Personalized Generative Models for Contextual Debiasing

ArXi:2605.26353v1 Announce Type: cross Different visual patterns appear with different frequencies in the world: e.g., beach balls appear on sand often than they do on a road. These statistics are reflected in vision datasets, and as a result trained models easily recognize objects in common scenarios. However, recognizing a beach ball on a road may arguably be even important than recognizing it on sand. We study how to mitigate this discrepancy.