3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Knowledge Graph Error Detection with Contrastive Confidence Adaption
Xiangyu Liu, Yang Liu, Wei Hu
Knowledge graphs (KGs) often contain various errors. Previous works on detecting errors in KGs mainly rely on triplet embedding from graph structure. We conduct an empirical study…
cs.CL2022★ 3 cited
I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning
Yang Liu, Zequn Sun, Guangyao Li +1
Knowledge graph (KG) embedding seeks to learn vector representations for entities and relations. Conventional models reason over graph structures, but they suffer from the issues o…
cs.LG2022★ 1 cited
Sparse Graph Learning with Spectrum Prior for Deep Graph Convolutional Networks
Jin Zeng, Yang Liu, Gene Cheung +1
A graph convolutional network (GCN) employs a graph filtering kernel tailored for data with irregular structures. However, simply stacking more GCN layers does not improve performa…