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 2,079 篇,第 27 / 42 页

  1. ICML 2025Private Federated Learning using Preference-Optimized Synthetic Data
  2. ICML 2025Progressively Label Enhancement for Large Language Model Alignment
  3. ICML 2025Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF
  4. ICML 2025Proto Successor Measure: Representing the Behavior Space of an RL Agent
  5. ICML 2025Provable Maximum Entropy Manifold Exploration via Diffusion Models
  6. ICML 2025Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity
  7. ICML 2025Provable Zero-Shot Generalization in Offline Reinforcement Learning
  8. ICML 2025Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
  9. ICML 2025Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces
  10. ICML 2025Q-Supervised Contrastive Representation: A State Decoupling Framework for Safe Offline Reinforcement Learning
  11. ICML 2025QPRL : Learning Optimal Policies with Quasi-Potential Functions for Asymmetric Traversal
  12. ICML 2025Quantum Algorithms for Finite-horizon Markov Decision Processes
  13. ICML 2025Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
  14. ICML 2025R*: Efficient Reward Design via Reward Structure Evolution and Parameter Alignment Optimization with Large Language Models
  15. ICML 2025R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning
  16. ICML 2025Random Policy Evaluation Uncovers Policies of Generative Flow Networks
  17. ICML 2025Rank-One Modified Value Iteration
  18. ICML 2025Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens
  19. ICML 2025Regret-Free Reinforcement Learning for Temporal Logic Specifications
  20. ICML 2025Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning
  21. ICML 2025ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
  22. ICML 2025REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
  23. ICML 2025Reinforce LLM Reasoning through Multi-Agent Reflection
  24. ICML 2025Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements
  25. ICML 2025Reinforced Lifelong Editing for Language Models
  26. ICML 2025Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator
  27. ICML 2025Reinforcement Learning for Quantum Control under Physical Constraints
  28. ICML 2025Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems
  29. ICML 2025Reinforcement Learning with Random Time Horizons
  30. ICML 2025Reinforcement Learning with Segment Feedback
  31. ICML 2025Rejecting Hallucinated State Targets during Planning
  32. ICML 2025Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
  33. ICML 2025Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
  34. ICML 2025ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
  35. ICML 2025Revisiting Cooperative Off-Policy Multi-Agent Reinforcement Learning
  36. ICML 2025Revisiting Non-Acyclic GFlowNets in Discrete Environments
  37. ICML 2025Reward Translation via Reward Machine in Semi-Alignable MDPs
  38. ICML 2025Reward-free World Models for Online Imitation Learning
  39. ICML 2025Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
  40. ICML 2025Risk-Sensitive Theory of Mind: Coordinating with Agents of Unknown Bias using Cumulative Prospect Theory
  41. ICML 2025RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
  42. ICML 2025RLTHF: Targeted Human Feedback for LLM Alignment
  43. ICML 2025Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism
  44. ICML 2025Robust Autonomy Emerges from Self-Play
  45. ICML 2025Robust Multi-Agent Reinforcement Learning with Stochastic Adversary
  46. ICML 2025Robust Multimodal Large Language Models Against Modality Conflict
  47. ICML 2025Robust Noise Attenuation via Adaptive Pooling of Transformer Outputs
  48. ICML 2025Robust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization
  49. ICML 2025Robust Reward Alignment via Hypothesis Space Batch Cutting
  50. ICML 2025RobustLight: Improving Robustness via Diffusion Reinforcement Learning for Traffic Signal Control

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。