Search Results for author: Chaoran Cui

Found 6 papers, 5 papers with code

Do We Fully Understand Students' Knowledge States? Identifying and Mitigating Answer Bias in Knowledge Tracing

1 code implementation15 Aug 2023 Chaoran Cui, Hebo Ma, Chen Zhang, Chunyun Zhang, Yumo Yao, Meng Chen, Yuling Ma

Existing models tend to memorize the answer bias as a shortcut for achieving high prediction performance in KT, thereby failing to fully understand students' knowledge states.

counterfactual Counterfactual Reasoning +1

DGEKT: A Dual Graph Ensemble Learning Method for Knowledge Tracing

1 code implementation23 Nov 2022 Chaoran Cui, Yumo Yao, Chunyun Zhang, Hebo Ma, Yuling Ma, Zhaochun Ren, Chen Zhang, James Ko

Knowledge tracing aims to trace students' evolving knowledge states by predicting their future performance on concept-related exercises.

Ensemble Learning Knowledge Distillation +1

Sequential Multi-task Learning with Task Dependency for Appeal Judgment Prediction

no code implementations9 Mar 2022 Lianxin Song, Xiaohui Han, Guangqi Liu, Wentong Wang, Chaoran Cui, Yilong Yin

SMAJudge utilizes two sequential components to model the complete proceeding from the lower court to the appellate court and employs an attention mechanism to make the prediction more explainable, which handles the challenges of AJP effectively.

Multi-Task Learning

Tri-Branch Convolutional Neural Networks for Top-$k$ Focused Academic Performance Prediction

1 code implementation22 Jul 2021 Chaoran Cui, Jian Zong, Yuling Ma, Xinhua Wang, Lei Guo, Meng Chen, Yilong Yin

Academic performance prediction aims to leverage student-related information to predict their future academic outcomes, which is beneficial to numerous educational applications, such as personalized teaching and academic early warning.

Towards Accurate and Robust Domain Adaptation under Noisy Environments

1 code implementation27 Apr 2020 Zhongyi Han, Xian-Jin Gui, Chaoran Cui, Yilong Yin

In non-stationary environments, learning machines usually confront the domain adaptation scenario where the data distribution does change over time.

Unsupervised Domain Adaptation

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