24 citations · 33 across the 4 of their papers we have counts for
4 papers
Improving the Robustness of Knowledge-Grounded Dialogue via Contrastive Learning
Jiaan Wang, Jianfeng Qu, Kexin Wang +4
Knowledge-grounded dialogue (KGD) learns to generate an informative response based on a given dialogue context and external knowledge (\emph{e.g.}, knowledge graphs; KGs). Recently…
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…
High-quality Task Division for Large-scale Entity Alignment
Bing Liu, Wen Hua, Guido Zuccon +2
Entity Alignment (EA) aims to match equivalent entities that refer to the same real-world objects and is a key step for Knowledge Graph (KG) fusion. Most neural EA models cannot be…
Frequency-based Randomization for Guaranteeing Differential Privacy in Spatial Trajectories
Fengmei Jin, Wen Hua, Boyu Ruan +1
With the popularity of GPS-enabled devices, a huge amount of trajectory data has been continuously collected and a variety of location-based services have been developed that great…