强化学习论文趋势 2023–2026

主要结论

• 强化学习论文从 2023 年的 1,070 篇增长到 2026 年的 2,985 篇，三年间扩大到约 2.8 倍。
• NeurIPS 是发强化学习论文最多的会议，2023–2026 年共 2,494 篇，占四个会议总量的 36%。
• 交叉方向里涨得最快的是推理模型：同时属于两个主题的论文从 2023 年的 9 篇增至 2026 年的 437 篇。

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 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
• ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
• ICLR 2026$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space
• CVPR 2026A Causal Marriage between VLM and IRM from Understanding to
• NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
• ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
• ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
• CVPR 2025All-Optical Nonlinear Diffractive Deep Network for Ultrafast Image Denoising
• NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
• ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
• ICLR 2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
• CVPR 2024DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning
• NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
• ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
• ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
• CVPR 2023"Seeing" Electric Network Frequency From Events
• NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
• ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
• ICLR 2026$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning
• CVPR 2026AdaptVision Efficient Vision-Language Models via Adaptive Visual Acquisition

全部强化学习论文

共 356 篇，第 1 / 8 页

1. ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
2. ICML 2024A Distributional Analogue to the Successor Representation
3. ICML 2024A General Framework for Sequential Decision-Making under Adaptivity Constraints
4. ICML 2024A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design
5. ICML 2024A Minimaximalist Approach to Reinforcement Learning from Human Feedback
6. ICML 2024A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
7. ICML 2024A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs
8. ICML 2024A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
9. ICML 2024A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback
10. ICML 2024Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
11. ICML 2024Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
12. ICML 2024Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning
13. ICML 2024ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
14. ICML 2024Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
15. ICML 2024Activation-Descent Regularization for Input Optimization of ReLU Networks
16. ICML 2024Active Preference Learning for Large Language Models
17. ICML 2024Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
18. ICML 2024Adaptive Accompaniment with ReaLchords
19. ICML 2024Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
20. ICML 2024Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
21. ICML 2024Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
22. ICML 2024Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
23. ICML 2024An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
24. ICML 2024An Information Theoretic Approach to Interaction-Grounded Learning
25. ICML 2024ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
26. ICML 2024ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories
27. ICML 2024Augmenting Decision with Hypothesis in Reinforcement Learning
28. ICML 2024Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
29. ICML 2024Bayesian Design Principles for Offline-to-Online Reinforcement Learning
30. ICML 2024Bayesian Exploration Networks
31. ICML 2024Bayesian Regret Minimization in Offline Bandits
32. ICML 2024BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images
33. ICML 2024Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays
34. ICML 2024BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback
35. ICML 2024Breadth-First Exploration on Adaptive Grid for Reinforcement Learning
36. ICML 2024Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
37. ICML 2024Bridging Environments and Language with Rendering Functions and Vision-Language Models
38. ICML 2024Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel
39. ICML 2024Code as Reward: Empowering Reinforcement Learning with VLMs
40. ICML 2024CogBench: a large language model walks into a psychology lab
41. ICML 2024Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
42. ICML 2024Combining Experimental and Historical Data for Policy Evaluation
43. ICML 2024Confidence Aware Inverse Constrained Reinforcement Learning
44. ICML 2024Constrained Ensemble Exploration for Unsupervised Skill Discovery
45. ICML 2024Constrained Reinforcement Learning Under Model Mismatch
46. ICML 2024Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
47. ICML 2024Controlled Decoding from Language Models
48. ICML 2024Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
49. ICML 2024Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation
50. ICML 2024Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning

常见问题

2023–2026 年四大会议一共有多少篇强化学习论文？

共 6,885 篇，按年份分别是 2023 年 1,070 篇、2024 年 1,190 篇、2025 年 1,640 篇、2026 年 2,985 篇。

NeurIPS 2026 有多少篇强化学习论文？

NeurIPS 2026 有 760 篇强化学习论文，上一届是 784 篇。

ICLR 2026 有多少篇强化学习论文？

ICLR 2026 有 911 篇强化学习论文，上一届是 379 篇。

ICML 2026 有多少篇强化学习论文？

ICML 2026 有 1,021 篇强化学习论文，上一届是 405 篇。

CVPR 2026 有多少篇强化学习论文？

CVPR 2026 有 293 篇强化学习论文，上一届是 72 篇。

哪个会议的强化学习论文最多？

NeurIPS，2023–2026 年共 2,494 篇。