arXiv Machine Learning By Rasmus Torp, Shailen K. Smith, Adam Breuer

Reducing information dependency does not cause training data privacy. Adversarially non-robust features do

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arXiv:2607. 12354v1 Announce Type: new Abstract: In this paper, we challenge the prevailing view that information dependency (including rote memorization) drives training data exposure to image reconstruction attacks.

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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