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

135 papers, page 2 of 3

51. ICLR 2024Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
52. ICLR 2024Understanding Domain Generalization: A Noise Robustness Perspective
53. ICLR 2024Understanding prompt engineering may not require rethinking generalization
54. ICLR 2024Unknown Domain Inconsistency Minimization for Domain Generalization
55. ICLR 2024Unraveling the Key Components of OOD Generalization via Diversification
56. ICLR 2024Why is SAM Robust to Label Noise?
57. ICML 2024Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
58. ICML 2024Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
59. ICML 2024Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss
60. ICML 2024Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function
61. ICML 2024DOGE: Domain Reweighting with Generalization Estimation
62. ICML 2024Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
63. ICML 2024Ensemble Pruning for Out-of-distribution Generalization
64. ICML 2024Generalization Analysis for Multi-Label Learning
65. ICML 2024Generalization Analysis of Deep Non-linear Matrix Completion
66. ICML 2024Generalization Analysis of Stochastic Weight Averaging with General Sampling
67. ICML 2024Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation
68. ICML 2024Generalization Error of Graph Neural Networks in the Mean-field Regime
69. ICML 2024Generalization in Kernel Regression Under Realistic Assumptions
70. ICML 2024Generalization to New Sequential Decision Making Tasks with In-Context Learning
71. ICML 2024Graph Structure Extrapolation for Out-of-Distribution Generalization
72. ICML 2024How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
73. ICML 2024Improved Generalization of Weight Space Networks via Augmentations
74. ICML 2024Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
75. ICML 2024Interpretability Illusions in the Generalization of Simplified Models
76. ICML 2024LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies
77. ICML 2024Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!
78. ICML 2024Non-Vacuous Generalization Bounds for Large Language Models
79. ICML 2024On the Generalization of Equivariant Graph Neural Networks
80. ICML 2024On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
81. ICML 2024Out-of-Domain Generalization in Dynamical Systems Reconstruction
82. ICML 2024Position: Understanding LLMs Requires More Than Statistical Generalization
83. ICML 2024Prediction-powered Generalization of Causal Inferences
84. ICML 2024Slicing Mutual Information Generalization Bounds for Neural Networks
85. ICML 2024SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms
86. ICML 2024Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
87. ICML 2024Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
88. ICML 2024Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective
89. ICML 2024Understanding the Impact of Introducing Constraints at Inference Time on Generalization Error
90. NeurIPS 2024A Kernel Perspective on Distillation-based Collaborative Learning
91. NeurIPS 2024A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations
92. NeurIPS 2024A Universal Growth Rate for Learning with Smooth Surrogate Losses
93. NeurIPS 2024Achievable distributional robustness when the robust risk is only partially identified
94. NeurIPS 2024Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
95. NeurIPS 2024Aligning to Thousands of Preferences via System Message Generalization
96. NeurIPS 2024An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models
97. NeurIPS 2024Back to the Continuous Attractor
98. NeurIPS 2024Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
99. NeurIPS 2024Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
100. NeurIPS 2024Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning

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.