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 2,079 篇,第 16 / 42 页
- ICML 2026Reward Shaping Control Variates for Off-Policy Evaluation Under Sparse Rewards
- ICML 2026Reward-Preserving Counterfactual State Editing for Offline Reinforcement Learning
- ICML 2026RiskZero: Plan More to Risk Less with a Learned Model
- ICML 2026RL with Learnable Textual Feedback: A Bilevel Approach
- ICML 2026RL-SPH: Learning to Achieve Feasible Solutions for Integer Linear Programs
- ICML 2026RL4RLA: Teaching ML to Discover Randomized Linear Algebra Algorithms Through Curriculum Design and Graph-Based Search
- ICML 2026RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System
- ICML 2026RLCracker: Evaluating the Worst-Case Vulnerability of LLM Watermarks with Adaptive RL Attacks
- ICML 2026RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
- ICML 2026RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning
- ICML 2026Robust Contextual Optimization with Missing Covariates
- ICML 2026Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks
- ICML 2026Robust Sequential Experimental Design for A/B Testing
- ICML 2026Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
- ICML 2026Role-Level Inductive Bias for Cross-Task Generalization in Multi-Agent Reinforcement Learning
- ICML 2026RSAgent: Learning to Reason and Act via Multi-Turn Tool Invocations for Text-Guided Segmentation
- ICML 2026Rubric Curriculum RL: Exploiting the Generation-Verification Gap in Non-Verifiable Domains
- ICML 2026RuCL: Stratified Rubric-Based Curriculum Learning for Multimodal Large Language Model Reasoning
- ICML 2026RulePlanner: All-in-One Reinforcement Learner for Unifying Design Rules in 3D Floorplanning
- ICML 2026Safe In-Context Reinforcement Learning
- ICML 2026Safe Reinforcement Learning with Preference-based Constraint Inference
- ICML 2026Safety Alignment of LMs via Non-cooperative Games
- ICML 2026Safety Game: Inference-Time Alignment of Black-Box LLMs via Constrained Optimization
- ICML 2026Safety Generalization Under Distribution Shift in Safe Reinforcement Learning: A Diabetes Testbed
- ICML 2026Safety Recovery in Reasoning Models Is Only a Few Early Steering Steps Away
- ICML 2026SAGE: Shaping Anchors for Guided Exploration in RLVR of LLMs
- ICML 2026Salus: Strategic Diagnostic Testing for Complex Diagnosis via Multi-Agent Reinforcement Learning
- ICML 2026Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance
- ICML 2026SARL: Structure-Aligned Reinforcement Learning for Bridging the Perception-Action Gap in Airspace
- ICML 2026Scalable and General Whole-Body Control for Cross-Humanoid Locomotion
- ICML 2026Scalable Option Learning in High-Throughput Environments
- ICML 2026Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening
- ICML 2026Scalable Reinforcement Learning via Adaptive Batch Scaling
- ICML 2026Scalable Traffic Signal Control with Shared Policy Framework
- ICML 2026ScaleMoE: Mixture-of-Experts for Scalable Continuous Control in Actor-Critic Reinforcement Learning
- ICML 2026Scaling Agentic Verifier for Competitive Coding
- ICML 2026Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection
- ICML 2026Scaling Long-Horizon Agent via Context Folding
- ICML 2026Scaling Multi-Agent Environment Co-Design with Diffusion Models
- ICML 2026Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning
- ICML 2026Scaling up Multi-Turn Off-Policy RL and Multi-Agent Tree Search for LLM Step-Provers
- ICML 2026Scaling, Benchmarking, and Reasoning of Vision-Language Agents for Mobile GUI Navigation
- ICML 2026ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving
- ICML 2026Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models
- ICML 2026SCOPE: Selective Conformal Optimized Pairwise LLM Judging
- ICML 2026Search-R2: Enhancing Search-Integrated Reasoning via Actor-Refiner Collaboration
- ICML 2026Second-Order Smooth Planning with Optimal-Transport Bellman Smoothing
- ICML 2026Secure Multi-agent Reinforcement Learning for Service Systems with Affinity and Byzantine Nodes: Stability Analysis and Protection Design
- ICML 2026See First, Reason Later: Mutual Information-Guided Reinforcement Learning for Vision-Language Models
- ICML 2026See, Act, Adapt: Active Perception for Unsupervised Cross-Domain Visual Adaptation via Personalized VLM-Guided Agent
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。