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 2,494 篇，第 50 / 50 页
- NeurIPS 2023Taylor TD-learning
- NeurIPS 2023TD Convergence: An Optimization Perspective
- NeurIPS 2023Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
- NeurIPS 2023Tempo Adaptation in Non-stationary Reinforcement Learning
- NeurIPS 2023The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
- NeurIPS 2023The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
- NeurIPS 2023The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
- NeurIPS 2023Thinker: Learning to Plan and Act
- NeurIPS 2023Thought Cloning: Learning to Think while Acting by Imitating Human Thinking
- NeurIPS 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
- NeurIPS 2023Towards robust and generalizable representations of extracellular data using contrastive learning
- NeurIPS 2023TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
- NeurIPS 2023Train Hard, Fight Easy: Robust Meta Reinforcement Learning
- NeurIPS 2023Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
- NeurIPS 2023Training Transitive and Commutative Multimodal Transformers with LoReTTa
- NeurIPS 2023Transportability for Bandits with Data from Different Environments
- NeurIPS 2023Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach
- NeurIPS 2023Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
- NeurIPS 2023Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
- NeurIPS 2023Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
- NeurIPS 2023Uncertainty-Aware Instance Reweighting for Off-Policy Learning
- NeurIPS 2023Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning
- NeurIPS 2023Understanding Contrastive Learning via Distributionally Robust Optimization
- NeurIPS 2023Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
- NeurIPS 2023Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
- NeurIPS 2023Unsupervised Behavior Extraction via Random Intent Priors
- NeurIPS 2023Unsupervised Learning for Solving the Travelling Salesman Problem
- NeurIPS 2023Use perturbations when learning from explanations
- NeurIPS 2023Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies
- NeurIPS 2023Video Prediction Models as Rewards for Reinforcement Learning
- NeurIPS 2023VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning
- NeurIPS 2023VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors
- NeurIPS 2023Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
- NeurIPS 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
- NeurIPS 2023Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets
- NeurIPS 2023WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
- NeurIPS 2023Weakly Coupled Deep Q-Networks
- NeurIPS 2023Weitzman's Rule for Pandora's Box with Correlations
- NeurIPS 2023When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
- NeurIPS 2023When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
- NeurIPS 2023When is Agnostic Reinforcement Learning Statistically Tractable?
- NeurIPS 2023Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
- NeurIPS 2023Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization
- NeurIPS 2023Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis
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。