通用机器学习 · generalization论文趋势 2023–2026

主要结论

• 通用机器学习 · generalization论文从 2023 年的 136 篇增长到 2026 年的 152 篇，三年间扩大到约 1.1 倍。
• NeurIPS 是发通用机器学习 · generalization论文最多的会议，2023–2026 年共 207 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是理论 · learning theory：同时属于两个主题的论文从 2023 年的 3 篇增至 2026 年的 20 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 5；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · generalization是 1.1 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 2026Asymmetric Generalization in Deep CTR Models: A Block-wise Diagnosis
• ICML 2026Anti-causal domain generalization: Leveraging unlabeled data
• ICLR 2026Generalization Below the Edge of Stability: The Role of Data Geometry
• CVPR 2026PriVi Towards a General-Purpose Video Model for Primate Behavior in
• NeurIPS 2025Automatic Visual Instrumental Variable Learning for Confounding-Resistant Domain Generalization
• ICML 2025Causality Inspired Federated Learning for OOD Generalization
• ICLR 2025Federated Domain Generalization with Data-free On-server Matching Gradient
• CVPR 2025Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
• NeurIPS 2024Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
• ICML 2024Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
• ICLR 2024Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
• CVPR 2024Disentangled Prompt Representation for Domain Generalization
• NeurIPS 2023A unified framework for information-theoretic generalization bounds
• ICML 2023Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
• ICLR 2023ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
• CVPR 2023AltFreezing for More General Video Face Forgery Detection
• NeurIPS 2026Beyond Average Flatness: Domain-wise Flatness for Domain Generalization
• ICML 2026Are Object-Centric Representations Better at Compositional Generalization?
• ICLR 2026Temporal Generalization: A Reality Check
• CVPR 2026The Golden Subspace Where Efficiency Meets Generalization in Continual Test-Time

全部通用机器学习 · generalization论文

共 207 篇，第 3 / 5 页

101. NeurIPS 2025Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification
102. NeurIPS 2025Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
103. NeurIPS 2025Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization
104. NeurIPS 2025Rethinking Out-of-Distribution Detection and Generalization with Collective Behavior Dynamics
105. NeurIPS 2025Revisiting Bi-Linear State Transitions in Recurrent Neural Networks
106. NeurIPS 2025Scaling can lead to compositional generalization
107. NeurIPS 2025Self-Training with Dynamic Weighting for Robust Gradual Domain Adaptation
108. NeurIPS 2025Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon
109. NeurIPS 2025Subsampled Ensemble Can Improve Generalization Tail Exponentially
110. NeurIPS 2025The $\varphi$ Curve: The Shape of Generalization through the Lens of Norm-based Capacity Control
111. NeurIPS 2025Tight Generalization Bounds for Large-Margin Halfspaces
112. NeurIPS 2025Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
113. NeurIPS 2025Uncertainty Estimation by Flexible Evidential Deep Learning
114. NeurIPS 2025Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks
115. NeurIPS 2025Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training
116. NeurIPS 2025Weak-to-Strong Generalization under Distribution Shifts
117. NeurIPS 2025What Can RL Bring to VLA Generalization? An Empirical Study
118. NeurIPS 2025When Models Don’t Collapse: On the Consistency of Iterative MLE
119. NeurIPS 2025Which Algorithms Have Tight Generalization Bounds?
120. NeurIPS 2024A Kernel Perspective on Distillation-based Collaborative Learning
121. NeurIPS 2024A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations
122. NeurIPS 2024A Universal Growth Rate for Learning with Smooth Surrogate Losses
123. NeurIPS 2024Achievable distributional robustness when the robust risk is only partially identified
124. NeurIPS 2024Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
125. NeurIPS 2024Aligning to Thousands of Preferences via System Message Generalization
126. NeurIPS 2024An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models
127. NeurIPS 2024Back to the Continuous Attractor
128. NeurIPS 2024Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
129. NeurIPS 2024Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
130. NeurIPS 2024Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
131. NeurIPS 2024Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
132. NeurIPS 2024Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
133. NeurIPS 2024Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
134. NeurIPS 2024Continuous Temporal Domain Generalization
135. NeurIPS 2024DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity
136. NeurIPS 2024Dissecting the Failure of Invariant Learning on Graphs
137. NeurIPS 2024Doubly Mild Generalization for Offline Reinforcement Learning
138. NeurIPS 2024Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets
139. NeurIPS 2024Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
140. NeurIPS 2024Focus On What Matters: Separated Models For Visual-Based RL Generalization
141. NeurIPS 2024Generalizablity of Memorization Neural Network
142. NeurIPS 2024Generalization Analysis for Label-Specific Representation Learning
143. NeurIPS 2024Generalization Bounds via Conditional $f$-Information
144. NeurIPS 2024Generalization of Hamiltonian algorithms
145. NeurIPS 2024Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
146. NeurIPS 2024In-Context Learning with Representations: Contextual Generalization of Trained Transformers
147. NeurIPS 2024Information-theoretic Generalization Analysis for Expected Calibration Error
148. NeurIPS 2024Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
149. NeurIPS 2024LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
150. NeurIPS 2024Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization

常见问题

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

共 592 篇，按年份分别是 2023 年 136 篇、2024 年 135 篇、2025 年 169 篇、2026 年 152 篇。

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

NeurIPS 2026 有 58 篇通用机器学习 · generalization论文，上一届是 61 篇。

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

ICLR 2026 有 38 篇通用机器学习 · generalization论文，上一届是 33 篇。

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

ICML 2026 有 47 篇通用机器学习 · generalization论文，上一届是 61 篇。

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

CVPR 2026 有 9 篇通用机器学习 · generalization论文，上一届是 14 篇。

哪个会议的通用机器学习 · generalization论文最多？

NeurIPS，2023–2026 年共 207 篇。