9 citations · 15 across the 7 of their papers we have counts for
7 papers
Do We Fully Understand Students' Knowledge States? Identifying and Mitigating Answer Bias in Knowledge Tracing
Chaoran Cui, Hebo Ma, Chen Zhang +4
Knowledge tracing (KT) aims to monitor students' evolving knowledge states through their learning interactions with concept-related questions, and can be indirectly evaluated by pr…
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…
Sequential Multi-task Learning with Task Dependency for Appeal Judgment Prediction
Lianxin Song, Xiaohui Han, Guangqi Liu +3
Legal Judgment Prediction (LJP) aims to automatically predict judgment results, such as charges, relevant law articles, and the term of penalty. It plays a vital role in legal assi…
Tri-Branch Convolutional Neural Networks for Top- Focused Academic Performance Prediction
Chaoran Cui, Jian Zong, Yuling Ma +4
Academic performance prediction aims to leverage student-related information to predict their future academic outcomes, which is beneficial to numerous educational applications, su…
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…
Towards Accurate and Robust Domain Adaptation under Noisy Environments
Zhongyi Han, Xian-Jin Gui, Chaoran Cui +1
In non-stationary environments, learning machines usually confront the domain adaptation scenario where the data distribution does change over time. Previous domain adaptation work…