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 174 篇，第 1 / 4 页

1. ICML 2026Anti-causal domain generalization: Leveraging unlabeled data
2. ICML 2026Are Object-Centric Representations Better at Compositional Generalization?
3. ICML 2026Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets
4. ICML 2026CoGe-GCD: Reframing Generalized Category Discovery with Compositional Generalization
5. ICML 2026Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models
6. ICML 2026Continual Learning of Domain-Invariant Representations
7. ICML 2026Contrastive Weak-to-Strong Generalization
8. ICML 2026CURE: Context-driven Diffusion with Progressive Expansion for Single Domain Generalization in Time Series Classification
9. ICML 2026DomED: Redesigning Ensemble Distillation for Domain Generalization
10. ICML 2026Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
11. ICML 2026Fix the Loss, Not the Radius: Rethinking the Adversarial Perturbation of Sharpness-Aware Minimization
12. ICML 2026From Distribution to Geometry: Stable Graph Generalization via Invariant Barycenters
13. ICML 2026Generalization Bounds for Discrete Diffusion: Statistical Advantage of Masking
14. ICML 2026Generalization Bounds for Out-of-distribution Generalization
15. ICML 2026Geometric Rate–Distortion Invariance for Domain Generalization
16. ICML 2026Grokking Finite-Dimensional Algebra
17. ICML 2026Harmful Overfitting in Sobolev Spaces
18. ICML 2026How can embedding models bind concepts?
19. ICML 2026Improved Scaling Laws via Weak-to-Strong Generalization in Random Features Ridge Regression
20. ICML 2026Inconsistency-Aware Minimization: Improving Generalization with Unlabeled Data
21. ICML 2026Intrinsic Task Symmetry Drives Generalization in Algorithmic Tasks
22. ICML 2026Is Generation Required for Data-Efficient Perception?
23. ICML 2026Length Generalization Bounds for Transformers
24. ICML 2026Local Intrinsic Dimension of Representations Predicts Alignment and Generalization in AI Models and Human Brain
25. ICML 2026MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization
26. ICML 2026Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains
27. ICML 2026Over-Alignment vs Over-Fitting: The Role of Feature Learning Strength in Generalization
28. ICML 2026Positive-Unlabeled Learning with Extreme Scarcity of Labeled Positives
29. ICML 2026Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
30. ICML 2026Quantifying the Generalization Gap in Seizure Detection: A Large-Scale Empirical Benchmark via the SzCORE Challenge
31. ICML 2026Relational Structural Causal Models
32. ICML 2026Revisiting OOD Generalization in Programmatic RL
33. ICML 2026Revisiting the Role of Pretrained Weights in Model Merging: On Near-Optimality within the Core Subspace
34. ICML 2026Semi-Supervised Learning with Noisy Proxy Covariates: Generalization Bounds and Distribution Regression
35. ICML 2026Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments
36. ICML 2026Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs
37. ICML 2026Symmetries in PAC-Bayesian Learning
38. ICML 2026The Illusion of Generalization in Tabular Language Models
39. ICML 2026Tight Margin-Based Generalization Bounds for Voting Classifiers over Finite Hypothesis Sets
40. ICML 2026Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning
41. ICML 2026TRACER: Persistent Regularization for Robust Multimodal Finetuning
42. ICML 2026Trust Functions: Near Lossless Weak-to-Strong Generalization by Learning to Trust the Weak Teacher
43. ICML 2026Tucker Attention: A generalization of approximate attention mechanisms
44. ICML 2026Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
45. ICML 2026URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
46. ICML 2026Weak-to-Strong Generalization via Bregman Bias–Variance Decomposition
47. ICML 2026Which Algorithms Can Graph Neural Networks Learn?
48. ICML 2025A Generalization Result for Convergence in Learning-to-Optimize
49. ICML 2025A Manifold Perspective on the Statistical Generalization of Graph Neural Networks
50. ICML 2025A Meta-learner for Heterogeneous Effects in Difference-in-Differences

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。