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News/Advancing the State-of-the-Art in Empirical Privacy Auditing
arxiv
PublishedJune 10, 2026 at 4:00 AM
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Advancing the State-of-the-Art in Empirical Privacy Auditing

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Publisher summary· verbatim

arXiv:2606.10481v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning of large language models (LLMs) can exhibit problematic memorization of individual training examples. Empirical privacy auditing (EPA) quantifies this risk by measuring realistic data leakage on membership inference (M

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#privacy#language-models#auditing#security

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