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 36 篇，第 1 / 1 页

1. ICLR 2023A new characterization of the edge of stability based on a sharpness measure aware of batch gradient distribution
2. ICLR 2023Agree to Disagree: Diversity through Disagreement for Better Transferability
3. ICLR 2023ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
4. ICLR 2023Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models
5. ICLR 2023Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
6. ICLR 2023Causal Balancing for Domain Generalization
7. ICLR 2023Compositional Semantic Parsing with Large Language Models
8. ICLR 2023Compositionality with Variation Reliably Emerges in Neural Networks
9. ICLR 2023Cycle-consistent Masked AutoEncoder for Unsupervised Domain Generalization
10. ICLR 2023Data Valuation Without Training of a Model
11. ICLR 2023Dataset Pruning: Reducing Training Data by Examining Generalization Influence
12. ICLR 2023Disentanglement of Correlated Factors via Hausdorff Factorized Support
13. ICLR 2023Disentangling the Mechanisms Behind Implicit Regularization in SGD
14. ICLR 2023Domain Generalization via Heckman-type Selection Models
15. ICLR 2023Exponential Generalization Bounds with Near-Optimal Rates for $L_q$-Stable Algorithms
16. ICLR 2023FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy
17. ICLR 2023GAIN: On the Generalization of Instructional Action Understanding
18. ICLR 2023Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement
19. ICLR 2023Improving Out-of-distribution Generalization with Indirection Representations
20. ICLR 2023Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
21. ICLR 2023Leveraging Unlabeled Data to Track Memorization
22. ICLR 2023Linear Connectivity Reveals Generalization Strategies
23. ICLR 2023Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent
24. ICLR 2023Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence
25. ICLR 2023Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
26. ICLR 2023No Reason for No Supervision: Improved Generalization in Supervised Models
27. ICLR 2023On The Specialization of Neural Modules
28. ICLR 2023Over-Training with Mixup May Hurt Generalization
29. ICLR 2023PGrad: Learning Principal Gradients For Domain Generalization
30. ICLR 2023Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process
31. ICLR 2023SIMPLE: Specialized Model-Sample Matching for Domain Generalization
32. ICLR 2023Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
33. ICLR 2023Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks
34. ICLR 2023Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning
35. ICLR 2023Towards the Generalization of Contrastive Self-Supervised Learning
36. ICLR 2023Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization

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。