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 124 / 138 页
- ICML 2023ContraBAR: Contrastive Bayes-Adaptive Deep RL
- ICML 2023Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning
- ICML 2023Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
- ICML 2023Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
- ICML 2023Curious Replay for Model-based Adaptation
- ICML 2023Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity
- ICML 2023Deep Laplacian-based Options for Temporally-Extended Exploration
- ICML 2023Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback
- ICML 2023Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum
- ICML 2023Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions
- ICML 2023Differentiable and Transportable Structure Learning
- ICML 2023Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
- ICML 2023Discovering Object-Centric Generalized Value Functions From Pixels
- ICML 2023Distance Weighted Supervised Learning for Offline Interaction Data
- ICML 2023Distributional Offline Policy Evaluation with Predictive Error Guarantees
- ICML 2023Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling
- ICML 2023Does Sparsity Help in Learning Misspecified Linear Bandits?
- ICML 2023Dynamical Linear Bandits
- ICML 2023ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines
- ICML 2023Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization
- ICML 2023Efficient Online Reinforcement Learning with Offline Data
- ICML 2023Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning
- ICML 2023Emergence of Sparse Representations from Noise
- ICML 2023Emergent Agentic Transformer from Chain of Hindsight Experience
- ICML 2023Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
- ICML 2023Entity Divider with Language Grounding in Multi-Agent Reinforcement Learning
- ICML 2023Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms
- ICML 2023Estimation Beyond Data Reweighting: Kernel Method of Moments
- ICML 2023Explainable Data-Driven Optimization: From Context to Decision and Back Again
- ICML 2023Explaining Reinforcement Learning with Shapley Values
- ICML 2023Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning
- ICML 2023Fair Densities via Boosting the Sufficient Statistics of Exponential Families
- ICML 2023Fair yet Asymptotically Equal Collaborative Learning
- ICML 2023Faith-Shap: The Faithful Shapley Interaction Index
- ICML 2023Fast Rates for Maximum Entropy Exploration
- ICML 2023Federated Online and Bandit Convex Optimization
- ICML 2023FLEX: an Adaptive Exploration Algorithm for Nonlinear Systems
- ICML 2023Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning
- ICML 2023For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal
- ICML 2023FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning
- ICML 2023From Hypergraph Energy Functions to Hypergraph Neural Networks
- ICML 2023From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
- ICML 2023Fundamental Tradeoffs in Learning with Prior Information
- ICML 2023Future-conditioned Unsupervised Pretraining for Decision Transformer
- ICML 2023GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
- ICML 2023Go Beyond Imagination: Maximizing Episodic Reachability with World Models
- ICML 2023Graph Reinforcement Learning for Network Control via Bi-Level Optimization
- ICML 2023Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning
- ICML 2023Guiding Pretraining in Reinforcement Learning with Large Language Models
- ICML 2023Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games
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。