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 230 篇，第 3 / 5 页

101. ICLR 2025Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning
102. ICLR 2025Lean-STaR: Learning to Interleave Thinking and Proving
103. ICLR 2025Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory
104. ICLR 2025Learning from negative feedback, or positive feedback or both
105. ICLR 2025Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation
106. ICLR 2025Learning mirror maps in policy mirror descent
107. ICLR 2025Learning on One Mode: Addressing Multi-modality in Offline Reinforcement Learning
108. ICLR 2025Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning
109. ICLR 2025Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning
110. ICLR 2025Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning
111. ICLR 2025Learning to Communicate Through Implicit Communication Channels
112. ICLR 2025Learning to Search from Demonstration Sequences
113. ICLR 2025Learning to Steer Markovian Agents under Model Uncertainty
114. ICLR 2025Learning Transformer-based World Models with Contrastive Predictive Coding
115. ICLR 2025Learning View-invariant World Models for Visual Robotic Manipulation
116. ICLR 2025Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning
117. ICLR 2025Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making
118. ICLR 2025Looking into User’s Long-term Interests through the Lens of Conservative Evidential Learning
119. ICLR 2025M^3PC: Test-time Model Predictive Control using Pretrained Masked Trajectory Model
120. ICLR 2025MA$^2$E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder
121. ICLR 2025MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL
122. ICLR 2025MaestroMotif: Skill Design from Artificial Intelligence Feedback
123. ICLR 2025MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
124. ICLR 2025Minimax Optimal Reinforcement Learning with Quasi-Optimism
125. ICLR 2025Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
126. ICLR 2025Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
127. ICLR 2025Model Risk-sensitive Offline Reinforcement Learning
128. ICLR 2025Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
129. ICLR 2025Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds
130. ICLR 2025Model-Free Offline Reinforcement Learning with Enhanced Robustness
131. ICLR 2025Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
132. ICLR 2025Multi-agent cooperation through learning-aware policy gradients
133. ICLR 2025Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
134. ICLR 2025Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
135. ICLR 2025Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
136. ICLR 2025Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
137. ICLR 2025Neuroplastic Expansion in Deep Reinforcement Learning
138. ICLR 2025Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
139. ICLR 2025Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
140. ICLR 2025Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
141. ICLR 2025ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
142. ICLR 2025Offline Hierarchical Reinforcement Learning via Inverse Optimization
143. ICLR 2025Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
144. ICLR 2025Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
145. ICLR 2025OGBench: Benchmarking Offline Goal-Conditioned RL
146. ICLR 2025On Bits and Bandits: Quantifying the Regret-Information Trade-off
147. ICLR 2025On Generalization Across Environments In Multi-Objective Reinforcement Learning
148. ICLR 2025On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
149. ICLR 2025On Rollouts in Model-Based Reinforcement Learning
150. ICLR 2025On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations

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。