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 31 / 42 页
- ICML 2024EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
- ICML 2024Emergence of In-Context Reinforcement Learning from Noise Distillation
- ICML 2024End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
- ICML 2024Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
- ICML 2024Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning
- ICML 2024Environment Design for Inverse Reinforcement Learning
- ICML 2024EvIL: Evolution Strategies for Generalisable Imitation Learning
- ICML 2024EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
- ICML 2024Exploration and Anti-Exploration with Distributional Random Network Distillation
- ICML 2024Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
- ICML 2024Exploring the LLM Journey from Cognition to Expression with Linear Representations
- ICML 2024Factored-Reward Bandits with Intermediate Observations
- ICML 2024Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models
- ICML 2024Fair Off-Policy Learning from Observational Data
- ICML 2024Fair Resource Allocation in Multi-Task Learning
- ICML 2024Fast Decision Boundary based Out-of-Distribution Detector
- ICML 2024Feasibility Consistent Representation Learning for Safe Reinforcement Learning
- ICML 2024Feasible Reachable Policy Iteration
- ICML 2024Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices
- ICML 2024Feedback Efficient Online Fine-Tuning of Diffusion Models
- ICML 2024FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
- ICML 2024Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
- ICML 2024Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
- ICML 2024Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
- ICML 2024Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
- ICML 2024Foundation Policies with Hilbert Representations
- ICML 2024Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
- ICML 2024From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
- ICML 2024From Generalization Analysis to Optimization Designs for State Space Models
- ICML 2024From Inverse Optimization to Feasibility to ERM
- ICML 2024From Neurons to Neutrons: A Case Study in Interpretability
- ICML 2024From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
- ICML 2024From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
- ICML 2024Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees
- ICML 2024Fundamental Limitations of Alignment in Large Language Models
- ICML 2024FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
- ICML 2024Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction
- ICML 2024GFlowNet Training by Policy Gradients
- ICML 2024Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods
- ICML 2024Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling
- ICML 2024HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning
- ICML 2024HarmonyDream: Task Harmonization Inside World Models
- ICML 2024HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
- ICML 2024HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming
- ICML 2024Hieros: Hierarchical Imagination on Structured State Space Sequence World Models
- ICML 2024How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
- ICML 2024How Does Goal Relabeling Improve Sample Efficiency?
- ICML 2024How to Explore with Belief: State Entropy Maximization in POMDPs
- ICML 2024How to Leverage Diverse Demonstrations in Offline Imitation Learning
- ICML 2024Human Alignment of Large Language Models through Online Preference Optimisation
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。