Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models

This paper proposes a lightweight, inference-time framework to mitigate demographic representational bias in text-to-image models like Stable Diffusion, without requiring model retraining. The approach allows users to select their own fairness specifications to generate more equitable outputs across professions.