156 citations · 470 across the 24 of their papers we have counts for
5 papers · 1 filter
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification
Xingcheng Fu, Yuecen Wei, Qingyun Sun +4
Learning unbiased node representations for imbalanced samples in the graph has become a more remarkable and important topic. For the graph, a significant challenge is that the topo…
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization
Dongcheng Zou, Hao Peng, Xiang Huang +5
Graph Neural Networks (GNNs) are de facto solutions to structural data learning. However, it is susceptible to low-quality and unreliable structure, which has been a norm rather th…
A Comprehensive Survey on Automatic Knowledge Graph Construction
Lingfeng Zhong, Jia Wu, Qian Li +2
Automatic knowledge graph construction aims to manufacture structured human knowledge. To this end, much effort has historically been spent extracting informative fact patterns fro…
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
Ce Zhou, Qian Li, Chen Li +16
Pretrained Foundation Models (PFMs) are regarded as the foundation for various downstream tasks with different data modalities. A PFM (e.g., BERT, ChatGPT, and GPT-4) is trained on…
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning
Cheng Ji, Jianxin Li, Hao Peng +4
Contrastive Learning (CL) has been proved to be a powerful self-supervised approach for a wide range of domains, including computer vision and graph representation learning. Howeve…