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 5 / 21 页
- ICML 2026Decision-focused Sparse Tangent Portfolio Optimization
- ICML 2026DECOR: Learning to Decompose and Collaborate in Deep Search via Multi-Agent Reinforcement Learning
- ICML 2026Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning
- ICML 2026Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
- ICML 2026Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance
- ICML 2026Deep Flow Networks
- ICML 2026Deep Reinforcement Learning Finds Bayes-Nash Equilibrium in Competitive Newsvendor Problems
- ICML 2026DeepHA: Scaling Action Chains Elicits Deep Hierarchical Agents
- ICML 2026DeFacto: Counterfactual Thinking with Images for Enforcing Evidence-Grounded and Faithful Reasoning
- ICML 2026Demystifying Entropy Control in LLM RL Training: Theoretical Analysis and Dynamic Scheduling
- ICML 2026Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
- ICML 2026Designing Observation and Action Models for Efficient Reinforcement Learning with LLMs
- ICML 2026Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch
- ICML 2026DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
- ICML 2026DF-ExpEnse: Diffusion Filtered Exploration for Sample Efficient Finetuning
- ICML 2026Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
- ICML 2026Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning
- ICML 2026Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies
- ICML 2026Diffusion Controller: Framework, Algorithms and Parameterization
- ICML 2026Direct Flow Q-Learning
- ICML 2026Directly Optimizing Natural Language Explanations for Behavioral Faithfulness: Simulatability and Recoverability
- ICML 2026Discounted Beta–Bernoulli Reward Estimation for Sample-Efficient Reinforcement Learning with Verifiable Rewards
- ICML 2026Discrete Tilt Matching
- ICML 2026DisPPO: Quantile-Based Distributional Reinforcement Learning for Large Language Models
- ICML 2026Dissecting Post-Training: Uncovering the Complementary Roles of SFT and RL for Document Parsing
- ICML 2026DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
- ICML 2026Distillation Models are Good Samplers for Diffusion Reinforcement Learning
- ICML 2026Distinguishing Imitation Error from Intrinsic Motion Learning Difficulty
- ICML 2026Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner
- ICML 2026Distributed Direct Preference Optimization
- ICML 2026Distributional Active Inference
- ICML 2026Distributional Inverse Reinforcement Learning
- ICML 2026Distributionally Robust Reinforcement Learning from Human Feedback
- ICML 2026DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
- ICML 2026Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
- ICML 2026DLM: Unified Decision Language Model for Offline Multi-Agent Sequential Decision Making
- ICML 2026Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
- ICML 2026Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
- ICML 2026Does Your Reasoning Model Implicitly Know When to Stop Thinking?
- ICML 2026Don't Overthink with Pixels: Efficient Reasoning for Segmentation
- ICML 2026Don't Walk the Line: Boundary Guidance for Filtered Generation
- ICML 2026Doubly Regularized Markov Decision Processes for Robust Reinforcement Learning
- ICML 2026Doubly Robust Distributionally Robust Offline Contextual Pricing
- ICML 2026DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
- ICML 2026DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents
- ICML 2026Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
- ICML 2026DR$^2$Seg: Decomposed Two-Stage Rollouts for Efficient Reasoning Segmentation in Multimodal Large Language Models
- ICML 2026Draft-and-Audit Reinforcement Learning for Optimization Modeling
- ICML 2026Dream-MPC: Gradient-Based Model Predictive Control with Latent Imagination
- ICML 2026DREAM-R: Multimodal Speculative Reasoning with RL-Based Refined Drafting, Precise Verification, and Fully Parallel Execution
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。