4 papers
RCTEA: Richness-guided Co-training for Temporal Entity Alignment
Jiayun Li, Wen Hua, Shiqi Fan +3
Temporal Entity Alignment (TEA), which aims to identify equivalent entities across Temporal Knowledge Graphs (TKGs), is crucial for integrating knowledge facts from multiple source…
Random Client Selection on Contrastive Federated Learning for Tabular Data
Achmad Ginanjar, Xue Li, Priyanka Singh +1
Vertical Federated Learning (VFL) has revolutionised collaborative machine learning by enabling privacy-preserving model training across multiple parties. However, it remains vulne…
Contrastive Federated Learning with Tabular Data Silos
Achmad Ginanjar, Xue Li, Wen Hua +1
Learning from vertical partitioned data silos is challenging due to the segmented nature of data, sample misalignment, and strict privacy concerns. Federated learning has been prop…
VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level Relation Extraction
Khai Phan Tran, Wen Hua, Xue Li
Document-level Relation Extraction (DocRE) aims to identify relationships between entity pairs within a document. However, most existing methods assume a uniform label distribution…