5 papers
Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion
Jiawei Sheng, Taoyu Su, Xixun Lin +2
Multi-domain knowledge graph completion (MKGC) aims to improve missing triple prediction in a target KG by transferring knowledge from other support KGs. Existing methods typically…
Unlocking the Power of Large Language Models for Multi-table Entity Matching
Yingkai Tang, Taoyu Su, Wenyuan Zhang +2
Multi-table entity matching (MEM) addresses the limitations of dual-table approaches by enabling simultaneous identification of equivalent entities across multiple data sources wit…
S2CDR: Smoothing-Sharpening Process Model for Cross-Domain Recommendation
Xiaodong Li, Juwei Yue, Xinghua Zhang +5
User cold-start problem is a long-standing challenge in recommendation systems. Fortunately, cross-domain recommendation (CDR) has emerged as a highly effective remedy for the user…
Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
Juwei Yue, Haikuo Li, Jiawei Sheng +4
Graph neural networks (GNNs) leverage message passing mechanisms to learn the topological features of graph data. Traditional GNNs learns node features in a spatial domain unrelate…
Mitigating Modality Bias in Multi-modal Entity Alignment from a Causal Perspective
Taoyu Su, Jiawei Sheng, Duohe Ma +5
Multi-Modal Entity Alignment (MMEA) aims to retrieve equivalent entities from different Multi-Modal Knowledge Graphs (MMKGs), a critical information retrieval task. Existing studie…