Papers with inference-time optimization losses

1 papers
R-Bind: Unified Enhancement of Attribute and Relation Binding in Text-to-Image Diffusion Models (2025.emnlp-main)

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Challenge: Existing approaches to improve semantic binding require costly retraining or focus on only correctly generating attributes of entities. Existing methods focus on correctly generating attributes, ignoring the cruciality of correctly forming relations between entities.
Approach: They propose a training-free method that improves both entity-attribute and entity-relation-entity binding by introducing three inference-time optimization losses that adjust attention maps during generation.
Outcome: The proposed method improves both entity-attribute and entity-relation-entity binding without additional training.

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