强化学习论文趋势 2023–2026

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。

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 1,190 篇，第 17 / 24 页

801. NeurIPS 2024CooHOI: Learning Cooperative Human-Object Interaction with Manipulated Object Dynamics
802. NeurIPS 2024Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification
803. NeurIPS 2024DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation
804. NeurIPS 2024Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL
805. NeurIPS 2024Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling
806. NeurIPS 2024Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization
807. NeurIPS 2024Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
808. NeurIPS 2024Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems
809. NeurIPS 2024Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time
810. NeurIPS 2024Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
811. NeurIPS 2024Differentiable Quantum Computing for Large-scale Linear Control
812. NeurIPS 2024Differentially Private Reinforcement Learning with Self-Play
813. NeurIPS 2024DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data
814. NeurIPS 2024DiffPhyCon: A Generative Approach to Control Complex Physical Systems
815. NeurIPS 2024DiffTORI: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning
816. NeurIPS 2024DiffuserLite: Towards Real-time Diffusion Planning
817. NeurIPS 2024Diffusion Actor-Critic with Entropy Regulator
818. NeurIPS 2024Diffusion for World Modeling: Visual Details Matter in Atari
819. NeurIPS 2024Diffusion Imitation from Observation
820. NeurIPS 2024Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning
821. NeurIPS 2024Diffusion Spectral Representation for Reinforcement Learning
822. NeurIPS 2024Diffusion-based Curriculum Reinforcement Learning
823. NeurIPS 2024Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
824. NeurIPS 2024Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
825. NeurIPS 2024Diffusion-Reward Adversarial Imitation Learning
826. NeurIPS 2024DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
827. NeurIPS 2024Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration
828. NeurIPS 2024Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning
829. NeurIPS 2024Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation
830. NeurIPS 2024Distributional Reinforcement Learning with Regularized Wasserstein Loss
831. NeurIPS 2024Distributional Successor Features Enable Zero-Shot Policy Optimization
832. NeurIPS 2024Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
833. NeurIPS 2024Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners
834. NeurIPS 2024DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
835. NeurIPS 2024Do LLMs Build World Representations? Probing Through the Lens of State Abstraction
836. NeurIPS 2024Do's and Don'ts: Learning Desirable Skills with Instruction Videos
837. NeurIPS 2024dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans
838. NeurIPS 2024Doubly Mild Generalization for Offline Reinforcement Learning
839. NeurIPS 2024Dual Critic Reinforcement Learning under Partial Observability
840. NeurIPS 2024Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning
841. NeurIPS 2024Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron
842. NeurIPS 2024DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
843. NeurIPS 2024e-COP : Episodic Constrained Optimization of Policies
844. NeurIPS 2024E-Motion: Future Motion Simulation via Event Sequence Diffusion
845. NeurIPS 2024EASI: Evolutionary Adversarial Simulator Identification for Sim-to-Real Transfer
846. NeurIPS 2024Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision
847. NeurIPS 2024Effective Exploration Based on the Structural Information Principles
848. NeurIPS 2024Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes
849. NeurIPS 2024Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
850. NeurIPS 2024Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance

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。