9 citations · 19 across the 5 of their papers we have counts for
5 papers
DGEKT: A Dual Graph Ensemble Learning Method for Knowledge Tracing
Chaoran Cui, Yumo Yao, Chunyun Zhang +5
Knowledge tracing aims to trace students' evolving knowledge states by predicting their future performance on concept-related exercises. Recently, some graph-based models have been…
A Robust Contrastive Alignment Method For Multi-Domain Text Classification
Xuefeng Li, Hao Lei, Liwen Wang +5
Multi-domain text classification can automatically classify texts in various scenarios. Due to the diversity of human languages, texts with the same label in different domains may…
Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction
Chaoran Cui, Xiaojie Li, Juan Du +4
Predicting the future price trends of stocks is a challenging yet intriguing problem given its critical role to help investors make profitable decisions. In this paper, we present…
Reinforced Generative Adversarial Network for Abstractive Text Summarization
Tianyang Xu, Chunyun Zhang
Sequence-to-sequence models provide a viable new approach to generative summarization, allowing models that are no longer limited to simply selecting and recombining sentences from…
Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs
Pengda Qin, Xin Wang, Wenhu Chen +3
Large-scale knowledge graphs (KGs) are shown to become more important in current information systems. To expand the coverage of KGs, previous studies on knowledge graph completion…