depth and Spatial-aware Key-Value Refinement
  20. ICLR 2026Mitigating the Safety Alignment Tax with Null-Space Constrained Policy Optimization
  21. ICLR 2026Mixture-of-World Models: Scaling Multi-Task Reinforcement Learning with Modular Latent Dynamics
  22. ICLR 2026MM-HELIX: Boosting Multimodal Long-Chain Reflective Reasoning with Holistic Platform and Adaptive Hybrid Policy Optimization
  23. ICLR 2026MMDuet2: Enhancing Proactive Interaction of Video MLLMs with Multi-Turn Reinforcement Learning
  24. ICLR 2026MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning
  25. ICLR 2026MobileRL: Online Agentic Reinforcement Learning for Mobile GUI Agents
  26. ICLR 2026MOBODY: Model-Based Off-Dynamics Offline Reinforcement Learning
  27. ICLR 2026Mode-conditioning unlocks superior test-time compute scaling
  28. ICLR 2026Model Predictive Adversarial Imitation Learning for Planning from Observation
  29. ICLR 2026Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting
  30. ICLR 2026MolEditRL: Structure-Preserving Molecular Editing via Discrete Diffusion and Reinforcement Learning
  31. ICLR 2026MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Models for Embodied Task Planning
  32. ICLR 2026More Thought, Less Accuracy? On the Dual Nature of Reasoning in Vision-Language Models
  33. ICLR 2026Motion-R1: Enhancing Motion Generation with Decomposed Chain-of-Thought and RL Binding
  34. ICLR 2026Multi-agent Coordination via Flow Matching
  35. ICLR 2026Multi-Agent Guided Policy Optimization
  36. ICLR 2026Multimodal LLM-assisted Evolutionary Search for Programmatic Control Policies
  37. ICLR 2026Multimodal Policy Internalization for Conversational Agents
  38. ICLR 2026Multiplayer Nash Preference Optimization
  39. ICLR 2026Music Flamingo: Scaling Music Understanding in Audio Language Models
  40. ICLR 2026MVR: Multi-view Video Reward Shaping for Reinforcement Learning
  41. ICLR 2026Native Reasoning Models: Training Language Models to Reason on Unverifiable Data
  42. ICLR 2026Near-Optimal Sample Complexity Bounds for Constrained Average-Reward MDPs
  43. ICLR 2026Negotiated Reasoning: On Provably Addressing Relative Over-Generalization
  44. ICLR 2026Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning
  45. ICLR 2026Neural Multi-Objective Combinatorial Optimization for Flexible Job Shop Scheduling Problems
  46. ICLR 2026Neural Predictor-Corrector: Solving Homotopy Problems with Reinforcement Learning
  47. ICLR 2026Neural+Symbolic Approaches for Interpretable Actor-Critic Reinforcement Learning
  48. ICLR 2026NFT: Bridging Supervised Learning and Reinforcement Learning in Math Reasoning
  49. ICLR 2026No Labels, No Problem: Training Visual Reasoners with Multimodal Verifiers
  50. ICLR 2026No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查强化学习在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "reinforcement-learning"}

两分钟接入 Paperlist MCP(Claude Code、Cursor、Codex、ChatGPT)

常见问题

2023–2026 年四大会议一共有多少篇强化学习论文?
共 6,885 篇,按年份分别是 2023 年 1,070 篇、2024 年 1,190 篇、2025 年 1,640 篇、2026 年 2,985 篇。
NeurIPS 2026 有多少篇强化学习论文?
NeurIPS 2026 有 760 篇强化学习论文,上一届是 784 篇。
ICLR 2026 有多少篇强化学习论文?
ICLR 2026 有 911 篇强化学习论文,上一届是 379 篇。
ICML 2026 有多少篇强化学习论文?
ICML 2026 有 1,021 篇强化学习论文,上一届是 405 篇。
CVPR 2026 有多少篇强化学习论文?
CVPR 2026 有 293 篇强化学习论文,上一届是 72 篇。
哪个会议的强化学习论文最多?
NeurIPS,2023–2026 年共 2,494 篇。