Provably Protecting Fine-Tuned LLMs from Training Data Extraction while Preserving Utility

Fuente: arXiv

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Bibliographic Details
Main Authors:	Segal, Tom, Shabtai, Asaf, Elovici, Yuval
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2602.00688