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

58 papers, page 1 of 2

1. NeurIPS 2026(Mis)generalization of Helpful-Only Fine-Tuning
2. NeurIPS 2026A General Concept-based Decomposition for Vision–Language Embeddings
3. NeurIPS 2026A mathematical theory of balancing relational generalization and memorization
4. NeurIPS 2026Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study
5. NeurIPS 2026Asymmetric Generalization in Deep CTR Models: A Block-wise Diagnosis
6. NeurIPS 2026Beyond Average Flatness: Domain-wise Flatness for Domain Generalization
7. NeurIPS 2026Building Transformation Layers for Riemannian Neural Networks
8. NeurIPS 2026CASAM: Consistency-Anchored Sharpness-Aware Minimization for Improved Model Generalization
9. NeurIPS 2026Certification-Enhanced Generalization Bounds
10. NeurIPS 2026Characterizing the Generalization Error of Random Feature Regression with Arbitrary Data-Augmentation
11. NeurIPS 2026Class–Domain Discriminability Guided Representation Enhancement for Domain Generalization
12. NeurIPS 2026Compositional Generalization Certificates via the Van Kampen Theorem
13. NeurIPS 2026Cross-Distribution Generalization in Longitudinal Behavioral Data Through Frozen Coherence Constraints
14. NeurIPS 2026Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold
15. NeurIPS 2026Does Compression Imply Generalization? A Minimum Description Length Perspective
16. NeurIPS 2026Does Sparse Connectivity Improve Generalization? Convolutional Networks Below the Edge of Stability
17. NeurIPS 2026Escaping Parameter Space: Tight Generalization Bounds via Representation Quality
18. NeurIPS 2026FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
19. NeurIPS 2026FLoRA-Chef: Making A Good LoRA Recipe in Federated Generalization
20. NeurIPS 2026FOCUS: Benchmarking Retinal Model Generalization from Foundation Vision Encoders to Multimodal LLMs
21. NeurIPS 2026Free Decompression with Algebraic Spectral Curves
22. NeurIPS 2026FuncFormer: Circuit Representation Learning via the Flow of Functional Propagation
23. NeurIPS 2026Generalization Analysis of Biased Stochastic Gradient Methods for Minimax Problems
24. NeurIPS 2026Generalization at the Edge of Stability
25. NeurIPS 2026Generalization Bounds for Neural Networks with Sparse Connectivity
26. NeurIPS 2026Generalization Dynamics of Linear Diffusion Models
27. NeurIPS 2026Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs
28. NeurIPS 2026Generalization in Neural Networks Through the Lens of Magnitude Potential
29. NeurIPS 2026Generalization Measures for Deep Learning Should Be Audited for Fragility
30. NeurIPS 2026Generalization Without Compression Penalty: A Stability Analysis of Error Feedback
31. NeurIPS 2026Guiding Data Allocation for Robust Subpopulation Generalization
32. NeurIPS 2026HoloGene: Learning to Lift Sliced Spatial Transcriptomics to Holistic 3D Gene Fields
33. NeurIPS 2026How Useful Is Cross-Domain Generalization for Training LLM Monitors?
34. NeurIPS 2026Irreducible Supervision Enables Compositional Generalization in Post-Training
35. NeurIPS 2026Is Memorization Actually Necessary for Generalization
36. NeurIPS 2026Label-Free Consistency Correction for Weak-to-Strong Generalization
37. NeurIPS 2026Learning Informative Invariant Representations via Hierarchical Latent Decomposition
38. NeurIPS 2026Learning Optimal Transport Plans Via Autoregressive Token Regression
39. NeurIPS 2026LIBERO-PeRM: Benchmarking Personalized Robotic Manipulation
40. NeurIPS 2026Multiple Descent of Generalization Curve for Optimally Regularized Ridge Regression
41. NeurIPS 2026Neural population tuning statistics as priors for multitask generalization
42. NeurIPS 2026Nexus: Same Pretraining Loss, Better Downstream Generalization via Common Minima
43. NeurIPS 2026Orthogonal Origin Parking: Decoupling Lorentz Manifolds for Robust OOD Generalization
44. NeurIPS 2026PENEX: AdaBoost-Inspired Neural Network Regularization
45. NeurIPS 2026Random-Effects Centroids for Domain Generalization
46. NeurIPS 2026Rethinking Memorization–Generalization Trade-Off in Generative Models
47. NeurIPS 2026Skipping Domain Shifts: Domain Memory Retention Enhanced Hyperspectral Single-Source Domain Generalization
48. NeurIPS 2026State-Action Selection in General Stochastic Games under Regularized Policy Gradient Methods
49. NeurIPS 2026StomataBench: Measuring Taxonomic Generalization in Stomatal Detection
50. NeurIPS 2026TF-PRVR: Training-Free Partially Relevant Video Retrieval for Real-World 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.