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About this paper
Xuming Hu, Zhijiang Guo, Zhiyang Teng, Irwin King, Philip S. Yu
Hu et al. introduce a multimodal relation extraction method that leverages cross-modal retrieval and synthesis of textual and visual evidence. This approach significantly improves performance on the MNRE dataset, showing particular strength in extracting challenging tail relations.
Key insights
- Relationships often manifest across multiple modalities, indicating that combining textual and visual evidence can disambiguate relations and provide additional support.
- The quantity and quality of retrieved evidence significantly impact performance, with an optimal range observed around 10-15 pieces.
- Retrieved evidence is particularly valuable for improving the extraction of tail relations, which are relationship types with limited training examples.
Summary by alphaXiv.
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