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 32 / 42 页
- ICML 2024Hybrid Inverse Reinforcement Learning
- ICML 2024Hybrid Reinforcement Learning from Offline Observation Alone
- ICML 2024Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States
- ICML 2024Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
- ICML 2024Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting
- ICML 2024Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
- ICML 2024Improving Token-Based World Models with Parallel Observation Prediction
- ICML 2024In value-based deep reinforcement learning, a pruned network is a good network
- ICML 2024In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
- ICML 2024In-Context Learning Agents Are Asymmetric Belief Updaters
- ICML 2024In-Context Reinforcement Learning for Variable Action Spaces
- ICML 2024Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
- ICML 2024Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
- ICML 2024Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments
- ICML 2024Information-Directed Pessimism for Offline Reinforcement Learning
- ICML 2024Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning
- ICML 2024INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
- ICML 2024Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study
- ICML 2024Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective
- ICML 2024Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
- ICML 2024Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint
- ICML 2024Iterative Regularized Policy Optimization with Imperfect Demonstrations
- ICML 2024Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations
- ICML 2024LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
- ICML 2024Langevin Policy for Safe Reinforcement Learning
- ICML 2024Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
- ICML 2024Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
- ICML 2024Learning a Diffusion Model Policy from Rewards via Q-Score Matching
- ICML 2024Learning Causal Dynamics Models in Object-Oriented Environments
- ICML 2024Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
- ICML 2024Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
- ICML 2024Learning Decision Policies with Instrumental Variables through Double Machine Learning
- ICML 2024Learning Decision Trees and Forests with Algorithmic Recourse
- ICML 2024Learning from Streaming Data when Users Choose
- ICML 2024Learning Latent Dynamic Robust Representations for World Models
- ICML 2024Learning Optimal Deterministic Policies with Stochastic Policy Gradients
- ICML 2024Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
- ICML 2024Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
- ICML 2024Learning the Target Network in Function Space
- ICML 2024Learning to Play Atari in a World of Tokens
- ICML 2024Learning to Reach Goals via Diffusion
- ICML 2024Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
- ICML 2024Learning with 3D rotations, a hitchhiker's guide to SO(3)
- ICML 2024Limited Preference Aided Imitation Learning from Imperfect Demonstrations
- ICML 2024Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback
- ICML 2024Linguistic Calibration of Long-Form Generations
- ICML 2024Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
- ICML 2024LLM-Empowered State Representation for Reinforcement Learning
- ICML 2024Logistic Variational Bayes Revisited
- ICML 2024Major-Minor Mean Field Multi-Agent Reinforcement Learning
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。