通用机器学习 · reinforcement learning论文趋势 2023–2026

通用机器学习：reinforcement_learning

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,676 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

通用机器学习 · reinforcement learning论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202314666723287
2024101216824403
2025108230712411
202611333511314575

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

全部通用机器学习 · reinforcement learning论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 411 篇，第 6 / 9 页

  1. ICML 2025Combinatorial Reinforcement Learning with Preference Feedback
  2. ICML 2025Conservative Offline Goal-Conditioned Implicit V-Learning
  3. ICML 2025Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium
  4. ICML 2025Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
  5. ICML 2025DIME: Diffusion-Based Maximum Entropy Reinforcement Learning
  6. ICML 2025Directly Forecasting Belief for Reinforcement Learning with Delays
  7. ICML 2025Distributionally Robust Policy Learning under Concept Drifts
  8. ICML 2025Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
  9. ICML 2025Empirical Design in Reinforcement Learning
  10. ICML 2025Flow Q-Learning
  11. ICML 2025Gradient Boosting Reinforcement Learning
  12. ICML 2025Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
  13. ICML 2025Hierarchical Reinforcement Learning with Targeted Causal Interventions
  14. ICML 2025Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
  15. ICML 2025Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning
  16. ICML 2025Hyperspherical Normalization for Scalable Deep Reinforcement Learning
  17. ICML 2025IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
  18. ICML 2025Improving Transformer World Models for Data-Efficient RL
  19. ICML 2025In-Context Reinforcement Learning From Suboptimal Historical Data
  20. ICML 2025KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies
  21. ICML 2025Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
  22. ICML 2025Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
  23. ICML 2025Linear $Q$-Learning Does Not Diverge in $L^2$: Convergence Rates to a Bounded Set
  24. ICML 2025Maximum Total Correlation Reinforcement Learning
  25. ICML 2025Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback
  26. ICML 2025Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
  27. ICML 2025Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization
  28. ICML 2025Partially Observable Reinforcement Learning with Memory Traces
  29. ICML 2025Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
  30. ICML 2025Polynomial-Time Approximability of Constrained Reinforcement Learning
  31. ICML 2025Position: Constants are Critical in Regret Bounds for Reinforcement Learning
  32. ICML 2025Position: General Intelligence Requires Reward-based Pretraining
  33. ICML 2025Position: Lifetime tuning is incompatible with continual reinforcement learning
  34. ICML 2025Provable Maximum Entropy Manifold Exploration via Diffusion Models
  35. ICML 2025Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
  36. ICML 2025QPRL : Learning Optimal Policies with Quasi-Potential Functions for Asymmetric Traversal
  37. ICML 2025Regret-Free Reinforcement Learning for Temporal Logic Specifications
  38. ICML 2025Reinforcement Learning with Random Time Horizons
  39. ICML 2025Reinforcement Learning with Segment Feedback
  40. ICML 2025Reward Translation via Reward Machine in Semi-Alignable MDPs
  41. ICML 2025Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
  42. ICML 2025Robust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization
  43. ICML 2025RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
  44. ICML 2025Sleeping Reinforcement Learning
  45. ICML 2025Stay Hungry, Keep Learning: Sustainable Plasticity for Deep Reinforcement Learning
  46. ICML 2025Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
  47. ICML 2025Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks
  48. ICML 2025The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning
  49. ICML 2025The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
  50. ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes

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常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · reinforcement learning论文？
共 1,676 篇，按年份分别是 2023 年 287 篇、2024 年 403 篇、2025 年 411 篇、2026 年 575 篇。
NeurIPS 2026 有多少篇通用机器学习 · reinforcement learning论文？
NeurIPS 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 108 篇。
ICLR 2026 有多少篇通用机器学习 · reinforcement learning论文？
ICLR 2026 有 335 篇通用机器学习 · reinforcement learning论文，上一届是 230 篇。
ICML 2026 有多少篇通用机器学习 · reinforcement learning论文？
ICML 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 71 篇。
CVPR 2026 有多少篇通用机器学习 · reinforcement learning论文？
CVPR 2026 有 14 篇通用机器学习 · reinforcement learning论文，上一届是 2 篇。
哪个会议的通用机器学习 · reinforcement learning论文最多？
ICLR，2023–2026 年共 847 篇。

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