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 1,676 篇，第 2 / 34 页

51. ICLR 2026Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning
52. ICLR 2026Beyond Softmax and Entropy: Convergence Rates of Policy Gradients with $\boldsymbol{f}$-SoftArgmax Parameterization $\&$ Coupled Regularization
53. ICLR 2026Breaking Barriers: Do Reinforcement Fine-tuning Gains Transfer To Unseen Domains?
54. ICLR 2026Breaking Safety Paradox with Feasible Dual Policy Iteration
55. ICLR 2026Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set
56. ICLR 2026BRIDGE: Bi-level Reinforcement Learning for Dynamic Group Structure in Coalition Formation Games
57. ICLR 2026Bridging Successor Measure and Online Policy Learning with Flow Matching-Based Representations
58. ICLR 2026Bridging the performance-gap between target-free and target-based reinforcement learning
59. ICLR 2026CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
60. ICLR 2026Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
61. ICLR 2026CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
62. ICLR 2026CE-Nav: Flow-Guided Reinforcement Refinement for Cross-Embodiment Local Navigation
63. ICLR 2026Chunking the Critic: A Transformer-based Soft Actor-Critic with N-Step Returns
64. ICLR 2026Code Driven Planning with Domain-Adaptive Selector
65. ICLR 2026Combinatorial Rising Bandits
66. ICLR 2026ContextIF: Enhancing Instruction-Following through Context Reward
67. ICLR 2026Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
68. ICLR 2026Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
69. ICLR 2026Convergence of an actor-critic gradient flow for entropy regularised MDPs in general spaces
70. ICLR 2026ConvRec-R1: Training LLM-based Conversational Recommender Systems with Reinforcement Learning
71. ICLR 2026Correlated Policy Optimization in Multi-Agent Subteams
72. ICLR 2026Critique-Coder: Enhancing Coder Models by Critique Reinforcement Learning
73. ICLR 2026Cross-Domain Policy Optimization via Bellman Consistency and Hybrid Critics
74. ICLR 2026Cross-Embodied Co-Design for Dexterous Hands
75. ICLR 2026Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets
76. ICLR 2026Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
77. ICLR 2026DEAS: DEtached value learning with Action Sequence for Scalable Offline RL
78. ICLR 2026Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner
79. ICLR 2026Decoupled Q-Chunking
80. ICLR 2026Deep SPI: Safe Policy Improvement via World Models
81. ICLR 2026DeepCompress: A Dual Reward Strategy for Dynamically Exploring and Compressing Reasoning Chains
82. ICLR 2026Demystifying Emergent Exploration in Goal-Conditioned RL
83. ICLR 2026DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
84. ICLR 2026Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
85. ICLR 2026Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
86. ICLR 2026Dichotomous Diffusion Policy Optimization
87. ICLR 2026Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach
88. ICLR 2026Discovering Diverse Behaviors via Temporal Contrastive Learning
89. ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
90. ICLR 2026Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
91. ICLR 2026Distributional value gradients for stochastic environments
92. ICLR 2026Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization
93. ICLR 2026Distributions as Actions: A Unified Framework for Diverse Action Spaces
94. ICLR 2026Diversity-Aware Online Prompt Assignment to Generative Models
95. ICLR 2026Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?
96. ICLR 2026DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
97. ICLR 2026DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
98. ICLR 2026Dual Goal Representations
99. ICLR 2026Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
100. ICLR 2026Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts

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。