15 citations · 16 across the 8 of their papers we have counts for
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cs.CL2024
Measuring Non-Adversarial Reproduction of Training Data in Large Language Models
Michael Aerni, Javier Rando, Edoardo Debenedetti +3
Large language models memorize parts of their training data. Memorizing short snippets and facts is required to answer questions about the world and to be fluent in any language. B…
cs.CR2024★ 15 cited
Evaluations of Machine Learning Privacy Defenses are Misleading
Michael Aerni, Jie Zhang, Florian Tramèr
Empirical defenses for machine learning privacy forgo the provable guarantees of differential privacy in the hope of achieving higher utility while resisting realistic adversaries.…