The DOI matches its OpenAlex record; 1 of the 1 references it cites were found in a registry or an index.
On Assessing ML Model Robustness: A Methodological Framework (Academic Track)
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Adversarial Robustness Toolbox v1.0.0
Nicolae, M.-I., Sinn, M., Tran, M. N., Buesser, B., Rawat, A., Wistuba, M., Zantedeschi, V., Baracaldo, N., Chen, B., Ludwig, H., et al. (2018) · arXiv · doi:10.48550/arxiv.1807.01069 · Cited by 594
Cited by
CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features
Yun, S., Han, D., Chun, S., Oh, S. J., Yoo, Y., & Choe, J. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00612 · Cited by 5,400
Self-Training With Noisy Student Improves ImageNet Classification
Xie, Q., Luong, M.-T., Hovy, E., & Le, Q. V. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01070 · Cited by 2,393
Shortcut learning in deep neural networks
Geirhos, R., Jacobsen, J.-H., Michaelis, C., Zemel, R., Brendel, W., Bethge, M., & Wichmann, F. A. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-020-00257-z · Cited by 2,224
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Akhtar, N., & Mian, A. (2018) · IEEE Access · doi:10.1109/access.2018.2807385 · Cited by 2,021
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Xu, W., Evans, D., & Qi, Y. (2018) · Proceedings 2018 Network and Distributed System Security Symposium · doi:10.14722/ndss.2018.23198 · Cited by 1,768
Metadata
- Authors
- Awadid, A., & Robert, B.
- Venue
- OASIcs : OpenAccess Series in Informatics
- Publisher
- Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- Published
- 2025
- ISSN
- 2190-6807 (ISSN-L)
- OpenAlex
- W4293846201
- Cited by
- 4,702
- References
- 1
- FWCI
- 904.68
- Type
- conference paper
- Language
- en
- Open access
- diamond
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- CoChat. (2026). Citation check: On Assessing ML Model Robustness: A Methodological Framework (Academic Track). https://app.cochat.ai/papers/10.4230/oasics.saia.2024.1
- The paper
- Awadid, A., & Robert, B. (2025). On Assessing ML Model Robustness: A Methodological Framework (Academic Track). OASIcs : OpenAccess Series in Informatics. https://doi.org/10.4230/oasics.saia.2024.1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
