69 citations · 91 across the 7 of their papers we have counts for
7 papers
Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables
Haisong Gong, Weizhi Xu, Shu wu +2
Fact checking aims to predict claim veracity by reasoning over multiple evidence pieces. It usually involves evidence retrieval and veracity reasoning. In this paper, we focus on t…
EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification
Huanhuan Ma, Weizhi Xu, Yifan Wei +4
Fact verification aims to automatically probe the veracity of a claim based on several pieces of evidence. Existing works are always engaging in accuracy improvement, let alone exp…
Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks
Junfei Wu, Weizhi Xu, Qiang Liu +2
The prevalence and perniciousness of fake news have been a critical issue on the Internet, which stimulates the development of automatic fake news detection in turn. In this paper,…
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,…
A Survey on Graph Structure Learning: Progress and Opportunities
Yanqiao Zhu, Weizhi Xu, Jinghao Zhang +5
Graphs are widely used to describe real-world objects and their interactions. Graph Neural Networks (GNNs) as a de facto model for analyzing graphstructured data, are highly sensit…
Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval
Xueli Yu, Weizhi Xu, Zeyu Cui +2
The ad-hoc retrieval task is to rank related documents given a query and a document collection. A series of deep learning based approaches have been proposed to solve such problem…
When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision
Yanqiao Zhu, Weizhi Xu, Qiang Liu +1
This paper studies active learning (AL) on graphs, whose purpose is to discover the most informative nodes to maximize the performance of graph neural networks (GNNs). Previously,…