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A Lightweight Velocity Correction Framework for Improving Instruction Following in Few-Step Text-to-Image Generation
Few-step text-to-image generators produce high-quality images with few network forward passes, yet struggle with complex prompts involving multiple subjects, interactions, spatial relations, counting, and attribute binding. Can these errors be reduced without changing the generator's parameters or i
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