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 335 篇，第 3 / 7 页

101. ICLR 2026Fathom-DeepResearch: Unlocking Long Horizon Information Retrieval and Synthesis for SLMs
102. ICLR 2026Fine-tuning Behavioral Cloning Policies with Preference‑Based Reinforcement Learning
103. ICLR 2026floq: Training Critics via Flow-Matching for Scaling Compute in Value-Based RL
104. ICLR 2026Flow Actor-Critic for Offline Reinforcement Learning
105. ICLR 2026Flow Matching Policy Gradients
106. ICLR 2026Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning
107. ICLR 2026Flow-Based Single-Step Completion for Efficient and Expressive Policy Learning
108. ICLR 2026Flowing Through States: Neural ODE Regularization for Reinforcement Learning
109. ICLR 2026FlowRL: Matching Reward Distributions for LLM Reasoning
110. ICLR 2026From Observations to Events: Event-Aware World Models for Reinforcement Learning
111. ICLR 2026From Parameters to Behaviors: Unsupervised Compression of the Policy Space
112. ICLR 2026From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments
113. ICLR 2026GAS: Enhancing Reward-Cost Balance of Generative Model-assisted Offline Safe RL
114. ICLR 2026General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess
115. ICLR 2026Geometric-Mean Policy Optimization
116. ICLR 2026Geometry of Uncertainty: Learning Metric Spaces for Multimodal State Estimation in RL
117. ICLR 2026GEPO: Group Expectation Policy Optimization for Stable Heterogeneous Reinforcement Learning
118. ICLR 2026Getting Your LLMs Ready for Reinforcement Learning with Lightweight SFT
119. ICLR 2026GlobeDiff: State Diffusion Process for Partial Observability in Multi-Agent System
120. ICLR 2026Goal Reaching with Eikonal-Constrained Hierarchical Quasimetric Reinforcement Learning
121. ICLR 2026GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies
122. ICLR 2026GRACE: A Language Model Framework for Explainable Inverse Reinforcement Learning
123. ICLR 2026Graph-Theoretic Intrinsic Reward: Guiding RL with Effective Resistance
124. ICLR 2026GRL-SNAM: Geometric Reinforcement Learning with Differential Hamiltonians for Navigation and Mapping in Unknown Environments
125. ICLR 2026Guided Flow Policy: Learning from High-Value Actions in Offline Reinforcement Learning
126. ICLR 2026Guided Policy Optimization under Partial Observability
127. ICLR 2026Heterogeneous Agent Q-weighted Policy Optimization
128. ICLR 2026Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion
129. ICLR 2026Hierarchy-of-Groups Policy Optimization for Long-Horizon Agentic Tasks
130. ICLR 2026How to Lose Inherent Counterfactuality in Reinforcement Learning
131. ICLR 2026Hybrid Reinforcement: when reward is sparse, better to be dense
132. ICLR 2026Imitation Learning as Return Distribution Matching
133. ICLR 2026Improving and Accelerating Offline RL in Large Discrete Action Spaces with Structured Policy Initialization
134. ICLR 2026Improving Human-AI Coordination through Online Adversarial Training and Generative Models
135. ICLR 2026In-Context Compositional Q-Learning for Offline Reinforcement Learning
136. ICLR 2026In-Context Learning for Pure Exploration
137. ICLR 2026Incentivizing Consistent, Effective and Scalable Reasoning Capability in Audio LLMs via Reasoning Process Rewards
138. ICLR 2026Information-based Value Iteration Networks for Decision Making Under Uncertainty
139. ICLR 2026Intention-Conditioned Flow Occupancy Models
140. ICLR 2026Inter-Agent Relative Representations for Multi-Agent Option Discovery
141. ICLR 2026Invert4TVG: A Temporal Video Grounding Framework with Inversion Tasks Preserving Action Understanding Ability
142. ICLR 2026Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation?
143. ICLR 2026Jackpot: Align Actor-Policy Distribution for scalable and stable RL for LLM
144. ICLR 2026KL-Regularized Reinforcement Learning is Designed to Mode Collapse
145. ICLR 2026Koopman-Assisted Trajectory Synthesis: A Data Augmentation Framework for Offline Imitation Learning
146. ICLR 2026Latent Wasserstein Adversarial Imitation Learning
147. ICLR 2026Learning Dynamics Feature Representation via Policy Attention for Dynamic Path Planning in Urban Road Networks
148. ICLR 2026Learning Efficient and Interpretable Multi-Agent Communication
149. ICLR 2026Learning from Algorithm Feedback: One-Shot SAT Solver Guidance with GNNs
150. ICLR 2026Learning Massively Multitask World Models for Continuous Control

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。