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 112 / 138 页
- NeurIPS 2024Is Value Learning Really the Main Bottleneck in Offline RL?
- NeurIPS 2024Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
- NeurIPS 2024iVideoGPT: Interactive VideoGPTs are Scalable World Models
- NeurIPS 2024JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
- NeurIPS 2024Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
- NeurIPS 2024KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
- NeurIPS 2024Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
- NeurIPS 2024Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication
- NeurIPS 2024Large Language Models Play StarCraft II:Benchmarks and A Chain of Summarization Approach
- NeurIPS 2024Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
- NeurIPS 2024Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning
- NeurIPS 2024Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference
- NeurIPS 2024Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training
- NeurIPS 2024Learning Distinguishable Trajectory Representation with Contrastive Loss
- NeurIPS 2024Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem
- NeurIPS 2024Learning Formal Mathematics From Intrinsic Motivation
- NeurIPS 2024Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
- NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
- NeurIPS 2024Learning Goal-Conditioned Representations for Language Reward Models
- NeurIPS 2024Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms
- NeurIPS 2024Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
- NeurIPS 2024Learning Successor Features the Simple Way
- NeurIPS 2024Learning to Assist Humans without Inferring Rewards
- NeurIPS 2024Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games
- NeurIPS 2024Learning to Cooperate with Humans using Generative Agents
- NeurIPS 2024Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf
- NeurIPS 2024Learning Versatile Skills with Curriculum Masking
- NeurIPS 2024Learning World Models for Unconstrained Goal Navigation
- NeurIPS 2024LeDex: Training LLMs to Better Self-Debug and Explain Code
- NeurIPS 2024Leveraging Separated World Model for Exploration in Visually Distracted Environments
- NeurIPS 2024LLM-based Skill Diffusion for Zero-shot Policy Adaptation
- NeurIPS 2024Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
- NeurIPS 2024Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
- NeurIPS 2024MADiff: Offline Multi-agent Learning with Diffusion Models
- NeurIPS 2024Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
- NeurIPS 2024Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
- NeurIPS 2024Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
- NeurIPS 2024Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
- NeurIPS 2024Measuring Goal-Directedness
- NeurIPS 2024Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration
- NeurIPS 2024Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence
- NeurIPS 2024MeMo: Meaningful, Modular Controllers via Noise Injection
- NeurIPS 2024Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
- NeurIPS 2024Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement
- NeurIPS 2024Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
- NeurIPS 2024MetaCURL: Non-stationary Concave Utility Reinforcement Learning
- NeurIPS 2024Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games
- NeurIPS 2024Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning
- NeurIPS 2024Minimum Entropy Coupling with Bottleneck
- NeurIPS 2024MiSO: Optimizing brain stimulation to create neural activity states
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。