通用机器学习 · reinforcement learning论文趋势 2023–2026

主要结论

• 通用机器学习 · reinforcement learning论文从 2023 年的 287 篇增长到 2026 年的 575 篇，三年间扩大到约 2.0 倍。
• ICLR 是发通用机器学习 · reinforcement learning论文最多的会议，2023–2026 年共 847 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 34 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 2；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · reinforcement learning是 2.0 倍。

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 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
• ICML 2026De-attribute to Forget for LLM Unlearning
• ICLR 2026AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
• CVPR 2026Dynamic Important Example Mining for Reinforcement Finetuning
• NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
• ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
• ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
• CVPR 2025Automated Proof of Polynomial Inequalities via Reinforcement Learning
• NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
• ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
• ICLR 2024Bandits with Replenishable Knapsacks: the Best of both Worlds
• CVPR 2024Improving Unsupervised Hierarchical Representation with Reinforcement Learning
• NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
• ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
• ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
• CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
• NeurIPS 2026Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
• ICML 2026Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
• ICLR 2026APPLE: Toward General Active Perception via Reinforcement Learning
• CVPR 2026Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

全部通用机器学习 · reinforcement learning论文

共 411 篇，第 2 / 9 页

51. ICLR 2025Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
52. ICLR 2025Discriminator-Guided Embodied Planning for LLM Agent
53. ICLR 2025Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning
54. ICLR 2025Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL
55. ICLR 2025DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback
56. ICLR 2025Doubly Optimal Policy Evaluation for Reinforcement Learning
57. ICLR 2025Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient
58. ICLR 2025Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment
59. ICLR 2025Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
60. ICLR 2025Efficient Active Imitation Learning with Random Network Distillation
61. ICLR 2025Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning
62. ICLR 2025Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction
63. ICLR 2025Efficient Imitation under Misspecification
64. ICLR 2025Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
65. ICLR 2025Efficient Off-Policy Learning for High-Dimensional Action Spaces
66. ICLR 2025Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
67. ICLR 2025Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning
68. ICLR 2025Efficient Reinforcement Learning with Large Language Model Priors
69. ICLR 2025Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
70. ICLR 2025Energy-Weighted Flow Matching for Offline Reinforcement Learning
71. ICLR 2025Episodic Novelty Through Temporal Distance
72. ICLR 2025Epistemic Monte Carlo Tree Search
73. ICLR 2025eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
74. ICLR 2025Expected Return Symmetries
75. ICLR 2025Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank
76. ICLR 2025Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning
77. ICLR 2025Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies
78. ICLR 2025Feature-Based Online Bilateral Trade
79. ICLR 2025Federated $Q$-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost
80. ICLR 2025Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset
81. ICLR 2025Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment
82. ICLR 2025Flat Reward in Policy Parameter Space Implies Robust Reinforcement Learning
83. ICLR 2025FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning
84. ICLR 2025FOSP: Fine-tuning Offline Safe Policy through World Models
85. ICLR 2025Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
86. ICLR 2025Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
87. ICLR 2025Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects
88. ICLR 2025Global Convergence of Policy Gradient in Average Reward MDPs
89. ICLR 2025Grammar Reinforcement Learning: path and cycle counting in graphs with a Context-Free Grammar and Transformer approach
90. ICLR 2025GROOT-2: Weakly Supervised Multimodal Instruction Following Agents
91. ICLR 2025Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval
92. ICLR 2025Handling Delay in Real-Time Reinforcement Learning
93. ICLR 2025Hierarchical World Models as Visual Whole-Body Humanoid Controllers
94. ICLR 2025Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning
95. ICLR 2025Horizon Generalization in Reinforcement Learning
96. ICLR 2025How to Find the Exact Pareto Front for Multi-Objective MDPs?
97. ICLR 2025INS: Interaction-aware Synthesis to Enhance Offline Multi-agent Reinforcement Learning
98. ICLR 2025Integral Performance Approximation for Continuous-Time Reinforcement Learning Control
99. ICLR 2025Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning
100. ICLR 2025Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · reinforcement learning论文？

共 1,676 篇，按年份分别是 2023 年 287 篇、2024 年 403 篇、2025 年 411 篇、2026 年 575 篇。

NeurIPS 2026 有多少篇通用机器学习 · reinforcement learning论文？

NeurIPS 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 108 篇。

ICLR 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICLR 2026 有 335 篇通用机器学习 · reinforcement learning论文，上一届是 230 篇。

ICML 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICML 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 71 篇。

CVPR 2026 有多少篇通用机器学习 · reinforcement learning论文？

CVPR 2026 有 14 篇通用机器学习 · reinforcement learning论文，上一届是 2 篇。

哪个会议的通用机器学习 · reinforcement learning论文最多？

ICLR，2023–2026 年共 847 篇。