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POET: Preference Optimization for Enhanced Text-to-Image Generation
Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecified user prompts due to a distributional gap with their descriptive training captions. This frequently leads to suboptimal image-text alignment, aesthetics
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