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 2,079 篇，第 34 / 42 页
- ICML 2024PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
- ICML 2024Planning, Fast and Slow: Online Reinforcement Learning with Action-Free Offline Data via Multiscale Planners
- ICML 2024Policy Evaluation for Variance in Average Reward Reinforcement Learning
- ICML 2024Policy Learning for Balancing Short-Term and Long-Term Rewards
- ICML 2024Policy-conditioned Environment Models are More Generalizable
- ICML 2024Position: Amazing Things Come From Having Many Good Models
- ICML 2024Position: Automatic Environment Shaping is the Next Frontier in RL
- ICML 2024Position: Benchmarking is Limited in Reinforcement Learning Research
- ICML 2024Position: Insights from Survey Methodology can Improve Training Data
- ICML 2024Position: Leverage Foundational Models for Black-Box Optimization
- ICML 2024Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
- ICML 2024Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
- ICML 2024Position: Social Environment Design Should be Further Developed for AI-based Policy-Making
- ICML 2024Position: Video as the New Language for Real-World Decision Making
- ICML 2024Predictive Performance Comparison of Decision Policies Under Confounding
- ICML 2024Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
- ICML 2024Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
- ICML 2024Privacy-Preserving Instructions for Aligning Large Language Models
- ICML 2024Probabilistic Constrained Reinforcement Learning with Formal Interpretability
- ICML 2024Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo
- ICML 2024Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning
- ICML 2024Profile Reconstruction from Private Sketches
- ICML 2024Prompt-based Visual Alignment for Zero-shot Policy Transfer
- ICML 2024Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning
- ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
- ICML 2024Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret
- ICML 2024Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation
- ICML 2024Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
- ICML 2024Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
- ICML 2024Q-value Regularized Transformer for Offline Reinforcement Learning
- ICML 2024QORA: Zero-Shot Transfer via Interpretable Object-Relational Model Learning
- ICML 2024Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization
- ICML 2024Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics
- ICML 2024Quality-Diversity with Limited Resources
- ICML 2024Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design
- ICML 2024Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
- ICML 2024Random Latent Exploration for Deep Reinforcement Learning
- ICML 2024Rate-Optimal Policy Optimization for Linear Markov Decision Processes
- ICML 2024Recovering Labels from Local Updates in Federated Learning
- ICML 2024ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation
- ICML 2024Refining Minimax Regret for Unsupervised Environment Design
- ICML 2024Reflective Policy Optimization
- ICML 2024Reinforcement Learning and Regret Bounds for Admission Control
- ICML 2024Reinforcement Learning from Reachability Specifications: PAC Guarantees with Expected Conditional Distance
- ICML 2024Reinforcement Learning within Tree Search for Fast Macro Placement
- ICML 2024Reinformer: Max-Return Sequence Modeling for Offline RL
- ICML 2024ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages
- ICML 2024ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models
- ICML 2024Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
- ICML 2024Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
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。