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 21 / 42 页
- ICML 2026What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
- ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
- ICML 2026What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion
- ICML 2026What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity
- ICML 2026When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
- ICML 2026When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
- ICML 2026When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
- ICML 2026When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM's Adaptive Reasoning
- ICML 2026When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
- ICML 2026Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
- ICML 2026Why Dedicated Critics: Eliminating Target Drift in Multi-Constraint RL
- ICML 2026Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
- ICML 2026Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
- ICML 2026World Models in Pieces: Structural Certification of General Agents
- ICML 2026World-R1: Reinforcing 3D Constraints for Text-to-Video Generation
- ICML 2026WorldCompass: Reinforcement Learning for Long-Horizon World Models
- ICML 2026WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning
- ICML 2026XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
- ICML 2026You Can Learn Tokenization End-to-End with Reinforcement Learning
- ICML 2026Zero-Shot Off-Policy Learning
- ICML 2026Zero-source LLM Hallucination Detection with Human-like Criteria Probing
- ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
- ICML 2025A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
- ICML 2025A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
- ICML 2025A Mixed-Curvature based Pre-training Paradigm for Multi-Task Vehicle Routing Solver
- ICML 2025A Model of Place Field Reorganization During Reward Maximization
- ICML 2025A Multi-Region Brain Model to Elucidate the Role of Hippocampus in Spatially Embedded Decision-Making
- ICML 2025A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems
- ICML 2025A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
- ICML 2025A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents
- ICML 2025A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
- ICML 2025A Theoretical Justification for Asymmetric Actor-Critic Algorithms
- ICML 2025A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization
- ICML 2025A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO
- ICML 2025Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
- ICML 2025Accurate and Efficient World Modeling with Masked Latent Transformers
- ICML 2025Action-Constrained Imitation Learning
- ICML 2025Action-Dependent Optimality-Preserving Reward Shaping
- ICML 2025Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
- ICML 2025Active Fine-Tuning of Multi-Task Policies
- ICML 2025Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
- ICML 2025Actor-Critics Can Achieve Optimal Sample Efficiency
- ICML 2025Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
- ICML 2025Ad-Hoc Human-AI Coordination Challenge
- ICML 2025Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
- ICML 2025Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection
- ICML 2025ADDQ: Adaptive distributional double Q-learning
- ICML 2025AdvAgent: Controllable Blackbox Red-teaming on Web Agents
- ICML 2025Adversarial Inception Backdoor Attacks against Reinforcement Learning
- ICML 2025Agent-Centric Actor-Critic for Asynchronous 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。