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 1,021 篇,第 21 / 21 页

  1. ICML 2026What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
  2. ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
  3. ICML 2026What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion
  4. ICML 2026What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity
  5. ICML 2026When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
  6. ICML 2026When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
  7. ICML 2026When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
  8. ICML 2026When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM's Adaptive Reasoning
  9. ICML 2026When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
  10. ICML 2026Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
  11. ICML 2026Why Dedicated Critics: Eliminating Target Drift in Multi-Constraint RL
  12. ICML 2026Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
  13. ICML 2026Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
  14. ICML 2026World Models in Pieces: Structural Certification of General Agents
  15. ICML 2026World-R1: Reinforcing 3D Constraints for Text-to-Video Generation
  16. ICML 2026WorldCompass: Reinforcement Learning for Long-Horizon World Models
  17. ICML 2026WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning
  18. ICML 2026XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
  19. ICML 2026You Can Learn Tokenization End-to-End with Reinforcement Learning
  20. ICML 2026Zero-Shot Off-Policy Learning
  21. ICML 2026Zero-source LLM Hallucination Detection with Human-like Criteria Probing

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。