Preprint
Aug 2026
Limitations of Synthetic Data Generation in Specialized Data-Scarce Domains
This work focuses on domains where images differ substantially from common image datasets and additional data are expensive to obtain, and evaluates the downstream classifier performance improvements yielded by two schools of generative sparse data extension: distribution modeling and sample perturbation.
Edward Zhang, Marcel Hussing, Tanay Tandon et al.
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