arXiv Machine Learning July 16, 2026 By Na Li, Boyu Kuang, Hongsheng Hu, Liquan Chen, Hyoungshick Kim, Yansong Gao, Anmin Fu

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

Read the original on arXiv Machine Learning →

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).

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