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 1,640 篇，第 28 / 33 页
- NeurIPS 2025Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs
- NeurIPS 2025ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
- NeurIPS 2025ProtoPairNet: Interpretable Regression through Prototypical Pair Reasoning
- NeurIPS 2025Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents
- NeurIPS 2025Provably Efficient Online RLHF with One-Pass Reward Modeling
- NeurIPS 2025Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation
- NeurIPS 2025Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
- NeurIPS 2025PurpCode: Reasoning for Safer Code Generation
- NeurIPS 2025Q-Insight: Understanding Image Quality via Visual Reinforcement Learning
- NeurIPS 2025QiMeng-CodeV-R1: Reasoning-Enhanced Verilog Generation
- NeurIPS 2025QiMeng-SALV: Signal-Aware Learning for Verilog Code Generation
- NeurIPS 2025QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Training
- NeurIPS 2025Quality-Driven Curation of Remote Sensing Vision-Language Data via Learned Scoring Models
- NeurIPS 2025Quantifying Generalisation in Imitation Learning
- NeurIPS 2025Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions
- NeurIPS 2025Quantization-Free Autoregressive Action Transformer
- NeurIPS 2025R$^2$ec: Towards Large Recommender Models with Reasoning
- NeurIPS 2025R1-ShareVL: Incentivizing Reasoning Capabilities of Multimodal Large Language Models via Share-GRPO
- NeurIPS 2025RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning
- NeurIPS 2025Rainbow Delay Compensation: A Multi-Agent Reinforcement Learning Framework for Mitigating Observation Delays
- NeurIPS 2025Ranking-based Preference Optimization for Diffusion Models from Implicit User Feedback
- NeurIPS 2025RAST: Reasoning Activation in LLMs via Small-model Transfer
- NeurIPS 2025Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)
- NeurIPS 2025RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon Tasks
- NeurIPS 2025ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
- NeurIPS 2025Real-DRL: Teach and Learn in Reality
- NeurIPS 2025Real-Time Execution of Action Chunking Flow Policies
- NeurIPS 2025Real-World Adverse Weather Image Restoration via Dual-Level Reinforcement Learning with High-Quality Cold Start
- NeurIPS 2025Real-World Reinforcement Learning of Active Perception Behaviors
- NeurIPS 2025Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning of Vision Language Models
- NeurIPS 2025ReasonFlux-PRM: Trajectory-Aware PRMs for Long Chain-of-Thought Reasoning in LLMs
- NeurIPS 2025Reasoning as an Adaptive Defense for Safety
- NeurIPS 2025Reasoning Gym: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
- NeurIPS 2025Reasoning Models Hallucinate More: Factuality-Aware Reinforcement Learning for Large Reasoning Models
- NeurIPS 2025Reasoning Models Sometimes Output Illegible Chains of Thought
- NeurIPS 2025Rebalancing Return Coverage for Conditional Sequence Modeling in Offline Reinforcement Learning
- NeurIPS 2025Rectifying Shortcut Behaviors in Preference-based Reward Learning
- NeurIPS 2025ReDit: Reward Dithering for Improved LLM Policy Optimization
- NeurIPS 2025Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference
- NeurIPS 2025Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach
- NeurIPS 2025Regret Lower Bounds for Decentralized Multi-Agent Stochastic Shortest Path Problems
- NeurIPS 2025Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning
- NeurIPS 2025ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning
- NeurIPS 2025REINFORCE Converges to Optimal Policies with Any Learning Rate
- NeurIPS 2025Reinforced Active Learning for Large-Scale Virtual Screening with Learnable Policy Model
- NeurIPS 2025Reinforced Context Order Recovery for Adaptive Reasoning and Planning
- NeurIPS 2025Reinforcement Learning Finetunes Small Subnetworks in Large Language Models
- NeurIPS 2025Reinforcement learning for one-shot DAG scheduling with comparability identification and dense reward
- NeurIPS 2025Reinforcement Learning for Out-of-Distribution Reasoning in LLMs: An Empirical Study on Diagnosis-Related Group Coding
- NeurIPS 2025Reinforcement Learning for Reasoning in Large Language Models with One Training Example
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。