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 847 篇，第 2 / 17 页

51. ICLR 2026Combinatorial Rising Bandits
52. ICLR 2026ContextIF: Enhancing Instruction-Following through Context Reward
53. ICLR 2026Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
54. ICLR 2026Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
55. ICLR 2026Convergence of an actor-critic gradient flow for entropy regularised MDPs in general spaces
56. ICLR 2026ConvRec-R1: Training LLM-based Conversational Recommender Systems with Reinforcement Learning
57. ICLR 2026Correlated Policy Optimization in Multi-Agent Subteams
58. ICLR 2026Critique-Coder: Enhancing Coder Models by Critique Reinforcement Learning
59. ICLR 2026Cross-Domain Policy Optimization via Bellman Consistency and Hybrid Critics
60. ICLR 2026Cross-Embodied Co-Design for Dexterous Hands
61. ICLR 2026Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets
62. ICLR 2026Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
63. ICLR 2026DEAS: DEtached value learning with Action Sequence for Scalable Offline RL
64. ICLR 2026Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner
65. ICLR 2026Decoupled Q-Chunking
66. ICLR 2026Deep SPI: Safe Policy Improvement via World Models
67. ICLR 2026DeepCompress: A Dual Reward Strategy for Dynamically Exploring and Compressing Reasoning Chains
68. ICLR 2026Demystifying Emergent Exploration in Goal-Conditioned RL
69. ICLR 2026DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
70. ICLR 2026Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
71. ICLR 2026Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
72. ICLR 2026Dichotomous Diffusion Policy Optimization
73. ICLR 2026Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach
74. ICLR 2026Discovering Diverse Behaviors via Temporal Contrastive Learning
75. ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
76. ICLR 2026Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
77. ICLR 2026Distributional value gradients for stochastic environments
78. ICLR 2026Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization
79. ICLR 2026Distributions as Actions: A Unified Framework for Diverse Action Spaces
80. ICLR 2026Diversity-Aware Online Prompt Assignment to Generative Models
81. ICLR 2026Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?
82. ICLR 2026DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
83. ICLR 2026DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
84. ICLR 2026Dual Goal Representations
85. ICLR 2026Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
86. ICLR 2026Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts
87. ICLR 2026Efficient Morphology–Control Co-Design via Stackelberg PPO under Non-Differentiable Leader–Follower Interfaces
88. ICLR 2026Efficient Offline Reinforcement Learning via Peer-Influenced Constraint
89. ICLR 2026Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data
90. ICLR 2026Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL
91. ICLR 2026ELMUR: External Layer Memory with Update/Rewrite for Long-Horizon RL
92. ICLR 2026EMFuse: Energy-based Model Fusion for Decision Making
93. ICLR 2026Enhancing Geometric Perception in VLMs via Translator-Guided Reinforcement Learning
94. ICLR 2026Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs
95. ICLR 2026Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints
96. ICLR 2026Entropy-preserving reinforcement learning
97. ICLR 2026EUBRL: Epistemic Uncertainty Directed Bayesian Reinforcement Learning
98. ICLR 2026Exploratory Diffusion Model for Unsupervised Reinforcement Learning
99. ICLR 2026Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization
100. ICLR 2026EXPO: Stable Reinforcement Learning with Expressive Policies

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。