21 citations · 36 across the 11 of their papers we have counts for
11 papers
NameGuess: Column Name Expansion for Tabular Data
Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan +3
Recent advances in large language models have revolutionized many sectors, including the database industry. One common challenge when dealing with large volumes of tabular data is…
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang +6
How can we learn effective node representations on textual graphs? Graph Neural Networks (GNNs) that use Language Models (LMs) to encode textual information of graphs achieve state…
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization
Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis +7
Graph Neural Networks (GNNs) are currently dominating in modeling graph-structure data, while their high reliance on graph structure for inference significantly impedes them from w…
MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System
Liangwei Yang, Shen Wang, Jibing Gong +4
Knowledge graph (KG) enhanced recommendation has demonstrated improved performance in the recommendation system (RecSys) and attracted considerable research interest. Recently the…
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation
Ziwei Fan, Zhiwei Liu, Lei Zheng +2
The sequential patterns within the user interactions are pivotal for representing the user's preference and capturing latent relationships among items. The recent advancements of s…
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
Shen Wang, Jibing Gong, Jinlong Wang +4
Massive open online courses are becoming a modish way for education, which provides a large-scale and open-access learning opportunity for students to grasp the knowledge. To attra…
Generative Temporal Link Prediction via Self-tokenized Sequence Modeling
Yue Wang, Chenwei Zhang, Shen Wang +4
We formalize networks with evolving structures as temporal networks and propose a generative link prediction model, Generative Link Sequence Modeling (GLSM), to predict future link…
Heterogeneous Graph Matching Networks
Shen Wang, Zhengzhang Chen, Xiao Yu +7
Information systems have widely been the target of malware attacks. Traditional signature-based malicious program detection algorithms can only detect known malware and are prone t…
Adversarial Defense Framework for Graph Neural Network
Shen Wang, Zhengzhang Chen, Jingchao Ni +4
Graph neural network (GNN), as a powerful representation learning model on graph data, attracts much attention across various disciplines. However, recent studies show that GNN is…
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification
Shen Wang, Zhengzhang Chen, Ding Li +6
Program or process is an integral part of almost every IT/OT system. Can we trust the identity/ID (e.g., executable name) of the program? To avoid detection, malware may disguise i…
Deep Co-investment Network Learning for Financial Assets
Yue Wang, Chenwei Zhang, Shen Wang +3
Most recent works model the market structure of the stock market as a correlation network of the stocks. They apply pre-defined patterns to extract correlation information from the…