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 784 篇，第 15 / 16 页
- NeurIPS 2025Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies
- NeurIPS 2025Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling
- NeurIPS 2025Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds
- NeurIPS 2025Towards Principled Unsupervised Multi-Agent Reinforcement Learning
- NeurIPS 2025Towards Provable Emergence of In-Context Reinforcement Learning
- NeurIPS 2025Towards Reliable Code-as-Policies: A Neuro-Symbolic Framework for Embodied Task Planning
- NeurIPS 2025Towards Robust Zero-Shot Reinforcement Learning
- NeurIPS 2025Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization
- NeurIPS 2025TP-MDDN: Task-Preferenced Multi-Demand-Driven Navigation with Autonomous Decision-Making
- NeurIPS 2025Tracing the Representation Geometry of Language Models from Pretraining to Post-training
- NeurIPS 2025Train on Pins and Test on Obstacles for Rectilinear Steiner Minimum Tree
- NeurIPS 2025Training a Scientific Reasoning Model for Chemistry
- NeurIPS 2025Training Language Models to Generate Quality Code with Program Analysis Feedback
- NeurIPS 2025Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training
- NeurIPS 2025Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning
- NeurIPS 2025Trajectory Graph Learning: Aligning with Long Trajectories in Reinforcement Learning Without Reward Design
- NeurIPS 2025Tree-Guided Diffusion Planner
- NeurIPS 2025Tru-POMDP: Task Planning Under Uncertainty via Tree of Hypotheses and Open-Ended POMDPs
- NeurIPS 2025Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm
- NeurIPS 2025Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
- NeurIPS 2025TTRL: Test-Time Reinforcement Learning
- NeurIPS 2025Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound
- NeurIPS 2025UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection
- NeurIPS 2025UFT: Unifying Supervised and Reinforcement Fine-Tuning
- NeurIPS 2025Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design
- NeurIPS 2025Uncertainty-aware Preference Alignment for Diffusion Policies
- NeurIPS 2025Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations
- NeurIPS 2025Uncertainty-Guided Exploration for Efficient AlphaZero Training
- NeurIPS 2025Uncertainty-quantified Rollout Policy Adaptation for Unlabelled Cross-domain Video Temporal Grounding
- NeurIPS 2025Uncertainty-Sensitive Privileged Learning
- NeurIPS 2025Understanding Data Influence in Reinforcement Finetuning
- NeurIPS 2025Uni-RL: Unifying Online and Offline RL via Implicit Value Regularization
- NeurIPS 2025UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning
- NeurIPS 2025Unified Reinforcement and Imitation Learning for Vision-Language Models
- NeurIPS 2025UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems
- NeurIPS 2025Unlocking Multimodal Mathematical Reasoning via Process Reward Model
- NeurIPS 2025Unveiling Chain of Step Reasoning for Vision-Language Models with Fine-grained Rewards
- NeurIPS 2025Unveiling the Compositional Ability Gap in Vision-Language Reasoning Model
- NeurIPS 2025URB - Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles
- NeurIPS 2025Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought
- NeurIPS 2025Value Diffusion Reinforcement Learning
- NeurIPS 2025Value Gradient Guidance for Flow Matching Alignment
- NeurIPS 2025Value Improved Actor Critic Algorithms
- NeurIPS 2025Value-Guided Decision Transformer: A Unified Reinforcement Learning Framework for Online and Offline Settings
- NeurIPS 2025Value-Guided Search for Efficient Chain-of-Thought Reasoning
- NeurIPS 2025VaporTok: RL-Driven Adaptive Video Tokenizer with Prior & Task Awareness
- NeurIPS 2025VERA: Variational Inference Framework for Jailbreaking Large Language Models
- NeurIPS 2025ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs
- NeurIPS 2025VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation Models
- NeurIPS 2025Video-R1: Reinforcing Video Reasoning in MLLMs
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。