Vision Language Models for Cross-Modal Retrieval
Contrastive Language–Image Pre-training (CLIP) gives strong zero-shot baselines for cross-modal retrieval, but full fine-tuning is costly and InfoNCE treats every non-matching pair as an equally wrong negative. We study parameter-efficient fine-tuning of CLIP ViT-B/32 on MS-COCO 2017 with three components added increme...