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cs.CV2025
Rethinking Bias in Generative Data Augmentation for Medical AI: a Frequency Recalibration Method
Chi Liu, Jincheng Liu, Congcong Zhu +5
Developing Medical AI relies on large datasets and easily suffers from data scarcity. Generative data augmentation (GDA) using AI generative models offers a solution to synthesize…
cs.CV2025
Causal Fingerprints of AI Generative Models
Hui Xu, Chi Liu, Congcong Zhu +3
AI generative models leave implicit traces in their generated images, which are commonly referred to as model fingerprints and are exploited for source attribution. Prior methods r…