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 784 篇,第 14 / 16 页
- NeurIPS 2025STAR: Efficient Preference-based Reinforcement Learning via Dual Regularization
- NeurIPS 2025State Entropy Regularization for Robust Reinforcement Learning
- NeurIPS 2025State-Covering Trajectory Stitching for Diffusion Planners
- NeurIPS 2025Steering Generative Models with Experimental Data for Protein Fitness Optimization
- NeurIPS 2025STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation
- NeurIPS 2025Stochastic Principal-Agent Problems: Computing and Learning Optimal History-Dependent Policies
- NeurIPS 2025Stop Summation: Min-Form Credit Assignment Is All Process Reward Model Needs for Reasoning
- NeurIPS 2025Strategyproof Reinforcement Learning from Human Feedback
- NeurIPS 2025Structural Information-based Hierarchical Diffusion for Offline Reinforcement Learning
- NeurIPS 2025Structure Matters: Dynamic Policy Gradient
- NeurIPS 2025Structured Reinforcement Learning for Combinatorial Decision-Making
- NeurIPS 2025Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control
- NeurIPS 2025SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models
- NeurIPS 2025SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agents
- NeurIPS 2025SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
- NeurIPS 2025SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning
- NeurIPS 2025SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
- NeurIPS 2025Systematic Reward Gap Optimization for Mitigating VLM Hallucinations
- NeurIPS 2025T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT
- NeurIPS 2025Table2LaTeX-RL: High-Fidelity LaTeX Code Generation from Table Images via Reinforced Multimodal Language Models
- NeurIPS 2025Tackling Continual Offline RL through Selective Weights Activation on Aligned Spaces
- NeurIPS 2025Tapered Off-Policy REINFORCE - Stable and efficient reinforcement learning for large language models
- NeurIPS 2025Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignment
- NeurIPS 2025Teaching Language Models to Reason with Tools
- NeurIPS 2025Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving
- NeurIPS 2025Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following
- NeurIPS 2025Temporal-Difference Variational Continual Learning
- NeurIPS 2025TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning for Video LLMs
- NeurIPS 2025TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture search
- NeurIPS 2025Test-Time Scaling of Diffusion Models via Noise Trajectory Search
- NeurIPS 2025Text-to-Decision Agent: Offline Meta-Reinforcement Learning from Natural Language Supervision
- NeurIPS 2025The Overthinker's DIET: Cutting Token Calories with DIfficulty-AwarE Training
- NeurIPS 2025The Promise of RL for Autoregressive Image Editing
- NeurIPS 2025The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning
- NeurIPS 2025The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
- NeurIPS 2025The World Is Bigger: A Computationally-Embedded Perspective on the Big World Hypothesis
- NeurIPS 2025Think before Recommendation: Autonomous Reasoning-enhanced Recommender
- NeurIPS 2025Think Only When You Need with Large Hybrid-Reasoning Models
- NeurIPS 2025Think or Not? Selective Reasoning via Reinforcement Learning for Vision-Language Models
- NeurIPS 2025Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains
- NeurIPS 2025Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models
- NeurIPS 2025Thinker: Learning to Think Fast and Slow
- NeurIPS 2025Thinking vs. Doing: Improving Agent Reasoning by Scaling Test-Time Interaction
- NeurIPS 2025Thinkless: LLM Learns When to Think
- NeurIPS 2025Time Reversal Symmetry for Efficient Robotic Manipulations in Deep Reinforcement Learning
- NeurIPS 2025Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
- NeurIPS 2025To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable RL
- NeurIPS 2025To Think or Not To Think: A Study of Thinking in Rule-Based Visual Reinforcement Fine-Tuning
- NeurIPS 2025ToolRL: Reward is All Tool Learning Needs
- NeurIPS 2025Touch in the Wild: Learning Fine-Grained Manipulation with a Portable Visuo-Tactile Gripper
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。