12 citations · 20 across the 10 of their papers we have counts for
10 papers
ButterMamba: Butterworth-Enhanced Spatial-Temporal Mamba for Efficient Traffic Flow Prediction
Limiao Zhang, Yuhui Lu, Jie Gao +3
Accurate traffic flow prediction is fundamental to intelligent transportation systems, playing a pivotal role in urban mobility optimization and smart city development. While Graph…
Diffusion-Inspired Cold Start with Sufficient Prior in Computerized Adaptive Testing
Haiping Ma, Aoqing Xia, Changqian Wang +2
Computerized Adaptive Testing (CAT) aims to select the most appropriate questions based on the examinee's ability and is widely used in online education. However, existing CAT syst…
DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
Shangshang Yang, Mingyang Chen, Ziwen Wang +4
Existing graph learning-based cognitive diagnosis (CD) methods have made relatively good results, but their student, exercise, and concept representations are learned and exchanged…
DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation
Xiaoshan Yu, Chuan Qin, Qi Zhang +4
The rapid development of online recruitment platforms has created unprecedented opportunities for job seekers while concurrently posing the significant challenge of quickly and acc…
RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes
Xiaoshan Yu, Chuan Qin, Dazhong Shen +4
In the realm of education, both independent learning and group learning are esteemed as the most classic paradigms. The former allows learners to self-direct their studies, while t…
Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networks
Shangshang Yang, Linrui Qin, Xiaoshan Yu
In the realm of intelligent education, cognitive diagnosis plays a crucial role in subsequent recommendation tasks attributed to the revealed students' proficiency in knowledge con…
ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness
Yunfei Zhang, Chuan Qin, Dazhong Shen +4
During the past few decades, cognitive diagnostics modeling has attracted increasing attention in computational education communities, which is capable of quantifying the learning…
Enhancing Cognitive Diagnosis using Un-interacted Exercises: A Collaboration-aware Mixed Sampling Approach
Haiping Ma, Changqian Wang, Hengshu Zhu +3
Cognitive diagnosis is a crucial task in computational education, aimed at evaluating students' proficiency levels across various knowledge concepts through exercises. Current mode…
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Shangshang Yang, Xiaoshan Yu, Ye Tian +3
Knowledge tracing (KT) aims to trace students' knowledge states by predicting whether students answer correctly on exercises. Despite the excellent performance of existing Transfor…
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Search
Shangshang Yang, Haiping Ma, Cheng Zhen +4
Cognitive diagnosis plays a vital role in modern intelligent education platforms to reveal students' proficiency in knowledge concepts for subsequent adaptive tasks. However, due t…