Papers by Sharon X Huang

1 papers
ANCHOR: LLM-driven Subject Conditioning for Text-to-Image Synthesis (2026.findings-acl)

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Challenge: Text-to-image (T2I) models are trained on literal, object-centric prompts designed to reflect the visible contents of an image.
Approach: They propose a method to extract key subjects and enhance their representation at embedding-level using Large Language Models.
Outcome: The proposed model significantly improves image-caption consistency and human preference alignment.

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