Reproduce “PE-OPSD: Internalizing Prompt Enhancement into Flow-matching Models via On-Policy Self-Distillation” on OpenResearch

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About this paper

Mingfeng Lin, Chengfei Cai, Lin Xu, Chengqian Ma, Yuxiang Wei, Liang Han

PE-OPSD transfers prompt enhancement into training for flow-matching text-to-image models. It distills an enhanced-prompt teacher at states reached by a student generating from the original prompt, so inference needs no rewriter. Across three backbones, it leads aggregate prompt-fidelity improvement over Base and improves aggregate visual appeal versus Base, though not every prompt improves or visual appeal always exceeds inference-time enhancement.

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