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 2,494 篇，第 41 / 50 页
- NeurIPS 2024When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
- NeurIPS 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
- NeurIPS 2024When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
- NeurIPS 2024WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena
- NeurIPS 2024WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
- NeurIPS 2024Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
- NeurIPS 2024Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference Heads
- NeurIPS 2024XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
- NeurIPS 2024Zero-Shot Reinforcement Learning from Low Quality Data
- NeurIPS 2024ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
- NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
- NeurIPS 2023$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
- NeurIPS 2023A Definition of Continual Reinforcement Learning
- NeurIPS 2023A Long $N$-step Surrogate Stage Reward for Deep Reinforcement Learning
- NeurIPS 2023A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
- NeurIPS 2023A Partially-Supervised Reinforcement Learning Framework for Visual Active Search
- NeurIPS 2023A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
- NeurIPS 2023A Robust and Opponent-Aware League Training Method for StarCraft II
- NeurIPS 2023A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
- NeurIPS 2023A State Representation for Diminishing Rewards
- NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
- NeurIPS 2023A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning
- NeurIPS 2023A Trichotomy for Transductive Online Learning
- NeurIPS 2023A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process
- NeurIPS 2023Accelerating Exploration with Unlabeled Prior Data
- NeurIPS 2023Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
- NeurIPS 2023Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
- NeurIPS 2023Accelerating Value Iteration with Anchoring
- NeurIPS 2023Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
- NeurIPS 2023Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models
- NeurIPS 2023Active Observing in Continuous-time Control
- NeurIPS 2023Active Vision Reinforcement Learning under Limited Visual Observability
- NeurIPS 2023Adaptive Online Replanning with Diffusion Models
- NeurIPS 2023Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
- NeurIPS 2023Adversarial Counterfactual Environment Model Learning
- NeurIPS 2023Adversarial Model for Offline Reinforcement Learning
- NeurIPS 2023AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation
- NeurIPS 2023Aligning Language Models with Human Preferences via a Bayesian Approach
- NeurIPS 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
- NeurIPS 2023An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
- NeurIPS 2023An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient
- NeurIPS 2023An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
- NeurIPS 2023Anytime-Competitive Reinforcement Learning with Policy Prior
- NeurIPS 2023Arbitrarily Scalable Environment Generators via Neural Cellular Automata
- NeurIPS 2023Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
- NeurIPS 2023AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions
- NeurIPS 2023Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
- NeurIPS 2023Bayesian Learning via Q-Exponential Process
- NeurIPS 2023Bayesian Risk-Averse Q-Learning with Streaming Observations
- NeurIPS 2023BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
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。