Yanjun Pu
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View article: Compromising Embodied Agents with Contextual Backdoor Attacks
Compromising Embodied Agents with Contextual Backdoor Attacks Open
Large language models (LLMs) have transformed the development of embodied intelligence. By providing a few contextual demonstrations, developers can utilize the extensive internal knowledge of LLMs to effortlessly translate complex tasks d…
View article: ELAKT: Enhancing Locality for Attentive Knowledge Tracing
ELAKT: Enhancing Locality for Attentive Knowledge Tracing Open
Knowledge tracing models based on deep learning can achieve impressive predictive performance by leveraging attention mechanisms. However, there still exist two challenges in attentive knowledge tracing (AKT): First, the mechanism of class…
View article: GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy
GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy Open
Graph neural networks (GNNs) have shown advantages in graph-based analysis tasks. However, most existing methods have the homogeneity assumption and show poor performance on heterophilic graphs, where the linked nodes have dissimilar featu…
View article: CLGT: A Graph Transformer for Student Performance Prediction in Collaborative Learning
CLGT: A Graph Transformer for Student Performance Prediction in Collaborative Learning Open
Modeling and predicting the performance of students in collaborative learning paradigms is an important task. Most of the research presented in literature regarding collaborative learning focuses on the discussion forums and social learnin…
View article: CLGT: A Graph Transformer for Student Performance Prediction in Collaborative Learning
CLGT: A Graph Transformer for Student Performance Prediction in Collaborative Learning Open
Modeling and predicting the performance of students in collaborative learning paradigms is an important task. Most of the research presented in literature regarding collaborative learning focuses on the discussion forums and social learnin…
View article: EAKT: Embedding Cognitive Framework with Attention for Interpretable Knowledge Tracing
EAKT: Embedding Cognitive Framework with Attention for Interpretable Knowledge Tracing Open
Recently, deep neural network-based cognitive models such as deep knowledge tracing have been introduced into the field of learning analytics and educational data mining. Despite an accurate predictive performance of such models, it is cha…
View article: HELP-DKT: An Interpretable Cognitive Model of How Students Learn Programming Based on Deep Knowledge Tracing
HELP-DKT: An Interpretable Cognitive Model of How Students Learn Programming Based on Deep Knowledge Tracing Open
Student cognitive models are playing an essential role in intelligent online tutoring for programming courses. These models capture students' learning interactions and store them in the form of a set of binary responses, thereby failing to…