45 citations · 141 across the 23 of their papers we have counts for
9 papers · 1 filter
A Boundary Regression Model for Nested Named Entity Recognition
Yanping Chen, Lefei Wu, Qinghua Zheng +7
Recognizing named entities (NEs) is commonly conducted as a classification problem that predicts a class tag for a word or a NE candidate in a sentence. In shallow structures, cate…
XTQA: Span-Level Explanations of the Textbook Question Answering
Jie Ma, Qi Chai, Jun Liu +3
Textbook Question Answering (TQA) is a task that one should answer a diagram/non-diagram question given a large multi-modal context consisting of abundant essays and diagrams. We a…
SeqTrans: Automatic Vulnerability Fix via Sequence to Sequence Learning
Jianlei Chi, Yu Qu, Ting Liu +2
Software vulnerabilities are now reported at an unprecedented speed due to the recent development of automated vulnerability hunting tools. However, fixing vulnerabilities still ma…
Self-Weighted Robust LDA for Multiclass Classification with Edge Classes
Caixia Yan, Xiaojun Chang, Minnan Luo +4
Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative features for multi-class classification. A vast majority of existing LDA algorithms are p…
TaxThemis: Interactive Mining and Exploration of Suspicious Tax Evasion Group
Yating Lin, Kamkwai Wong, Yong Wang +4
Tax evasion is a serious economic problem for many countries, as it can undermine the government' s tax system and lead to an unfair business competition environment. Recent resear…
DWMD: Dimensional Weighted Orderwise Moment Discrepancy for Domain-specific Hidden Representation Matching
Rongzhe Wei, Fa Zhang, Bo Dong +1
Knowledge transfer from a source domain to a different but semantically related target domain has long been an important topic in the context of unsupervised domain adaptation (UDA…
Scalable Attack on Graph Data by Injecting Vicious Nodes
Jihong Wang, Minnan Luo, Fnu Suya +3
Recent studies have shown that graph convolution networks (GCNs) are vulnerable to carefully designed attacks, which aim to cause misclassification of a specific node on the graph…
Self-Supervised Graph Representation Learning via Global Context Prediction
Zhen Peng, Yixiang Dong, Minnan Luo +2
To take full advantage of fast-growing unlabeled networked data, this paper introduces a novel self-supervised strategy for graph representation learning by exploiting natural supe…
Graph Representation Learning via Graphical Mutual Information Maximization
Zhen Peng, Wenbing Huang, Minnan Luo +4
The richness in the content of various information networks such as social networks and communication networks provides the unprecedented potential for learning high-quality expres…