% Key papers for Empirical generalization measures (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_exploring_56304,
  title = {{Exploring Generalization in Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9367},
}

@inproceedings{iclr2018_sensitivity_28506,
  title = {{Sensitivity and Generalization in Neural Networks: an Empirical Study}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/65},
}

@inproceedings{iclr2020_fantastic_29627,
  title = {{Fantastic Generalization Measures and Where to Find Them}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=SJgIPJBFvH},
}

@inproceedings{iclr2019_the_28836,
  title = {{The role of over-parametrization in generalization of neural networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/886},
}

@inproceedings{iclr2019_deep_29206,
  title = {{Deep learning generalizes because the parameter-function map is biased towards simple functions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/989},
}

@inproceedings{iclr2019_non_28775,
  title = {{Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/806},
}

@inproceedings{icml2018_stronger_37016,
  title = {{Stronger Generalization Bounds for Deep Nets via a Compression Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2412},
}

@inproceedings{iclr2021_in_30595,
  title = {{In Search of Lost Domain Generalization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2998},
}

@inproceedings{aaai2020_rethinking_102966,
  title = {{Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6276},
}

@inproceedings{iclr2020_a_29877,
  title = {{A Constructive Prediction of the Generalization Error Across Scales}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=ryenvpEKDr},
}

@inproceedings{iclr2018_on_28530,
  title = {{On the Discrimination-Generalization Tradeoff in GANs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/248},
}

@inproceedings{iclr2019_an_29214,
  title = {{An analytic theory of generalization dynamics and transfer learning in deep linear networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/798},
}

@inproceedings{iclr2020_compression_29360,
  title = {{Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=ByeGzlrKwH},
}

@inproceedings{icml2018_learning_36804,
  title = {{Learning and Memorization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2080},
}

@inproceedings{neurips2021_intrinsic_61168,
  title = {{Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26392},
}

@inproceedings{icml2020_normalized_38517,
  title = {{Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6348},
}

@inproceedings{neurips2019_generalization_58324,
  title = {{Generalization in multitask deep neural classifiers: a statistical physics approach}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14471},
}

@inproceedings{icml2020_small_38765,
  title = {{Small Data, Big Decisions: Model Selection in the Small-Data Regime}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6850},
}

@inproceedings{iclr2020_improved_29444,
  title = {{Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HJe_yR4Fwr},
}

@inproceedings{neurips2021_model_61888,
  title = {{Model-Based Domain Generalization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26562},
}

@inproceedings{aaai2024_lost_6549,
  title = {{Lost Domain Generalization Is a Natural Consequence of Lack of Training Domains}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29497},
}

@inproceedings{aaai2025_generalization_9315,
  title = {{Generalization Analysis for Deep Contrastive Representation Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33889},
}

@inproceedings{icml2024_interpretability_44675,
  title = {{Interpretability Illusions in the Generalization of Simplified Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33777},
}

@inproceedings{iclr2025_how_83555,
  title = {{How many samples are needed to train a deep neural network?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28262},
}

@inproceedings{aaai2024_understanding_7685,
  title = {{Understanding Surprising Generalization Phenomena in Deep Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30285},
}

@inproceedings{icml2024_on_44640,
  title = {{On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33812},
}

@inproceedings{icml2025_understanding_45853,
  title = {{Understanding Nonlinear Implicit Bias via Region Counts in Input Space}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46690},
}

@inproceedings{icml2025_algorithm_46020,
  title = {{Algorithm Development in Neural Networks: Insights from the Streaming Parity Task}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46526},
}

@inproceedings{icml2026_the_49602,
  title = {{The Data Manifold under the Microscope}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=42cOdUJOhH},
}

@inproceedings{icml2026_compositional_50241,
  title = {{Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=AQZZWVp6XA},
}

@inproceedings{neurips2024_where_71318,
  title = {{Where Do Large Learning Rates Lead Us?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95929},
}

@inproceedings{neurips2024_on_72683,
  title = {{On the Limitations of Fractal Dimension as a Measure of Generalization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94703},
}

@inproceedings{neurips2025_length_77076,
  title = {{Length Generalization via Auxiliary Tasks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=QL3J1fyAFv},
}

@inproceedings{neurips2025_generalization_79214,
  title = {{Generalization Bounds for Rank-sparse Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=n3M8h9mqDm},
}

@inproceedings{iclr2025_generalization_82025,
  title = {{Generalization and Distributed Learning of GFlowNets}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29760},
}

@inproceedings{iclr2026_bound_87220,
  title = {{Bound by semanticity: universal laws governing the generalization-identification tradeoff}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=ZF0xRAdsuY},
}

@inproceedings{neurips2026_length_91714,
  title = {{Length Generalization for Transformers via Compression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150600},
}

@inproceedings{neurips2026_a_91891,
  title = {{A Measure-Theoretic Analysis of Reasoning: Structural Generalization and Approximation Limits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155536},
}

@inproceedings{icml2026_understanding_53949,
  title = {{Understanding Generalization from Embedding Dimension and Distributional Convergence}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=kKlzS0HQjJ},
}

@inproceedings{neurips2026_does_91761,
  title = {{Does Compression Imply Generalization? A Minimum Description Length Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151042},
}