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 1,070 篇，第 15 / 22 页

701. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
702. NeurIPS 2023Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
703. NeurIPS 2023Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
704. NeurIPS 2023Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
705. NeurIPS 2023Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning
706. NeurIPS 2023Diversify \& Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement
707. NeurIPS 2023Domain Adaptive Imitation Learning with Visual Observation
708. NeurIPS 2023Double Gumbel Q-Learning
709. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
710. NeurIPS 2023Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
711. NeurIPS 2023DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
712. NeurIPS 2023Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL
713. NeurIPS 2023DynaDojo: An Extensible Benchmarking Platform for Scalable Dynamical System Identification
714. NeurIPS 2023Dynamic Regret of Adversarial Linear Mixture MDPs
715. NeurIPS 2023Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
716. NeurIPS 2023Easy Learning from Label Proportions
717. NeurIPS 2023Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
718. NeurIPS 2023Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning
719. NeurIPS 2023Efficient Diffusion Policies For Offline Reinforcement Learning
720. NeurIPS 2023Efficient Exploration in Continuous-time Model-based Reinforcement Learning
721. NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
722. NeurIPS 2023Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization
723. NeurIPS 2023Efficient Model-Free Exploration in Low-Rank MDPs
724. NeurIPS 2023Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
725. NeurIPS 2023Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric
726. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
727. NeurIPS 2023Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
728. NeurIPS 2023Elastic Decision Transformer
729. NeurIPS 2023ELDEN: Exploration via Local Dependencies
730. NeurIPS 2023Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback
731. NeurIPS 2023End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
732. NeurIPS 2023Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
733. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
734. NeurIPS 2023Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
735. NeurIPS 2023Explore to Generalize in Zero-Shot RL
736. NeurIPS 2023Exponential Lower Bounds for Fictitious Play in Potential Games
737. NeurIPS 2023Extracting Reward Functions from Diffusion Models
738. NeurIPS 2023f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences
739. NeurIPS 2023Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network
740. NeurIPS 2023Facing Off World Model Backbones: RNNs, Transformers, and S4
741. NeurIPS 2023FAMO: Fast Adaptive Multitask Optimization
742. NeurIPS 2023Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
743. NeurIPS 2023Feature Learning for Interpretable, Performant Decision Trees
744. NeurIPS 2023Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
745. NeurIPS 2023Finding Safe Zones of Markov Decision Processes Policies
746. NeurIPS 2023Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
747. NeurIPS 2023Finite-Time Analysis of Single-Timescale Actor-Critic
748. NeurIPS 2023First- and Second-Order Bounds for Adversarial Linear Contextual Bandits
749. NeurIPS 2023Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs
750. NeurIPS 2023Flexible Attention-Based Multi-Policy Fusion for Efficient Deep 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。