Zero-shot Classification with Vision-Language Models Leveraging Unlabeled Data through Label Propagation
By leveraging the inherent structure of unlabeled data through label propagation, the proposed ZLaP method can significantly improve the zero-shot classification performance of vision-language models in both transductive and inductive inference setups.