Seongwoong Shim

FALCON: False-Negative Aware Learning of Contrastive Negatives in Vision-Language Alignment

False negatives pose a critical challenge in vision-language pretraining (VLP) due to the many-to-many correspondence between images and texts in large-scale datasets. These false negatives introduce conflicting supervision signals that degrade the learned embedding space and diminish the effectiven