Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models

ICLROral2026

Authors
Bartłomiej Marek, Lorenzo Rossi, Vincent Hanke, Xun Wang, Michael Backes, Franziska Boenisch, Adam Dziedzic
Affiliation
CISPA Helmholtz Center for Information Security
Venue
ICLR 2026
Track
Oral

TL;DR

DP adaptations of LLMs can leak data in practice, with risk rising as adaptation data becomes closer to the pretraining distribution.

Opening excerpt from the authors’ abstract. source

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Topics

large language model language model pretraining benchmark privacy llm

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