4 papers
Beyond Completion: A Foundation Model for General Knowledge Graph Reasoning
Yin Hua, Zhiqiang Liu, Mingyang Chen +6
In natural language processing (NLP) and computer vision (CV), the successful application of foundation models across diverse tasks has demonstrated their remarkable potential. How…
SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network
Yushan Zhu, Wen Zhang, Yajing Xu +3
Graph Neural Network (GNN), with the main idea of encoding graph structure information of graphs by propagation and aggregation, has developed rapidly. It achieved excellent perfor…
Croppable Knowledge Graph Embedding
Yushan Zhu, Wen Zhang, Zhiqiang Liu +3
Knowledge Graph Embedding (KGE) is a common approach for Knowledge Graphs (KGs) in AI tasks. Embedding dimensions depend on application scenarios. Requiring a new dimension means t…
Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph Embedding
Xiangnan Chen, Wen Zhang, Zhen Yao +2
Knowledge graph embedding (KGE) aims to map entities and relations of a knowledge graph (KG) into a low-dimensional and dense vector space via contrasting the positive and negative…