AINeutralarXiv – CS AI · May 297/10
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Rethinking FID Through the Geometry of the Reference Dataset
Researchers demonstrate that Fréchet Inception Distance (FID), a standard metric for evaluating image generators, produces inconsistent results depending on the reference dataset's geometric properties. The study shows that dataset density and effective rank significantly influence FID trends, meaning lower FID scores don't reliably indicate better sample quality across different benchmarks.