General ML · generalization papers, 2023–2026

Key findings

• General ML · generalization went from 136 papers in 2023 to 152 in 2026, roughly 1.1x in three years.
• NeurIPS publishes the most General ML · generalization work: 207 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Theory · learning theory: papers tagged with both rose from 3 in 2023 to 20 in 2026.
• Among the 6 topics under General Machine Learning, it ranks #5 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 1.1x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All General ML · generalization papers

42 papers, page 1 of 1

1. NeurIPS 2023A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
2. NeurIPS 2023A unified framework for information-theoretic generalization bounds
3. NeurIPS 2023A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning
4. NeurIPS 2023An Iterative Self-Learning Framework for Medical Domain Generalization
5. NeurIPS 2023Analyzing Generalization of Neural Networks through Loss Path Kernels
6. NeurIPS 2023Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization
7. NeurIPS 2023Approximately Equivariant Graph Networks
8. NeurIPS 2023Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
9. NeurIPS 2023Balancing memorization and generalization in RNNs for high performance brain-machine Interfaces
10. NeurIPS 2023Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
11. NeurIPS 2023Compositional Generalization from First Principles
12. NeurIPS 2023Data Augmentations for Improved (Large) Language Model Generalization
13. NeurIPS 2023Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
14. NeurIPS 2023Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss
15. NeurIPS 2023Evolving Standardization for Continual Domain Generalization over Temporal Drift
16. NeurIPS 2023GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
17. NeurIPS 2023Learning Generalizable Agents via Saliency-guided Features Decorrelation
18. NeurIPS 2023Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
19. NeurIPS 2023Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head
20. NeurIPS 2023Learning Trajectories are Generalization Indicators
21. NeurIPS 2023MADG: Margin-based Adversarial Learning for Domain Generalization
22. NeurIPS 2023Near-optimal learning with average Hölder smoothness
23. NeurIPS 2023Networks are Slacking Off: Understanding Generalization Problem in Image Deraining
24. NeurIPS 2023Normalization Layers Are All That Sharpness-Aware Minimization Needs
25. NeurIPS 2023On Certified Generalization in Structured Prediction
26. NeurIPS 2023On Generalization Bounds for Projective Clustering
27. NeurIPS 2023On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay
28. NeurIPS 2023On the Importance of Exploration for Generalization in Reinforcement Learning
29. NeurIPS 2023PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction
30. NeurIPS 2023PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization
31. NeurIPS 2023Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability
32. NeurIPS 2023Residual Alignment: Uncovering the Mechanisms of Residual Networks
33. NeurIPS 2023Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds
34. NeurIPS 2023Secure Out-of-Distribution Task Generalization with Energy-Based Models
35. NeurIPS 2023Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
36. NeurIPS 2023The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
37. NeurIPS 2023Tight Risk Bounds for Gradient Descent on Separable Data
38. NeurIPS 2023Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms
39. NeurIPS 2023Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach
40. NeurIPS 2023Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
41. NeurIPS 2023Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
42. NeurIPS 2023Understanding and Improving Feature Learning for Out-of-Distribution Generalization

FAQ

How many General ML · generalization papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

592 in total: 136 in 2023, 135 in 2024, 169 in 2025, 152 in 2026.

How many General ML · generalization papers are at NeurIPS 2026?

NeurIPS 2026 has 58 General ML · generalization papers, versus 61 the year before.

How many General ML · generalization papers are at ICLR 2026?

ICLR 2026 has 38 General ML · generalization papers, versus 33 the year before.

How many General ML · generalization papers are at ICML 2026?

ICML 2026 has 47 General ML · generalization papers, versus 61 the year before.

How many General ML · generalization papers are at CVPR 2026?

CVPR 2026 has 9 General ML · generalization papers, versus 14 the year before.

Which conference publishes the most General ML · generalization papers?

NeurIPS, with 207 papers from 2023 to 2026.