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

47 papers, page 1 of 1

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?

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.