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 10 / 138 页
- ICLR 2026DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning
- ICLR 2026DeepEyesV2: Toward Agentic Multimodal Model
- ICLR 2026DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
- ICLR 2026DeepRAG: Thinking to Retrieve Step by Step for Large Language Models
- ICLR 2026DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
- ICLR 2026Deft Scheduling of Dynamic Cloud Workflows with Varying Deadlines via Mixture-of-Experts
- ICLR 2026DELTA-Code: How RL Unlocks and Transfers New Programming Algorithms in LLMs
- ICLR 2026DemoGrasp: Universal Dexterous Grasping from a Single Demonstration
- ICLR 2026Demystifying Emergent Exploration in Goal-Conditioned RL
- ICLR 2026DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
- ICLR 2026DePO: Demonstration-guided Policy Optimization for Molecular Optimization
- ICLR 2026Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
- ICLR 2026Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
- ICLR 2026Dichotomous Diffusion Policy Optimization
- ICLR 2026Differentiable Model Predictive Control on the GPU
- ICLR 2026DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
- ICLR 2026Diffusion Alignment as Variataional Expectation-Maximization
- ICLR 2026Diffusion Blend: Inference-Time Multi-Preference Alignment for Diffusion Models
- ICLR 2026Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
- ICLR 2026DiffusionNFT: Online Diffusion Reinforcement with Forward Process
- ICLR 2026Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach
- ICLR 2026Discovering Diverse Behaviors via Temporal Contrastive Learning
- ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
- ICLR 2026Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving
- ICLR 2026Discrete Variational Autoencoding via Policy Search
- ICLR 2026Disentangling Length Bias in Preference Learning via Response-Conditioned Modeling
- ICLR 2026Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
- ICLR 2026Distributional value gradients for stochastic environments
- ICLR 2026Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization
- ICLR 2026Distributions as Actions: A Unified Framework for Diverse Action Spaces
- ICLR 2026DIVA-GRPO: Enhancing Multimodal Reasoning through Difficulty-Adaptive Variant Advantage
- ICLR 2026DiVE-k: DIFFERENTIAL VISUAL REASONING FOR FINE-GRAINED IMAGE RECOGNITION
- ICLR 2026Diversity-Enhanced Reasoning for Subjective Questions
- ICLR 2026Diversity-Incentivized Exploration for Versatile Reasoning
- ICLR 2026Divide, Harmonize, Then Conquer It: Shooting Multi-Commodity Flow Problems with Multimodal Language Models
- ICLR 2026Do LLM Agents Know How to Ground, Recover, and Assess? Evaluating Epistemic Competence in Information-Seeking Agents
- ICLR 2026Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs
- ICLR 2026Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning
- ICLR 2026Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?
- ICLR 2026Don't Just Fine-tune the Agent, Tune the Environment
- ICLR 2026Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models
- ICLR 2026DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
- ICLR 2026DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
- ICLR 2026DriveAgent-R1: Advancing VLM-based Autonomous Driving with Active Perception and Hybrid Thinking
- ICLR 2026DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization
- ICLR 2026Dual Goal Representations
- ICLR 2026Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
- ICLR 2026Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts
- ICLR 2026DUET: Optimizing LLM Training Data Mixtures via Noisy Feedback from Unseen, Downstream Evaluation Tasks
- ICLR 2026DuPO: Enabling Reliable Self-Verification via Dual Preference Optimization
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。