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 3 / 16 页
- NeurIPS 2025Coarse-to-fine Q-Network with Action Sequence for Data-Efficient Reinforcement Learning
- NeurIPS 2025COGNAC: Cooperative Graph-based Networked Agent Challenges for Multi-Agent Reinforcement Learning
- NeurIPS 2025Cognitive Predictive Processing: A Human-inspired Framework for Adaptive Exploration in Open-World Reinforcement Learning
- NeurIPS 2025COLA: Towards Efficient Multi-Objective Reinforcement Learning with Conflict Objective Regularization in Latent Space
- NeurIPS 2025Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning
- NeurIPS 2025Complexity Scaling Laws for Neural Models using Combinatorial Optimization
- NeurIPS 2025Composing Linear Layers from Irreducibles
- NeurIPS 2025Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
- NeurIPS 2025Compositional Monte Carlo Tree Diffusion for Extendable Planning
- NeurIPS 2025Computational Hardness of Reinforcement Learning with Partial $q^{\pi}$-Realizability
- NeurIPS 2025Compute-Optimal Scaling for Value-Based Deep RL
- NeurIPS 2025Conditioning Matters: Training Diffusion Policies is Faster Than You Think
- NeurIPS 2025Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation
- NeurIPS 2025Confounding Robust Deep Reinforcement Learning: A Causal Approach
- NeurIPS 2025Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning
- NeurIPS 2025Consistently Simulating Human Personas with Multi-Turn Reinforcement Learning
- NeurIPS 2025Constrained Best Arm Identification
- NeurIPS 2025Constrained Optimization From a Control Perspective via Feedback Linearization
- NeurIPS 2025Constructing an Optimal Behavior Basis for the Option Keyboard
- NeurIPS 2025Contextual Integrity in LLMs via Reasoning and Reinforcement Learning
- NeurIPS 2025Contextual Online Pricing with (Biased) Offline Data
- NeurIPS 2025Continual Knowledge Adaptation for Reinforcement Learning
- NeurIPS 2025Continuous Q-Score Matching: Diffusion Guided Reinforcement Learning for Continuous-Time Control
- NeurIPS 2025Continuous Soft Actor-Critic: An Off-Policy Learning Method Robust to Time Discretization
- NeurIPS 2025Convergence Theorems for Entropy-Regularized and Distributional Reinforcement Learning
- NeurIPS 2025Convergent Functions, Divergent Forms
- NeurIPS 2025CORE: Collaborative Optimization with Reinforcement Learning and Evolutionary Algorithm for Floorplanning
- NeurIPS 2025Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning
- NeurIPS 2025CPPO: Accelerating the Training of Group Relative Policy Optimization-Based Reasoning Models
- NeurIPS 2025CReFT-CAD: Boosting Orthographic Projection Reasoning for CAD via Reinforcement Fine-Tuning
- NeurIPS 2025Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RL
- NeurIPS 2025CURE: Co-Evolving Coders and Unit Testers via Reinforcement Learning
- NeurIPS 2025Curriculum Design for Trajectory-Constrained Agent: Compressing Chain-of-Thought Tokens in LLMs
- NeurIPS 2025CURV: Coherent Uncertainty-Aware Reasoning in Vision-Language Models for X-Ray Report Generation
- NeurIPS 2025Curvature Tuning: Provable Training-free Model Steering From a Single Parameter
- NeurIPS 2025Cypher-RI: Reinforcement Learning for Integrating Schema Selection into Cypher Generation
- NeurIPS 2025d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning
- NeurIPS 2025DAIL: Beyond Task Ambiguity for Language-Conditioned Reinforcement Learning
- NeurIPS 2025DAPO : Improving Multi-Step Reasoning Abilities of Large Language Models with Direct Advantage-Based Policy Optimization
- NeurIPS 2025DAPO: An Open-Source LLM Reinforcement Learning System at Scale
- NeurIPS 2025DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
- NeurIPS 2025DEAL: Diffusion Evolution Adversarial Learning for Sim-to-Real Transfer
- NeurIPS 2025Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generation
- NeurIPS 2025Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environments
- NeurIPS 2025DeepDiver: Adaptive Web-Search Intensity Scaling via Reinforcement Learning
- NeurIPS 2025DeepVideo-R1: Video Reinforcement Fine-Tuning via Difficulty-aware Regressive GRPO
- NeurIPS 2025Delving into RL for Image Generation with CoT: A Study on DPO vs. GRPO
- NeurIPS 2025Deployment Efficient Reward-Free Exploration with Linear Function Approximation
- NeurIPS 2025DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
- NeurIPS 2025DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation
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。