28 citations · 52 across the 5 of their papers we have counts for
5 papers
Breaking the Reasoning Horizon in Entity Alignment Foundation Models
Yuanning Cui, Zequn Sun, Wei Hu +2
Entity alignment (EA) is critical for knowledge graph (KG) fusion. Existing EA models lack transferability and are incapable of aligning unseen KGs without retraining. While using…
Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production
Kexuan Xin, Qingyun Wang, Junyu Chen +3
In the rapidly evolving field of metabolic engineering, the quest for efficient and precise gene target identification for metabolite production enhancement presents significant ch…
Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding
Kexuan Xin, Zequn Sun, Wen Hua +3
Entity alignment is a crucial task in knowledge graph fusion. However, most entity alignment approaches have the scalability problem. Recent methods address this issue by dividing…
Ensemble Semi-supervised Entity Alignment via Cycle-teaching
Kexuan Xin, Zequn Sun, Wen Hua +4
Entity alignment is to find identical entities in different knowledge graphs. Although embedding-based entity alignment has recently achieved remarkable progress, training data ins…
Informed Multi-context Entity Alignment
Kexuan Xin, Zequn Sun, Wen Hua +2
Entity alignment is a crucial step in integrating knowledge graphs (KGs) from multiple sources. Previous attempts at entity alignment have explored different KG structures, such as…