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 119 / 138 页
- ICLR 2023Causal Confusion and Reward Misidentification in Preference-Based Reward Learning
- ICLR 2023Causal Imitation Learning via Inverse Reinforcement Learning
- ICLR 2023Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication
- ICLR 2023CFlowNets: Continuous Control with Generative Flow Networks
- ICLR 2023Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning
- ICLR 2023Choreographer: Learning and Adapting Skills in Imagination
- ICLR 2023CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
- ICLR 2023Composing Task Knowledge With Modular Successor Feature Approximators
- ICLR 2023Confidence-Conditioned Value Functions for Offline Reinforcement Learning
- ICLR 2023Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
- ICLR 2023Critic Sequential Monte Carlo
- ICLR 2023Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots
- ICLR 2023DaxBench: Benchmarking Deformable Object Manipulation with Differentiable Physics
- ICLR 2023Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
- ICLR 2023Decision S4: Efficient Sequence-Based RL via State Spaces Layers
- ICLR 2023Decision Transformer under Random Frame Dropping
- ICLR 2023Deep Generative Symbolic Regression
- ICLR 2023Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
- ICLR 2023DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
- ICLR 2023DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
- ICLR 2023Dichotomy of Control: Separating What You Can Control from What You Cannot
- ICLR 2023DiffMimic: Efficient Motion Mimicking with Differentiable Physics
- ICLR 2023Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
- ICLR 2023Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
- ICLR 2023Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data
- ICLR 2023Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality
- ICLR 2023Distributional Meta-Gradient Reinforcement Learning
- ICLR 2023Does Zero-Shot Reinforcement Learning Exist?
- ICLR 2023Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting
- ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
- ICLR 2023Efficient Offline Policy Optimization with a Learned Model
- ICLR 2023Efficient Planning in a Compact Latent Action Space
- ICLR 2023Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
- ICLR 2023Emergence of Maps in the Memories of Blind Navigation Agents
- ICLR 2023ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation
- ICLR 2023ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret
- ICLR 2023EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
- ICLR 2023Evaluating Long-Term Memory in 3D Mazes
- ICLR 2023Evolving Populations of Diverse RL Agents with MAP-Elites
- ICLR 2023Explaining RL Decisions with Trajectories
- ICLR 2023Extreme Q-Learning: MaxEnt RL without Entropy
- ICLR 2023Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
- ICLR 2023Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
- ICLR 2023FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation
- ICLR 2023From $t$-SNE to UMAP with contrastive learning
- ICLR 2023From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data
- ICLR 2023Generalize Learned Heuristics to Solve Large-scale Vehicle Routing Problems in Real-time
- ICLR 2023Generating Diverse Cooperative Agents by Learning Incompatible Policies
- ICLR 2023Generative Augmented Flow Networks
- ICLR 2023GFlowNets and variational inference
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。