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cs.LG2025
Attackers Can Do Better: Over- and Understated Factors of Model Stealing Attacks
Daryna Oliynyk, Rudolf Mayer, Andreas Rauber
Machine learning models were shown to be vulnerable to model stealing attacks, which lead to intellectual property infringement. Among other methods, substitute model training is a…
cs.LG2023★ 2 cited
Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis
Anahid Jalali, Bernhard Haslhofer, Simone Kriglstein +1
Post-hoc explainability methods aim to clarify predictions of black-box machine learning models. However, it is still largely unclear how well users comprehend the provided explana…