COCO-DR Continuous Contrastive Learning for Cross-Domain Multimodal Retrieval on Flickr30k

Abstract

Abstract: Multimodal sarcasm detection aims to identify sarcasm in the given image-text pairs and has wide applications in the multimodal domains. Previous works primarily design complex network structures to fuse the image-text modality features for classification. However, such complicated structures may risk overfitting on in-domain data, reducing the performance in out-of-distribution (OOD) scenarios. Additionally, existing methods typically do not fully utilize cross-modal features, limiting their performance on in-domain datasets. Therefore, to build a more reliable multimodal sarcasm detection mo

Research Question

Does the COCO-DR approach of continuous contrastive learning on target corpora improve cross-domain generalization for multimodal retrieval on Flickr30k relative to in-distribution performance?

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