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

主要结论

• 通用机器学习 · reinforcement learning论文从 2023 年的 287 篇增长到 2026 年的 575 篇，三年间扩大到约 2.0 倍。
• ICLR 是发通用机器学习 · reinforcement learning论文最多的会议，2023–2026 年共 847 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 34 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 2；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · reinforcement learning是 2.0 倍。

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

• NeurIPS 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
• ICML 2026De-attribute to Forget for LLM Unlearning
• ICLR 2026AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
• CVPR 2026Dynamic Important Example Mining for Reinforcement Finetuning
• NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
• ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
• ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
• CVPR 2025Automated Proof of Polynomial Inequalities via Reinforcement Learning
• NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
• ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
• ICLR 2024Bandits with Replenishable Knapsacks: the Best of both Worlds
• CVPR 2024Improving Unsupervised Hierarchical Representation with Reinforcement Learning
• NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
• ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
• ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
• CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
• NeurIPS 2026Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
• ICML 2026Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
• ICLR 2026APPLE: Toward General Active Perception via Reinforcement Learning
• CVPR 2026Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

全部通用机器学习 · reinforcement learning论文

共 82 篇，第 2 / 2 页

51. ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
52. ICML 2024Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation
53. ICML 2024Q-value Regularized Transformer for Offline Reinforcement Learning
54. ICML 2024Random Latent Exploration for Deep Reinforcement Learning
55. ICML 2024Reinforcement Learning from Reachability Specifications: PAC Guarantees with Expected Conditional Distance
56. ICML 2024Rethinking Decision Transformer via Hierarchical Reinforcement Learning
57. ICML 2024Reward Shaping for Reinforcement Learning with An Assistant Reward Agent
58. ICML 2024Reward-Free Kernel-Based Reinforcement Learning
59. ICML 2024RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
60. ICML 2024Rich-Observation Reinforcement Learning with Continuous Latent Dynamics
61. ICML 2024RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences
62. ICML 2024Risk-Sensitive Reward-Free Reinforcement Learning with CVaR
63. ICML 2024Robust Inverse Constrained Reinforcement Learning under Model Misspecification
64. ICML 2024RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
65. ICML 2024Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
66. ICML 2024Sample-Efficient Multiagent Reinforcement Learning with Reset Replay
67. ICML 2024Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
68. ICML 2024SHINE: Shielding Backdoors in Deep Reinforcement Learning
69. ICML 2024Simple Ingredients for Offline Reinforcement Learning
70. ICML 2024Single-Trajectory Distributionally Robust Reinforcement Learning
71. ICML 2024SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning
72. ICML 2024Switching the Loss Reduces the Cost in Batch Reinforcement Learning
73. ICML 2024Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
74. ICML 2024Test-Time Regret Minimization in Meta Reinforcement Learning
75. ICML 2024To the Max: Reinventing Reward in Reinforcement Learning
76. ICML 2024Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
77. ICML 2024Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
78. ICML 2024Uncertainty-Aware Reward-Free Exploration with General Function Approximation
79. ICML 2024Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation
80. ICML 2024Value-Evolutionary-Based Reinforcement Learning
81. ICML 2024When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
82. ICML 2024Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach

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。