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 33 / 42 页
- ICML 2024MaxMin-RLHF: Alignment with Diverse Human Preferences
- ICML 2024Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning
- ICML 2024Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
- ICML 2024Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
- ICML 2024Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary
- ICML 2024Mixtures of Experts Unlock Parameter Scaling for Deep RL
- ICML 2024MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation
- ICML 2024Model-based Reinforcement Learning for Confounded POMDPs
- ICML 2024Model-based Reinforcement Learning for Parameterized Action Spaces
- ICML 2024Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
- ICML 2024Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
- ICML 2024Mollification Effects of Policy Gradient Methods
- ICML 2024Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
- ICML 2024More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
- ICML 2024Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
- ICML 2024Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
- ICML 2024Multi-View Clustering by Inter-cluster Connectivity Guided Reward
- ICML 2024MusicRL: Aligning Music Generation to Human Preferences
- ICML 2024Nash Learning from Human Feedback
- ICML 2024Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
- ICML 2024Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
- ICML 2024Neural-Kernel Conditional Mean Embeddings
- ICML 2024No-Regret Reinforcement Learning in Smooth MDPs
- ICML 2024Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation
- ICML 2024Nonlinear Filtering with Brenier Optimal Transport Maps
- ICML 2024ODIN: Disentangled Reward Mitigates Hacking in RLHF
- ICML 2024Offline Actor-Critic Reinforcement Learning Scales to Large Models
- ICML 2024Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
- ICML 2024Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms
- ICML 2024Offline Multi-Objective Optimization
- ICML 2024Offline Transition Modeling via Contrastive Energy Learning
- ICML 2024Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
- ICML 2024OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning
- ICML 2024OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
- ICML 2024On the Second-Order Convergence of Biased Policy Gradient Algorithms
- ICML 2024On The Statistical Complexity of Offline Decision-Making
- ICML 2024On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation
- ICML 2024On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective
- ICML 2024Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning
- ICML 2024Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
- ICML 2024OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videos
- ICML 2024Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks
- ICML 2024Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
- ICML 2024Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
- ICML 2024Pausing Policy Learning in Non-stationary Reinforcement Learning
- ICML 2024PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
- ICML 2024Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
- ICML 2024Pi-DUAL: Using privileged information to distinguish clean from noisy labels
- ICML 2024PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
- ICML 2024PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling
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。