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 5 / 9 页

201. ICLR 2025SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback
202. ICLR 2025Solving New Tasks by Adapting Internet Video Knowledge
203. ICLR 2025Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation
204. ICLR 2025Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
205. ICLR 2025Student-Informed Teacher Training
206. ICLR 2025Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
207. ICLR 2025Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
208. ICLR 2025Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
209. ICLR 2025Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster
210. ICLR 2025The Value of Sensory Information to a Robot
211. ICLR 2025TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning
212. ICLR 2025Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization
213. ICLR 2025Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
214. ICLR 2025Towards General-Purpose Model-Free Reinforcement Learning
215. ICLR 2025Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
216. ICLR 2025TPO: Aligning Large Language Models with Multi-branch & Multi-step Preference Trees
217. ICLR 2025Training Language Models to Self-Correct via Reinforcement Learning
218. ICLR 2025Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction
219. ICLR 2025Trajectory-Class-Aware Multi-Agent Reinforcement Learning
220. ICLR 2025Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning
221. ICLR 2025Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback
222. ICLR 2025Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
223. ICLR 2025UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP
224. ICLR 2025Utilitarian Algorithm Configuration for Infinite Parameter Spaces
225. ICLR 2025UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning
226. ICLR 2025Value-aligned Behavior Cloning for Offline Reinforcement Learning via Bi-level Optimization
227. ICLR 2025Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
228. ICLR 2025VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation
229. ICLR 2025What Makes a Good Diffusion Planner for Decision Making?
230. ICLR 2025XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
231. ICLR 2025Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models
232. ICLR 2025Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
233. ICML 2025A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
234. ICML 2025A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents
235. ICML 2025A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
236. ICML 2025Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
237. ICML 2025Action-Dependent Optimality-Preserving Reward Shaping
238. ICML 2025Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
239. ICML 2025Actor-Critics Can Achieve Optimal Sample Efficiency
240. ICML 2025Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
241. ICML 2025An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
242. ICML 2025Automatic Reward Shaping from Confounded Offline Data
243. ICML 2025Behavior-agnostic Task Inference for Robust Offline In-context Reinforcement Learning
244. ICML 2025Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
245. ICML 2025Benchmarking Quantum Reinforcement Learning
246. ICML 2025Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment
247. ICML 2025Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning
248. ICML 2025Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC
249. ICML 2025C2IQL: Constraint-Conditioned Implicit Q-learning for Safe Offline Reinforcement Learning
250. ICML 2025CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries

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。