Daniel Garibi

Fine-grained identity tuning enables precise facial edits in text-to-image models without additional training, preserving identity consistency across diverse outputs.

Unleashing creative potential in text-to-image models just got easier: on-the-fly repulsion in the contextual space lets you steer diffusion transformers towards richer diversity without sacrificing image quality or blowing your compute budget.