The authors apply the MPR metric (an integral probability metric) to text-to-image generation, derive tractable forms for linear and decision-tree function classes, and use it as a fine-tuning objective that reduces intersectional demographic bias while keeping CLIP scores nearly unchanged.
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Multi-Group Proportional Representation for Text-to-Image Models
The authors apply the MPR metric (an integral probability metric) to text-to-image generation, derive tractable forms for linear and decision-tree function classes, and use it as a fine-tuning objective that reduces intersectional demographic bias while keeping CLIP scores nearly unchanged.