33 citations · 51 across the 6 of their papers we have counts for
6 papers
Graph Learning and Its Advancements on Large Language Models: A Holistic Survey
Shaopeng Wei, Jun Wang, Yu Zhao +6
Graph learning is a prevalent domain that endeavors to learn the intricate relationships among nodes and the topological structure of graphs. Over the years, graph learning has tra…
ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling
Yu Guo, Zhilong Xie, Xingyan Chen +7
Natural language understanding (NLU) has two core tasks: intent classification and slot filling. The success of pre-training language models resulted in a significant breakthrough…
Combining Intra-Risk and Contagion Risk for Enterprise Bankruptcy Prediction Using Graph Neural Networks
Yu Zhao, Shaopeng Wei, Yu Guo +6
Predicting the bankruptcy risk of small and medium-sized enterprises (SMEs) is an important step for financial institutions when making decisions about loans. Existing studies in b…
Learning Bi-typed Multi-relational Heterogeneous Graph via Dual Hierarchical Attention Networks
Yu Zhao, Shaopeng Wei, Huaming Du +5
Bi-type multi-relational heterogeneous graph (BMHG) is one of the most common graphs in practice, for example, academic networks, e-commerce user behavior graph and enterprise know…
Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks
Yu Zhao, Huaming Du, Ying Liu +6
Stock Movement Prediction (SMP) aims at predicting listed companies' stock future price trend, which is a challenging task due to the volatile nature of financial markets. Recent f…
Deep Keyphrase Completion
Yu Zhao, Jia Song, Huali Feng +4
Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text r…