413 citations · 956 across the 26 of their papers we have counts for
39 papers
Evidence-aware Fake News Detection with Graph Neural Networks
Weizhi Xu, Junfei Wu, Qiang Liu +2
The prevalence and perniciousness of fake news has been a critical issue on the Internet, which stimulates the development of automatic fake news detection in turn. In this paper,…
An Empirical Study of Graph Contrastive Learning
Yanqiao Zhu, Yichen Xu, Qiang Liu +1
Graph Contrastive Learning (GCL) establishes a new paradigm for learning graph representations without human annotations. Although remarkable progress has been witnessed recently,…
Relation-aware Heterogeneous Graph for User Profiling
Qilong Yan, Yufeng Zhang, Qiang Liu +2
User profiling has long been an important problem that investigates user interests in many real applications. Some recent works regard users and their interacted objects as entitie…
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning
Yanqiao Zhu, Yichen Xu, Hejie Cui +3
Recently, heterogeneous Graph Neural Networks (GNNs) have become a de facto model for analyzing HGs, while most of them rely on a relative large number of labeled data. In this wor…
Deep Active Learning for Text Classification with Diverse Interpretations
Qiang Liu, Yanqiao Zhu, Zhaocheng Liu +2
Recently, Deep Neural Networks (DNNs) have made remarkable progress for text classification, which, however, still require a large number of labeled data. To train high-performing…
Fully Hyperbolic Graph Convolution Network for Recommendation
Liping Wang, Fenyu Hu, Shu Wu +1
Recently, Graph Convolution Network (GCN) based methods have achieved outstanding performance for recommendation. These methods embed users and items in Euclidean space, and perfor…