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 1,190 篇,第 9 / 24 页

  1. ICML 2024Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays
  2. ICML 2024BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback
  3. ICML 2024Breadth-First Exploration on Adaptive Grid for Reinforcement Learning
  4. ICML 2024Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
  5. ICML 2024Bridging Environments and Language with Rendering Functions and Vision-Language Models
  6. ICML 2024Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel
  7. ICML 2024Code as Reward: Empowering Reinforcement Learning with VLMs
  8. ICML 2024CogBench: a large language model walks into a psychology lab
  9. ICML 2024Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
  10. ICML 2024Combining Experimental and Historical Data for Policy Evaluation
  11. ICML 2024Confidence Aware Inverse Constrained Reinforcement Learning
  12. ICML 2024Constrained Ensemble Exploration for Unsupervised Skill Discovery
  13. ICML 2024Constrained Reinforcement Learning Under Model Mismatch
  14. ICML 2024Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
  15. ICML 2024Controlled Decoding from Language Models
  16. ICML 2024Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
  17. ICML 2024Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation
  18. ICML 2024Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
  19. ICML 2024Cross-Domain Policy Adaptation by Capturing Representation Mismatch
  20. ICML 2024Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
  21. ICML 2024Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics
  22. ICML 2024Decoding-time Realignment of Language Models
  23. ICML 2024Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
  24. ICML 2024Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration
  25. ICML 2024Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration
  26. ICML 2024Dense Reward for Free in Reinforcement Learning from Human Feedback
  27. ICML 2024Detecting Influence Structures in Multi-Agent Reinforcement Learning
  28. ICML 2024DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching
  29. ICML 2024Discovering Features with Synergistic Interactions in Multiple Views
  30. ICML 2024Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning
  31. ICML 2024Distinguishing the Knowable from the Unknowable with Language Models
  32. ICML 2024Distributional Bellman Operators over Mean Embeddings
  33. ICML 2024Do Transformer World Models Give Better Policy Gradients?
  34. ICML 2024DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems
  35. ICML 2024Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming
  36. ICML 2024DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design
  37. ICML 2024DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
  38. ICML 2024ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance
  39. ICML 2024Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
  40. ICML 2024Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
  41. ICML 2024Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
  42. ICML 2024Efficient World Models with Context-Aware Tokenization
  43. ICML 2024EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
  44. ICML 2024Emergence of In-Context Reinforcement Learning from Noise Distillation
  45. ICML 2024End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
  46. ICML 2024Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
  47. ICML 2024Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning
  48. ICML 2024Environment Design for Inverse Reinforcement Learning
  49. ICML 2024EvIL: Evolution Strategies for Generalisable Imitation Learning
  50. ICML 2024EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search

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。