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 304 篇，第 5 / 7 页
- ICLR 2024Provable Reward-Agnostic Preference-Based Reinforcement Learning
- ICLR 2024Provably Efficient CVaR RL in Low-rank MDPs
- ICLR 2024Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
- ICLR 2024Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
- ICLR 2024Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
- ICLR 2024Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification
- ICLR 2024Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
- ICLR 2024Query-Policy Misalignment in Preference-Based Reinforcement Learning
- ICLR 2024RAIN: Your Language Models Can Align Themselves without Finetuning
- ICLR 2024RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering
- ICLR 2024Reasoning with Latent Diffusion in Offline Reinforcement Learning
- ICLR 2024Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces
- ICLR 2024Reconciling Spatial and Temporal Abstractions for Goal Representation
- ICLR 2024Reinforcement Symbolic Regression Machine
- ICLR 2024Replay across Experiments: A Natural Extension of Off-Policy RL
- ICLR 2024Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL
- ICLR 2024Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization
- ICLR 2024Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
- ICLR 2024REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
- ICLR 2024Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency
- ICLR 2024Revisiting Data Augmentation in Deep Reinforcement Learning
- ICLR 2024Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages
- ICLR 2024Reward Design for Justifiable Sequential Decision-Making
- ICLR 2024Reward Model Ensembles Help Mitigate Overoptimization
- ICLR 2024Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
- ICLR 2024Reward-Free Curricula for Training Robust World Models
- ICLR 2024RingAttention with Blockwise Transformers for Near-Infinite Context
- ICLR 2024RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment
- ICLR 2024RLIF: Interactive Imitation Learning as Reinforcement Learning
- ICLR 2024Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula
- ICLR 2024Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control
- ICLR 2024S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
- ICLR 2024Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
- ICLR 2024Safe RLHF: Safe Reinforcement Learning from Human Feedback
- ICLR 2024SafeDreamer: Safe Reinforcement Learning with World Models
- ICLR 2024SALMON: Self-Alignment with Instructable Reward Models
- ICLR 2024Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
- ICLR 2024Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
- ICLR 2024Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
- ICLR 2024Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
- ICLR 2024Sample-Efficient Multi-Agent RL: An Optimization Perspective
- ICLR 2024Sample-Efficient Quality-Diversity by Cooperative Coevolution
- ICLR 2024Score Models for Offline Goal-Conditioned Reinforcement Learning
- ICLR 2024Score Regularized Policy Optimization through Diffusion Behavior
- ICLR 2024SEABO: A Simple Search-Based Method for Offline Imitation Learning
- ICLR 2024Searching for High-Value Molecules Using Reinforcement Learning and Transformers
- ICLR 2024Selective Visual Representations Improve Convergence and Generalization for Embodied AI
- ICLR 2024Simple Hierarchical Planning with Diffusion
- ICLR 2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
- ICLR 2024Skill or Luck? Return Decomposition via Advantage Functions
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。