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 71 / 138 页
- ICML 2025CogReact: A Reinforced Framework to Model Human Cognitive Reaction Modulated by Dynamic Intervention
- ICML 2025CollabLLM: From Passive Responders to Active Collaborators
- ICML 2025Combinatorial Reinforcement Learning with Preference Feedback
- ICML 2025Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries
- ICML 2025Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method
- ICML 2025Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value Iteration
- ICML 2025Consensus Based Stochastic Optimal Control
- ICML 2025Conservative Offline Goal-Conditioned Implicit V-Learning
- ICML 2025Constrain Alignment with Sparse Autoencoders
- ICML 2025Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium
- ICML 2025Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
- ICML 2025Continual Reinforcement Learning by Planning with Online World Models
- ICML 2025Controlling Large Language Model with Latent Action
- ICML 2025Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
- ICML 2025Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
- ICML 2025Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
- ICML 2025Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning
- ICML 2025Counting atoms faster: policy-based nuclear magnetic resonance pulse sequencing for atomic abundance measurement
- ICML 2025Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
- ICML 2025Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination
- ICML 2025D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
- ICML 2025David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
- ICML 2025Decision Mixer: Integrating Long-term and Local Dependencies via Dynamic Token Selection for Decision-Making
- ICML 2025Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization
- ICML 2025Deep Reinforcement Learning from Hierarchical Preference Design
- ICML 2025Demonstration Selection for In-Context Learning via Reinforcement Learning
- ICML 2025Demystifying Long Chain-of-Thought Reasoning
- ICML 2025Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
- ICML 2025Design Considerations in Offline Preference-based RL
- ICML 2025DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation
- ICML 2025DiMa: Understanding the Hardness of Online Matching Problems via Diffusion Models
- ICML 2025DIME: Diffusion-Based Maximum Entropy Reinforcement Learning
- ICML 2025DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy
- ICML 2025Directly Forecasting Belief for Reinforcement Learning with Delays
- ICML 2025Discriminative Policy Optimization for Token-Level Reward Models
- ICML 2025Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
- ICML 2025Distributionally Robust Policy Learning under Concept Drifts
- ICML 2025Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
- ICML 2025Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
- ICML 2025Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement Learning
- ICML 2025Diving into Self-Evolving Training for Multimodal Reasoning
- ICML 2025Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective
- ICML 2025DPO Meets PPO: Reinforced Token Optimization for RLHF
- ICML 2025DSBRouter: End-to-end Global Routing via Diffusion Schr\"{o}dinger Bridge
- ICML 2025EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
- ICML 2025Efficient Online Reinforcement Learning for Diffusion Policy
- ICML 2025Efficient Skill Discovery via Regret-Aware Optimization
- ICML 2025EGPlace: An Efficient Macro Placement Method via Evolutionary Search with Greedy Repositioning Guided Mutation
- ICML 2025ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
- ICML 2025Eliciting Language Model Behaviors with Investigator Agents
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。