semantic-repair

This paper introduces Type-Aware Repair Allocation (TARA), a training-free framework that decomposes text-to-image prompt optimization into atomic repair allocation, where each failed proposition is routed to a type-conditioned repair operator. Experiments show TARA achieves the best semantic accuracy on DSG and TIFA benchmarks across four generators, improving over VisualPrompter while maintaining image quality.