Learning with Dual-level Noisy Correspondence for Multi-modal Entity Alignment

TL;DR

Multi-modal entity alignment (MMEA) aims to identify equivalent entities across heterogeneous multi-modal knowledge graphs (MMKGs), where each entity is described by attributes from various modalities. Existing methods typically assume that both intra-entity and inter-graph correspondences are faultless, which is often violated in real-world MMK...

Opening excerpt from the authors’ abstract. source