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About this paper
Delong Zeng, Yuexiang Xie, Yaliang Li, Ying Shen
The CIEA method enhances multimodal retrieval by explicitly identifying and utilizing complementary visual information not redundant with associated text. This approach integrates language and CLIP models with a specialized extractor, leading to significant performance gains across multimodal datasets like WebQA and EDIS.
Key insights
- Explicitly extracting and leveraging complementary information unique to visual modalities significantly improves the accuracy and robustness of multimodal retrieval systems.
- Measuring dissimilarity between image patches and text tokens is an effective strategy for identifying visual elements not well-described by text.
- Combining a standard semantic integrity loss with a tailored complementary information extraction loss effectively balances overall relevance with the capture of unique modal contributions.
Summary by alphaXiv.
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