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 28 / 138 页
- ICML 2026CofactGVR: Counterfactual Intervention for Grounded Visual Reasoning
- ICML 2026CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
- ICML 2026COLLIE: Guiding Skill Discovery in Semantically Coherent Latent Space
- ICML 2026Commit to the Bit: Reactive Reinforcement Learning Done Right
- ICML 2026CompleteP for RL: Maintaining Feature Learning When Scaling Deep Reinforcement Learning
- ICML 2026Compositional Behavioral Semantics for State Abstraction in Reinforcement Learning
- ICML 2026Compositional Transduction with Latent Analogies for Offline Goal-Conditioned Reinforcement Learning
- ICML 2026Compute Where it Counts: Self Optimizing Language Models
- ICML 2026Conditional Equivalence of DPO and RLHF: Assumptions, Failure Modes, and Provable Alignment
- ICML 2026Conformal Policy Control
- ICML 2026ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure
- ICML 2026Consistent Zero-Shot Imitation with Contrastive Goal Inference
- ICML 2026Constrained Flow Optimization via Sequential Fine-Tuning for Molecular Design
- ICML 2026Constrained Meta Reinforcement Learning with Provable Test-Time Safety
- ICML 2026Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
- ICML 2026Context-Aware Reasoner: Enhancing Contextual Reasoning in Multimodal Large Language Models
- ICML 2026Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
- ICML 2026Contextualized Privacy Defense for LLM Agents
- ICML 2026Contextualized Visual Personalization in Vision-Language Models
- ICML 2026Continuity-Regularized Flow Matching for Offline Reinforcement Learning
- ICML 2026Contrastive Reasoning Alignment: Reinforcement Learning from Hidden Representations
- ICML 2026Controllable and Explainable Personality Sliders for LLMs at Inference Time
- ICML 2026Convergence of Steepest Descent and Adam under Non-Uniform Smoothness
- ICML 2026Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning
- ICML 2026Conversation for Non-verifiable Learning: Self-Evolving Large Language Models through Meta-Evaluation
- ICML 2026Convex Optimization for Alignment and Preference Learning on a Single GPU
- ICML 2026CooT: Learning to Coordinate In-Context with Coordination Transformers
- ICML 2026CoRe: Collaborative Reasoning via Cross Teaching
- ICML 2026CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning
- ICML 2026CorrectionPlanner: Self-Correction Planner with Reinforcement Learning in Autonomous Driving
- ICML 2026Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
- ICML 2026Counterfactual Bootstrap for Robust Meta-Reinforcement Learning
- ICML 2026Coupled Variational Reinforcement Learning for Language Model General Reasoning
- ICML 2026Covariance Volume Maximization for Embodied Latent Exploration in Deep Reinforcement Learning
- ICML 2026CPMöbius: Iterative Coach–Player Reasoning for Data-Free Reinforcement Learning
- ICML 2026Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking
- ICML 2026CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents
- ICML 2026CSG: Cognitive Structure Generation for Intelligent Education
- ICML 2026CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning
- ICML 2026Curating the Future: A Scalable Recipe for Training Open-Ended Forecasters
- ICML 2026Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
- ICML 2026D-ARL: A Distribution-Matched Asynchronous Reinforcement Learning Framework for Language Reasoning
- ICML 2026D-CORE: Incentivizing Task Decomposition in Large Reasoning Models for Complex Tool Use
- ICML 2026d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation
- ICML 2026D²Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning
- ICML 2026DADP: Domain Adaptive Diffusion Policy
- ICML 2026DARTS: Distribution-Aware Active Rollout Trajectory Shaping for Accelerating LLM Reinforcement Learning
- ICML 2026Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
- ICML 2026De-attribute to Forget for LLM Unlearning
- ICML 2026Debate2Create: Robot Co-design via Multi-Agent LLM Debate
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。