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 29 / 42 页
- ICML 2025The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
- ICML 2025Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization
- ICML 2025Think Twice, Act Once: A Co-Evolution Framework of LLM and RL for Large-Scale Decision Making
- ICML 2025Time-Aware World Model for Adaptive Prediction and Control
- ICML 2025Towards Cost-Effective Reward Guided Text Generation
- ICML 2025Towards Efficient Online Tuning of VLM Agents via Counterfactual Soft Reinforcement Learning
- ICML 2025Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback
- ICML 2025Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
- ICML 2025Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra
- ICML 2025Transfer Q-Learning with Composite MDP Structures
- ICML 2025Trust-Region Twisted Policy Improvement
- ICML 2025TtBA: Two-third Bridge Approach for Decision-Based Adversarial Attack
- ICML 2025Universal Approximation Theorem of Deep Q-Networks
- ICML 2025Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
- ICML 2025Unveiling Markov heads in Pretrained Language Models for Offline Reinforcement Learning
- ICML 2025Value-Based Deep RL Scales Predictably
- ICML 2025Video-Enhanced Offline Reinforcement Learning: A Model-Based Approach
- ICML 2025VinePPO: Refining Credit Assignment in RL Training of LLMs
- ICML 2025Vintix: Action Model via In-Context Reinforcement Learning
- ICML 2025Wait-Less Offline Tuning and Re-solving for Online Decision Making
- ICML 2025Wasserstein Policy Optimization
- ICML 2025When Maximum Entropy Misleads Policy Optimization
- ICML 2025When to retrain a machine learning model
- ICML 2025Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning
- ICML 2025Zero Shot Generalization of Vision-Based RL Without Data Augmentation
- ICML 2025Zero-Shot Offline Imitation Learning via Optimal Transport
- ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
- ICML 2024A Distributional Analogue to the Successor Representation
- ICML 2024A General Framework for Sequential Decision-Making under Adaptivity Constraints
- ICML 2024A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design
- ICML 2024A Minimaximalist Approach to Reinforcement Learning from Human Feedback
- ICML 2024A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
- ICML 2024A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs
- ICML 2024A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
- ICML 2024A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback
- ICML 2024Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
- ICML 2024Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
- ICML 2024Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning
- ICML 2024ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
- ICML 2024Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
- ICML 2024Activation-Descent Regularization for Input Optimization of ReLU Networks
- ICML 2024Active Preference Learning for Large Language Models
- ICML 2024Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
- ICML 2024Adaptive Accompaniment with ReaLchords
- ICML 2024Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
- ICML 2024Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
- ICML 2024Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
- ICML 2024Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
- ICML 2024An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
- ICML 2024An Information Theoretic Approach to Interaction-Grounded 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。