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 1,021 篇，第 12 / 21 页
- ICML 2026Models Under SCOPE: Scalable and Controllable Routing via Pre-hoc Reasoning
- ICML 2026Moment Matching Q-Learning
- ICML 2026Monitorability as a Free Gift: How RLVR Spontaneously Aligns Reasoning
- ICML 2026MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion Recovery
- ICML 2026MRPO: Magnitude-Regularized Policy Optimization via L1 Constraints
- ICML 2026Multi-Agent Reinforcement Learning with Submodular Reward
- ICML 2026Multi-Task GRPO: Reliable LLM Reasoning Across Tasks
- ICML 2026Multi-timescale Reinforcement Learning by Value Reconstruction
- ICML 2026Multi-view Consistent Latent Action Learning for World Modeling and Control
- ICML 2026Multilingual Safety Alignment Via Sparse Weight Editing
- ICML 2026Multimodal Meta-Verifier with Explicit Structured Recalibration
- ICML 2026Multivariate Distributional Reinforcement Learning Using Sliced Divergences
- ICML 2026MVR-cache: Optimizing Semantic Caching via Multi-Vector Retrieval and Learned Prompt Segmentation
- ICML 2026Native Active Perception as Reasoning for Omni-Modal Understanding
- ICML 2026Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning
- ICML 2026NavOL: Navigation Policy with Online Imitation Learning
- ICML 2026Near-Minimax Multi-Objective RL under Predictable Adversarial Preferences and Preference-Free Exploration in Linear MDPs
- ICML 2026Near-Optimal Regret for KL-Regularized Multi-Armed Bandits
- ICML 2026Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
- ICML 2026Neural–Evolutionary Symbolic Regression with Global Constraints: Constraint-Aware Decoding and Reward Shaping
- ICML 2026Neuro-evolutionary Continual Reinforcement Learning
- ICML 2026Noise as a Natural Regularizer in Markov Decision Processes: Connecting Environmental Stochasticity and Policy Simplicity
- ICML 2026Noise-corrected GRPO: From Noisy Rewards to Unbiased Gradients
- ICML 2026Noise-Guided Transport: Imitation Learning from Random Priors
- ICML 2026Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning
- ICML 2026Non-Adversarial Imitation Learning Provably Free of Compounding Errors: The Value Flow Mechanism
- ICML 2026Non-Parametric Optimization for Scalable Learning in Stochastic Decision Problems
- ICML 2026Non-Uniform Noise-to-Signal Ratio in the REINFORCE Policy-Gradient Estimator
- ICML 2026NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search
- ICML 2026Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random
- ICML 2026Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
- ICML 2026Offline Multi-Agent Reinforcement Learning via Sequential Score Decomposition
- ICML 2026Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment
- ICML 2026Offline Reinforcement Learning with Generative Trajectory Policies
- ICML 2026Offline Reinforcement Learning with Universal Horizon Models
- ICML 2026OGPO: Sample Efficient Full-Finetuning of Generative Control Policies
- ICML 2026Omni-Perception Policy Optimization for Multimodal Emotion Reasoning
- ICML 2026OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization
- ICML 2026On Effectiveness and Efficiency of Agentic Tool-calling and RL Training
- ICML 2026On Group Relative Policy Optimization Collapse in Agent Search: The Lazy Likelihood-Displacement
- ICML 2026On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents
- ICML 2026On Robustness and Chain-of-Thought Consistency of RL-Finetuned VLMs
- ICML 2026On the Emergence of Implicit Curriculum in RLVR Learning Dynamics
- ICML 2026On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
- ICML 2026On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach
- ICML 2026On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
- ICML 2026On the Role of Computation in Reinforcement Learning
- ICML 2026One Tool Is Enough: Reinforcement Learning of LLM Agents for Repository-Level Code Navigation
- ICML 2026One-Way Policy Optimization for Self-Evolving LLMs
- ICML 2026OnePO: Direct One-stage Policy Optimization for SFT-free Domain Adaptation
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。