6 citations · 10 across the 4 of their papers we have counts for
4 papers
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers
Xiaoyan Zhao, Yang Deng, Min Yang +6
Relation extraction (RE) involves identifying the relations between entities from underlying content. RE serves as the foundation for many natural language processing (NLP) and inf…
CSGCL: Community-Strength-Enhanced Graph Contrastive Learning
Han Chen, Ziwen Zhao, Yuhua Li +3
Graph Contrastive Learning (GCL) is an effective way to learn generalized graph representations in a self-supervised manner, and has grown rapidly in recent years. However, the und…
Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptive Residual Module
Jingbo Zhou, Yixuan Du, Ruqiong Zhang +7
Graph Neural Networks (GNNs), a type of neural network that can learn from graph-structured data through neighborhood information aggregation, have shown superior performance in va…
Adaptive Depth Graph Attention Networks
Jingbo Zhou, Yixuan Du, Ruqiong Zhang +1
As one of the most popular GNN architectures, the graph attention networks (GAT) is considered the most advanced learning architecture for graph representation and has been widely…