41 citations · 42 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings
Kai Wang, Yu Liu, Quan Z. Sheng
Knowledge graph embedding (KGE) has shown great potential in automatic knowledge graph (KG) completion and knowledge-driven tasks. However, recent KGE models suffer from high train…
cs.AI2021
Hyperbolic Geometry is Not Necessary: Lightweight Euclidean-Based Models for Low-Dimensional Knowledge Graph Embeddings
Kai Wang, Yu Liu, Dan Lin +1
Recent knowledge graph embedding (KGE) models based on hyperbolic geometry have shown great potential in a low-dimensional embedding space. However, the necessity of hyperbolic spa…
cs.AI2020★ 41 cited
MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings
Kai Wang, Yu Liu, Qian Ma +1
Link prediction based on knowledge graph embeddings (KGE) aims to predict new triples to automatically construct knowledge graphs (KGs). However, recent KGE models achieve performa…