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

46 papers, page 1 of 1

1. NeurIPS 2024A Kernel Perspective on Distillation-based Collaborative Learning
2. NeurIPS 2024A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations
3. NeurIPS 2024A Universal Growth Rate for Learning with Smooth Surrogate Losses
4. NeurIPS 2024Achievable distributional robustness when the robust risk is only partially identified
5. NeurIPS 2024Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
6. NeurIPS 2024Aligning to Thousands of Preferences via System Message Generalization
7. NeurIPS 2024An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models
8. NeurIPS 2024Back to the Continuous Attractor
9. NeurIPS 2024Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
10. NeurIPS 2024Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
11. NeurIPS 2024Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
12. NeurIPS 2024Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
13. NeurIPS 2024Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
14. NeurIPS 2024Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
15. NeurIPS 2024Continuous Temporal Domain Generalization
16. NeurIPS 2024DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity
17. NeurIPS 2024Dissecting the Failure of Invariant Learning on Graphs
18. NeurIPS 2024Doubly Mild Generalization for Offline Reinforcement Learning
19. NeurIPS 2024Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets
20. NeurIPS 2024Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
21. NeurIPS 2024Focus On What Matters: Separated Models For Visual-Based RL Generalization
22. NeurIPS 2024Generalizablity of Memorization Neural Network
23. NeurIPS 2024Generalization Analysis for Label-Specific Representation Learning
24. NeurIPS 2024Generalization Bounds via Conditional $f$-Information
25. NeurIPS 2024Generalization of Hamiltonian algorithms
26. NeurIPS 2024Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
27. NeurIPS 2024In-Context Learning with Representations: Contextual Generalization of Trained Transformers
28. NeurIPS 2024Information-theoretic Generalization Analysis for Expected Calibration Error
29. NeurIPS 2024Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
30. NeurIPS 2024LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
31. NeurIPS 2024Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization
32. NeurIPS 2024On the Limitations of Fractal Dimension as a Measure of Generalization
33. NeurIPS 2024Partial Transportability for Domain Generalization
34. NeurIPS 2024Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Cloud Analysis
35. NeurIPS 2024Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure
36. NeurIPS 2024Quantifying the Gain in Weak-to-Strong Generalization
37. NeurIPS 2024Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes
38. NeurIPS 2024The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
39. NeurIPS 2024The Price of Implicit Bias in Adversarially Robust Generalization
40. NeurIPS 2024Towards Combating Frequency Simplicity-biased Learning for Domain Generalization
41. NeurIPS 2024Transformers Can Do Arithmetic with the Right Embeddings
42. NeurIPS 2024Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
43. NeurIPS 2024Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models
44. NeurIPS 2024What Variables Affect Out-of-Distribution Generalization in Pretrained Models?
45. NeurIPS 2024Where Do Large Learning Rates Lead Us?
46. NeurIPS 2024WikiDO: Evaluating Out-of-Distribution Generalization of Vision-Language Models in Cross-Modal Retrieval

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.