Podakanti Satyajith Chary

A multimodal framework that accurately detects ambivalence and hesitancy in health behavior videos achieves a macro F1 score nearly double that of existing zero-shot methods.

Differential attention and asymmetric loss functions can significantly improve the performance of BiomedCLIP on highly imbalanced video classification tasks like identifying rare pathologies in video capsule endoscopy.