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 6,885 篇,第 108 / 138 页

  1. NeurIPS 2024A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
  2. NeurIPS 2024A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
  3. NeurIPS 2024A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
  4. NeurIPS 2024A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations
  5. NeurIPS 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data
  6. NeurIPS 2024A Structure-Aware Framework for Learning Device Placements on Computation Graphs
  7. NeurIPS 2024A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
  8. NeurIPS 2024A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning
  9. NeurIPS 2024A Tractable Inference Perspective of Offline RL
  10. NeurIPS 2024A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
  11. NeurIPS 2024A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective
  12. NeurIPS 2024Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
  13. NeurIPS 2024Achieving $\tilde{O}(1/\epsilon)$ Sample Complexity for Constrained Markov Decision Process
  14. NeurIPS 2024Achieving Constant Regret in Linear Markov Decision Processes
  15. NeurIPS 2024Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
  16. NeurIPS 2024Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
  17. NeurIPS 2024Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
  18. NeurIPS 2024Adaptive $Q$-Aid for Conditional Supervised Learning in Offline Reinforcement Learning
  19. NeurIPS 2024Adaptive Exploration for Data-Efficient General Value Function Evaluations
  20. NeurIPS 2024Adaptive Labeling for Efficient Out-of-distribution Model Evaluation
  21. NeurIPS 2024Adaptive Preference Scaling for Reinforcement Learning with Human Feedback
  22. NeurIPS 2024AdaptiveISP: Learning an Adaptive Image Signal Processor for Object Detection
  23. NeurIPS 2024AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
  24. NeurIPS 2024ADOPT: Modified Adam Can Converge with Any $\beta_2$ with the Optimal Rate
  25. NeurIPS 2024Adversarial Environment Design via Regret-Guided Diffusion Models
  26. NeurIPS 2024Adversarially Robust Decision Transformer
  27. NeurIPS 2024Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning
  28. NeurIPS 2024AGILE: A Novel Reinforcement Learning Framework of LLM Agents
  29. NeurIPS 2024Aligner: Efficient Alignment by Learning to Correct
  30. NeurIPS 2024Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
  31. NeurIPS 2024Aligning Individual and Collective Objectives in Multi-Agent Cooperation
  32. NeurIPS 2024Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
  33. NeurIPS 2024Aligning Vision Models with Human Aesthetics in Retrieval: Benchmarks and Algorithms
  34. NeurIPS 2024Alignment at Pre-training! Towards Native Alignment for Arabic LLMs
  35. NeurIPS 2024AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
  36. NeurIPS 2024Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection
  37. NeurIPS 2024Amortized Active Causal Induction with Deep Reinforcement Learning
  38. NeurIPS 2024Amortizing intractable inference in diffusion models for vision, language, and control
  39. NeurIPS 2024An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning
  40. NeurIPS 2024An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
  41. NeurIPS 2024An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
  42. NeurIPS 2024Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning
  43. NeurIPS 2024Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability
  44. NeurIPS 2024AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
  45. NeurIPS 2024Automated Multi-level Preference for MLLMs
  46. NeurIPS 2024Autoregressive Policy Optimization for Constrained Allocation Tasks
  47. NeurIPS 2024Axioms for AI Alignment from Human Feedback
  48. NeurIPS 2024Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
  49. NeurIPS 2024Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback
  50. NeurIPS 2024BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning

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。