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 233 篇，第 1 / 5 页

1. ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
2. ICLR 2023A CMDP-within-online framework for Meta-Safe Reinforcement Learning
3. ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
4. ICLR 2023A Mixture-of-Expert Approach to RL-based Dialogue Management
5. ICLR 2023A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search
6. ICLR 2023A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation
7. ICLR 2023A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
8. ICLR 2023A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta.
9. ICLR 2023Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation
10. ICLR 2023Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data
11. ICLR 2023Adversarial Diversity in Hanabi
12. ICLR 2023Adversarial Imitation Learning with Preferences
13. ICLR 2023Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
14. ICLR 2023Automated Data Augmentations for Graph Classification
15. ICLR 2023Average Sensitivity of Decision Tree Learning
16. ICLR 2023Backstepping Temporal Difference Learning
17. ICLR 2023BC-IRL: Learning Generalizable Reward Functions from Demonstrations
18. ICLR 2023Become a Proficient Player with Limited Data through Watching Pure Videos
19. ICLR 2023Behavior Prior Representation learning for Offline Reinforcement Learning
20. ICLR 2023Behavior Proximal Policy Optimization
21. ICLR 2023Benchmarking Constraint Inference in Inverse Reinforcement Learning
22. ICLR 2023Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
23. ICLR 2023Betty: An Automatic Differentiation Library for Multilevel Optimization
24. ICLR 2023Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks
25. ICLR 2023Broken Neural Scaling Laws
26. ICLR 2023Building a Subspace of Policies for Scalable Continual Learning
27. ICLR 2023Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
28. ICLR 2023Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study
29. ICLR 2023Can We Find Nash Equilibria at a Linear Rate in Markov Games?
30. ICLR 2023Causal Confusion and Reward Misidentification in Preference-Based Reward Learning
31. ICLR 2023Causal Imitation Learning via Inverse Reinforcement Learning
32. ICLR 2023Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication
33. ICLR 2023CFlowNets: Continuous Control with Generative Flow Networks
34. ICLR 2023Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning
35. ICLR 2023Choreographer: Learning and Adapting Skills in Imagination
36. ICLR 2023CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
37. ICLR 2023Composing Task Knowledge With Modular Successor Feature Approximators
38. ICLR 2023Confidence-Conditioned Value Functions for Offline Reinforcement Learning
39. ICLR 2023Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
40. ICLR 2023Critic Sequential Monte Carlo
41. ICLR 2023Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots
42. ICLR 2023DaxBench: Benchmarking Deformable Object Manipulation with Differentiable Physics
43. ICLR 2023Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
44. ICLR 2023Decision S4: Efficient Sequence-Based RL via State Spaces Layers
45. ICLR 2023Decision Transformer under Random Frame Dropping
46. ICLR 2023Deep Generative Symbolic Regression
47. ICLR 2023Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
48. ICLR 2023DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
49. ICLR 2023DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
50. ICLR 2023Dichotomy of Control: Separating What You Can Control from What You Cannot

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。