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 1,676 篇，第 23 / 34 页

  1. ICLR 2024ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update
  2. ICLR 2024Off-Policy Primal-Dual Safe Reinforcement Learning
  3. ICLR 2024Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees
  4. ICLR 2024Offline RL with Observation Histories: Analyzing and Improving Sample Complexity
  5. ICLR 2024OMNI: Open-endedness via Models of human Notions of Interestingness
  6. ICLR 2024On Differentially Private Federated Linear Contextual Bandits
  7. ICLR 2024On Double Descent in Reinforcement Learning with LSTD and Random Features
  8. ICLR 2024On Stationary Point Convergence of PPO-Clip
  9. ICLR 2024On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
  10. ICLR 2024On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning
  11. ICLR 2024On the Role of General Function Approximation in Offline Reinforcement Learning
  12. ICLR 2024On Trajectory Augmentations for Off-Policy Evaluation
  13. ICLR 2024Online Information Acquisition: Hiring Multiple Agents
  14. ICLR 2024Optimal Sample Complexity for Average Reward Markov Decision Processes
  15. ICLR 2024PAE: Reinforcement Learning from External Knowledge for Efficient Exploration
  16. ICLR 2024PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback
  17. ICLR 2024Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
  18. ICLR 2024Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
  19. ICLR 2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
  20. ICLR 2024Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning
  21. ICLR 2024Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning
  22. ICLR 2024Pre-training with Synthetic Data Helps Offline Reinforcement Learning
  23. ICLR 2024Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
  24. ICLR 2024Privileged Sensing Scaffolds Reinforcement Learning
  25. ICLR 2024Proper Laplacian Representation Learning
  26. ICLR 2024Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
  27. ICLR 2024Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
  28. ICLR 2024Provable Offline Preference-Based Reinforcement Learning
  29. ICLR 2024Provable Reward-Agnostic Preference-Based Reinforcement Learning
  30. ICLR 2024Provably Efficient CVaR RL in Low-rank MDPs
  31. ICLR 2024Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
  32. ICLR 2024Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
  33. ICLR 2024Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
  34. ICLR 2024Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification
  35. ICLR 2024Query-Policy Misalignment in Preference-Based Reinforcement Learning
  36. ICLR 2024Reasoning with Latent Diffusion in Offline Reinforcement Learning
  37. ICLR 2024Reconciling Spatial and Temporal Abstractions for Goal Representation
  38. ICLR 2024Replay across Experiments: A Natural Extension of Off-Policy RL
  39. ICLR 2024Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL
  40. ICLR 2024REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
  41. ICLR 2024Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency
  42. ICLR 2024Revisiting Data Augmentation in Deep Reinforcement Learning
  43. ICLR 2024Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages
  44. ICLR 2024Reward Design for Justifiable Sequential Decision-Making
  45. ICLR 2024Reward Model Ensembles Help Mitigate Overoptimization
  46. ICLR 2024Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
  47. ICLR 2024Reward-Free Curricula for Training Robust World Models
  48. ICLR 2024RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment
  49. ICLR 2024RLIF: Interactive Imitation Learning as Reinforcement Learning
  50. ICLR 2024Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula

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 查通用机器学习 · reinforcement learning在 ICLR 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": "gml-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。

「通用机器学习」下的其他主题