17 citations · 36 across the 8 of their papers we have counts for
8 papers
LLM as Prompter: Low-resource Inductive Reasoning on Arbitrary Knowledge Graphs
Kai Wang, Yuwei Xu, Zhiyong Wu +1
Knowledge Graph (KG) inductive reasoning, which aims to infer missing facts from new KGs that are not seen during training, has been widely adopted in various applications. One cri…
Mutual Information as Intrinsic Reward of Reinforcement Learning Agents for On-demand Ride Pooling
Xianjie Zhang, Jiahao Sun, Chen Gong +4
The emergence of on-demand ride pooling services allows each vehicle to serve multiple passengers at a time, thus increasing drivers' income and enabling passengers to travel at lo…
When Large Language Models Meet Citation: A Survey
Yang Zhang, Yufei Wang, Kai Wang +5
Citations in scholarly work serve the essential purpose of acknowledging and crediting the original sources of knowledge that have been incorporated or referenced. Depending on the…
River of No Return: Graph Percolation Embeddings for Efficient Knowledge Graph Reasoning
Kai Wang, Siqiang Luo, Dan Lin
We study Graph Neural Networks (GNNs)-based embedding techniques for knowledge graph (KG) reasoning. For the first time, we link the path redundancy issue in the state-of-the-art K…
Trust-SIoT: Towards Trustworthy Object Classification in the Social Internet of Things
Subhash Sagar, Adnan Mahmood, Kai Wang +2
The recent emergence of the promising paradigm of the Social Internet of Things (SIoT) is a result of an intelligent amalgamation of the social networking concepts with the Interne…
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…
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…
Knowledge Graph Embedding with Entity Neighbors and Deep Memory Network
Kai Wang, Yu Liu, Xiujuan Xu +1
Knowledge Graph Embedding (KGE) aims to represent entities and relations of knowledge graph in a low-dimensional continuous vector space. Recent works focus on incorporating struct…