arXiv Machine Learning By Antoine Szatkownik (TAU, BioInfo), Aur\'elien Decelle (TAU), Beatriz Seoane (TAU), Nicolas B\'ereux (TAU), L\'eo Planche (BioInfo), Guillaume Charpiat (TAU), Burak Yelmen (BioInfo, TAU), Flora Jay (BioInfo, TAU), Cyril Furtlehner (TAU)

PRIVET: PRoximIty leakage detection Via Extreme value Theory

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arXiv Machine Learning
Jul 16

When T2I Synthetic Data Backfires: Amplified Privacy Risks in Real-Synthetic Mix Training

arXiv:2607. 13541v1 Announce Type: cross Abstract: To overcome data scarcity and privacy constraints in data collection, it has become standard practice across academia and industry to augment real training data with text-to-image (T2I)-generated synthetic data, a paradigm we term Real-Synthetic Mix-Training (RSMT).

By Na Li, Boyu Kuang, Hongsheng Hu, Liquan Chen, Hyoungshick Kim, Yansong Gao, Anmin Fu