12 citations · 21 across the 15 of their papers we have counts for
15 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…
AgentCAT: Simulating Computerized Adaptive Testing via Multi-Agent Large Language Models
Weiyuan Zhou, Haiping Ma, Xiaoshan Yu +3
Computerized Adaptive Testing (CAT), as a key technology for personalized education, aims to accurately assess examinee proficiency by retrieving exercises dynamically matching cur…
Trustworthy Intelligent Education: A Systematic Perspective on Progress, Challenges, and Future Directions
Xiaoshan Yu, Shangshang Yang, Ziwen Wang +2
In recent years, trustworthiness has garnered increasing attention and exploration in the field of intelligent education, due to the inherent sensitivity of educational scenarios,…
Breaking Robustness Barriers in Cognitive Diagnosis: A One-Shot Neural Architecture Search Perspective
Ziwen Wang, Shangshang Yang, Xiaoshan Yu +2
With the advancement of network technologies, intelligent tutoring systems (ITS) have emerged to deliver increasingly precise and tailored personalized learning services. Cognitive…
PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing
Xiaoshan Yu, Ziwei Huang, Shangshang Yang +3
With the rapid advancement of intelligent education, Computerized Adaptive Testing (CAT) has attracted increasing attention by integrating educational psychology with deep learning…
FedCD: A Fairness-aware Federated Cognitive Diagnosis Framework
Shangshang Yang, Jialin Han, Xiaoshan Yu +5
Online intelligent education platforms have generated a vast amount of distributed student learning data. This influx of data presents opportunities for cognitive diagnosis (CD) to…
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…
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…
EQ-Net: Elastic Quantization Neural Networks
Ke Xu, Lei Han, Ye Tian +2
Current model quantization methods have shown their promising capability in reducing storage space and computation complexity. However, due to the diversity of quantization forms s…
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…