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 7 / 24 页
- ICLR 2024Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
- ICLR 2024Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
- ICLR 2024Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
- ICLR 2024Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
- ICLR 2024Sample-Efficient Multi-Agent RL: An Optimization Perspective
- ICLR 2024Sample-Efficient Quality-Diversity by Cooperative Coevolution
- ICLR 2024Score Models for Offline Goal-Conditioned Reinforcement Learning
- ICLR 2024Score Regularized Policy Optimization through Diffusion Behavior
- ICLR 2024SEABO: A Simple Search-Based Method for Offline Imitation Learning
- ICLR 2024Searching for High-Value Molecules Using Reinforcement Learning and Transformers
- ICLR 2024Selective Visual Representations Improve Convergence and Generalization for Embodied AI
- ICLR 2024Simple Hierarchical Planning with Diffusion
- ICLR 2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
- ICLR 2024Skill or Luck? Return Decomposition via Advantage Functions
- ICLR 2024Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
- ICLR 2024Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution
- ICLR 2024Spatially-Aware Transformers for Embodied Agents
- ICLR 2024SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores
- ICLR 2024Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
- ICLR 2024STARC: A General Framework For Quantifying Differences Between Reward Functions
- ICLR 2024Statistical Rejection Sampling Improves Preference Optimization
- ICLR 2024Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
- ICLR 2024Submodular Reinforcement Learning
- ICLR 2024SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
- ICLR 2024Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
- ICLR 2024Task Planning for Visual Room Rearrangement under Partial Observability
- ICLR 2024TD-MPC2: Scalable, Robust World Models for Continuous Control
- ICLR 2024Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
- ICLR 2024Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
- ICLR 2024The Curse of Diversity in Ensemble-Based Exploration
- ICLR 2024The Effective Horizon Explains Deep RL Performance in Stochastic Environments
- ICLR 2024The Generalization Gap in Offline Reinforcement Learning
- ICLR 2024The Trickle-down Impact of Reward Inconsistency on RLHF
- ICLR 2024The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
- ICLR 2024The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
- ICLR 2024Thin-Shell Object Manipulations With Differentiable Physics Simulations
- ICLR 2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
- ICLR 2024Time-Varying Propensity Score to Bridge the Gap between the Past and Present
- ICLR 2024Tool-Augmented Reward Modeling
- ICLR 2024TorchRL: A data-driven decision-making library for PyTorch
- ICLR 2024Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games
- ICLR 2024Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
- ICLR 2024Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
- ICLR 2024Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
- ICLR 2024Towards Principled Representation Learning from Videos for Reinforcement Learning
- ICLR 2024Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
- ICLR 2024Towards Understanding Sycophancy in Language Models
- ICLR 2024Training Diffusion Models with Reinforcement Learning
- ICLR 2024Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining
- ICLR 2024Tree Search-Based Policy Optimization under Stochastic Execution Delay
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。