3 accepted papers
Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multimodal knowledge graphs (MMKGs). However, the intrinsic noise within modalities, such as the inconsistency in visual modality and redundant attributes, has not been thoroughly investigated. Excessive noise not o
Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs, which consist of structural triples and images associated with entities. Unfortunately, prior works fuse the multi-modal knowledge of all entities only via solely one single fusion s…
Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs. Current methods have made significant progress by improving embedding and cross-modal fusion. However, most of them depend on using loss functions to capture the relationship between…