AI RESEARCH
Evolutionary Token-Level Prompt Optimization for Diffusion Models
arXiv CS.AI
•
ArXi:2604.09861v1 Announce Type: new Text-to-image diffusion models exhibit strong generative performance but remain highly sensitive to prompt formulation, often requiring extensive manual trial and error to obtain satisfactory results. This motivates the development of automated, model-agnostic prompt optimization methods that can systematically explore the conditioning space beyond conventional text rewriting. This work investigates the use of a Genetic Algorithm (GA) for prompt optimization by directly evolving the token vectors employed by CLIP-based diffusion models.