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 411 篇，第 4 / 9 页

151. ICLR 2025On Rollouts in Model-Based Reinforcement Learning
152. ICLR 2025On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
153. ICLR 2025On the Modeling Capabilities of Large Language Models for Sequential Decision Making
154. ICLR 2025Online Reinforcement Learning in Non-Stationary Context-Driven Environments
155. ICLR 2025Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
156. ICLR 2025Online-to-Offline RL for Agent Alignment
157. ICLR 2025Open-World Reinforcement Learning over Long Short-Term Imagination
158. ICLR 2025Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
159. ICLR 2025Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
160. ICLR 2025OptionZero: Planning with Learned Options
161. ICLR 2025ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
162. ICLR 2025Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
163. ICLR 2025PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
164. ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
165. ICLR 2025Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model
166. ICLR 2025Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
167. ICLR 2025PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
168. ICLR 2025POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
169. ICLR 2025Preference Elicitation for Offline Reinforcement Learning
170. ICLR 2025Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
171. ICLR 2025Prioritized Generative Replay
172. ICLR 2025PWM: Policy Learning with Multi-Task World Models
173. ICLR 2025Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation
174. ICLR 2025Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning
175. ICLR 2025QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing
176. ICLR 2025Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency
177. ICLR 2025REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments
178. ICLR 2025Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
179. ICLR 2025Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
180. ICLR 2025Reinforcement learning with combinatorial actions for coupled restless bandits
181. ICLR 2025Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
182. ICLR 2025Revisiting a Design Choice in Gradient Temporal Difference Learning
183. ICLR 2025REvolve: Reward Evolution with Large Language Models using Human Feedback
184. ICLR 2025Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
185. ICLR 2025Reward Learning from Multiple Feedback Types
186. ICLR 2025Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
187. ICLR 2025Robust Transfer of Safety-Constrained Reinforcement Learning Agents
188. ICLR 2025RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
189. ICLR 2025Safety Representations for Safer Policy Learning
190. ICLR 2025Safety-Prioritizing Curricula for Constrained Reinforcement Learning
191. ICLR 2025Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
192. ICLR 2025Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
193. ICLR 2025Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
194. ICLR 2025Select before Act: Spatially Decoupled Action Repetition for Continuous Control
195. ICLR 2025SELF-EVOLVED REWARD LEARNING FOR LLMS
196. ICLR 2025Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
197. ICLR 2025SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
198. ICLR 2025SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
199. ICLR 2025Simple, Good, Fast: Self-Supervised World Models Free of Baggage
200. ICLR 2025Simplifying Deep Temporal Difference Learning

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。