Composing Multiple LoRA Models for Coherent Image Generation

CLoRA, a novel framework that leverages contrastive learning to effectively compose multiple LoRA (Low-Rank Adaptation) models, addressing challenges related to attention overlap and attribute binding to generate coherent images that faithfully reflect the characteristics of each LoRA.