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 297 篇，第 1 / 6 页

1. ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
2. ICML 2023A Coupled Flow Approach to Imitation Learning
3. ICML 2023A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems
4. ICML 2023A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints
5. ICML 2023A Reinforcement Learning Framework for Dynamic Mediation Analysis
6. ICML 2023A Robust Test for the Stationarity Assumption in Sequential Decision Making
7. ICML 2023A Universal Unbiased Method for Classification from Aggregate Observations
8. ICML 2023Abstracting Imperfect Information Away from Two-Player Zero-Sum Games
9. ICML 2023Action Matching: Learning Stochastic Dynamics from Samples
10. ICML 2023Active Policy Improvement from Multiple Black-box Oracles
11. ICML 2023Actor-Critic Alignment for Offline-to-Online Reinforcement Learning
12. ICML 2023AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners
13. ICML 2023Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
14. ICML 2023Adversarial Cheap Talk
15. ICML 2023Adversarial Learning of Distributional Reinforcement Learning
16. ICML 2023Aligning Language Models with Preferences through $f$-divergence Minimization
17. ICML 2023An Adaptive Entropy-Regularization Framework for Multi-Agent Reinforcement Learning
18. ICML 2023An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning
19. ICML 2023Anti-Exploration by Random Network Distillation
20. ICML 2023Atari-5: Distilling the Arcade Learning Environment down to Five Games
21. ICML 2023Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability
22. ICML 2023Automatic Intrinsic Reward Shaping for Exploration in Deep Reinforcement Learning
23. ICML 2023Bayesian Design Principles for Frequentist Sequential Learning
24. ICML 2023Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models
25. ICML 2023Behavior Contrastive Learning for Unsupervised Skill Discovery
26. ICML 2023Best of Both Worlds Policy Optimization
27. ICML 2023Better Training of GFlowNets with Local Credit and Incomplete Trajectories
28. ICML 2023Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic
29. ICML 2023Beyond Reward: Offline Preference-guided Policy Optimization
30. ICML 2023Bidirectional Learning for Offline Model-based Biological Sequence Design
31. ICML 2023Bilevel Optimization with Coupled Decision-Dependent Distributions
32. ICML 2023Boosting Offline Reinforcement Learning with Action Preference Query
33. ICML 2023Bootstrapped Representations in Reinforcement Learning
34. ICML 2023Cell-Free Latent Go-Explore
35. ICML 2023ChiPFormer: Transferable Chip Placement via Offline Decision Transformer
36. ICML 2023CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling
37. ICML 2023CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms
38. ICML 2023CLUTR: Curriculum Learning via Unsupervised Task Representation Learning
39. ICML 2023Complementary Attention for Multi-Agent Reinforcement Learning
40. ICML 2023Compositional Exemplars for In-context Learning
41. ICML 2023Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
42. ICML 2023Conditional Graph Information Bottleneck for Molecular Relational Learning
43. ICML 2023Constrained Decision Transformer for Offline Safe Reinforcement Learning
44. ICML 2023Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
45. ICML 2023Continual Task Allocation in Meta-Policy Network via Sparse Prompting
46. ICML 2023Continuation Path Learning for Homotopy Optimization
47. ICML 2023ContraBAR: Contrastive Bayes-Adaptive Deep RL
48. ICML 2023Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning
49. ICML 2023Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
50. ICML 2023Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes

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。