强化学习论文趋势 2023–2026
策略优化、离线 RL 与基于环境的决策学习
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 6,885 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 484 | 233 | 297 | 56 | 1,070 |
| 2024 | 466 | 304 | 356 | 64 | 1,190 |
| 2025 | 784 | 379 | 405 | 72 | 1,640 |
| 2026 | 760 | 911 | 1,021 | 293 | 2,985 |
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 6,885 篇，第 127 / 138 页
- ICML 2023Policy Gradient in Robust MDPs with Global Convergence Guarantee
- ICML 2023Policy Regularization with Dataset Constraint for Offline Reinforcement Learning
- ICML 2023Posterior Sampling for Deep Reinforcement Learning
- ICML 2023PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient
- ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
- ICML 2023Predicting Rare Events by Shrinking Towards Proportional Odds
- ICML 2023Principled Offline RL in the Presence of Rich Exogenous Information
- ICML 2023Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons
- ICML 2023Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
- ICML 2023Provable Benefit of Mixup for Finding Optimal Decision Boundaries
- ICML 2023Provable Reset-free Reinforcement Learning by No-Regret Reduction
- ICML 2023Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources
- ICML 2023Provably Invariant Learning without Domain Information
- ICML 2023Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
- ICML 2023QAS-Bench: Rethinking Quantum Architecture Search and A Benchmark
- ICML 2023Quantile Credit Assignment
- ICML 2023Quantum Policy Gradient Algorithm with Optimized Action Decoding
- ICML 2023RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution
- ICML 2023Reachability-Aware Laplacian Representation in Reinforcement Learning
- ICML 2023Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
- ICML 2023Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
- ICML 2023Reinforcement Learning Can Be More Efficient with Multiple Rewards
- ICML 2023Reinforcement Learning from Passive Data via Latent Intentions
- ICML 2023Reinforcement Learning in Low-rank MDPs with Density Features
- ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
- ICML 2023Reinforcement Learning with History Dependent Dynamic Contexts
- ICML 2023ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs
- ICML 2023Reparameterized Policy Learning for Multimodal Trajectory Optimization
- ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
- ICML 2023Representation-Driven Reinforcement Learning
- ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
- ICML 2023Retrosynthetic Planning with Dual Value Networks
- ICML 2023Revisiting Bellman Errors for Offline Model Selection
- ICML 2023Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization
- ICML 2023Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
- ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
- ICML 2023RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents
- ICML 2023Robust Collaborative Learning with Linear Gradient Overhead
- ICML 2023Robust Satisficing MDPs
- ICML 2023Robust Situational Reinforcement Learning in Face of Context Disturbances
- ICML 2023Robust Subtask Learning for Compositional Generalization
- ICML 2023Robustly Learning a Single Neuron via Sharpness
- ICML 2023Safe Offline Reinforcement Learning with Real-Time Budget Constraints
- ICML 2023SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
- ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
- ICML 2023Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
- ICML 2023Scalable Safe Policy Improvement via Monte Carlo Tree Search
- ICML 2023Scaling Laws for Reward Model Overoptimization
- ICML 2023Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
- ICML 2023SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查强化学习在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "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。