Enhancing Multimodal Retrieval via Complementary Information Extraction and Alignment (2025.acl-long)
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| Challenge: | Existing studies focus on capturing information in multimodal data that is similar to their paired texts, but often ignores the complementary information contained in multimodule data. |
| Approach: | They propose a multimodal retrieval approach that employs Complementary Information Extraction and Alignment to capture complementary information in multimodal data. |
| Outcome: | The proposed approach achieves significant improvements over divide-and-conquer models and universal dense retrieval models. |
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