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 1,190 篇,第 24 / 24 页
- NeurIPS 2024The Sample-Communication Complexity Trade-off in Federated Q-Learning
- NeurIPS 2024The surprising efficiency of temporal difference learning for rare event prediction
- NeurIPS 2024The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
- NeurIPS 2024The Value of Reward Lookahead in Reinforcement Learning
- NeurIPS 2024Time-Constrained Robust MDPs
- NeurIPS 2024Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
- NeurIPS 2024Towards Effective Planning Strategies for Dynamic Opinion Networks
- NeurIPS 2024Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework
- NeurIPS 2024Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
- NeurIPS 2024Towards Visual Text Design Transfer Across Languages
- NeurIPS 2024Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear $q^\pi$-Realizability and Concentrability
- NeurIPS 2024Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
- NeurIPS 2024Transition Constrained Bayesian Optimization via Markov Decision Processes
- NeurIPS 2024Truncated Variance Reduced Value Iteration
- NeurIPS 2024TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models
- NeurIPS 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
- NeurIPS 2024UltraMedical: Building Specialized Generalists in Biomedicine
- NeurIPS 2024Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
- NeurIPS 2024Understanding and Improving Training-free Loss-based Diffusion Guidance
- NeurIPS 2024Understanding Model Selection for Learning in Strategic Environments
- NeurIPS 2024Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
- NeurIPS 2024Unlock the Intermittent Control Ability of Model Free Reinforcement Learning
- NeurIPS 2024Using Unity to Help Solve Reinforcement Learning
- NeurIPS 2024Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training
- NeurIPS 2024Variational Delayed Policy Optimization
- NeurIPS 2024Verifiably Robust Conformal Prediction
- NeurIPS 2024Verified Safe Reinforcement Learning for Neural Network Dynamic Models
- NeurIPS 2024Vision-Language Navigation with Energy-Based Policy
- NeurIPS 2024Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
- NeurIPS 2024WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
- NeurIPS 2024When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
- NeurIPS 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
- NeurIPS 2024When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
- NeurIPS 2024WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena
- NeurIPS 2024WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
- NeurIPS 2024Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
- NeurIPS 2024Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference Heads
- NeurIPS 2024XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
- NeurIPS 2024Zero-Shot Reinforcement Learning from Low Quality Data
- NeurIPS 2024ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
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。