Re-Assessing Accuracy Degradation: A Framework for Understanding DNN Behavior on Similar-but-Non-Identical Test Datasets

Anzaku et al. "Re-Assessing Accuracy Degradation: A Framework for Understanding DNN Behavior on Similar-but-Non-Identical Test Datasets." Machine Learning, 2025. doi:10.1007/S10994-024-06693-X

[Anzaku et al. "Re-Assessing Accuracy Degradation: A Framework for Understanding DNN Behavior on Similar-but-Non-Identical Test Datasets." Machine Learning, 2025.](https://mlanthology.org/mlj/2025/anzaku2025mlj-reassessing/) doi:10.1007/S10994-024-06693-X

@article{anzaku2025mlj-reassessing,
  title     = {{Re-Assessing Accuracy Degradation: A Framework for Understanding DNN Behavior on Similar-but-Non-Identical Test Datasets}},
  author    = {Anzaku, Esla Timothy and Wang, Haohan and Babalola, Ajiboye and Van Messem, Arnout and De Neve, Wesley},
  journal   = {Machine Learning},
  year      = {2025},
  pages     = {84},
  doi       = {10.1007/S10994-024-06693-X},
  volume    = {114},
  url       = {https://mlanthology.org/mlj/2025/anzaku2025mlj-reassessing/}
}