47 citations · 113 across the 11 of their papers we have counts for
11 papers
Learning to Generate Secure Code via Token-Level Rewards
Jiazheng Quan, Xiaodong Li, Bin Wang +5
Large language models (LLMs) have demonstrated strong capabilities in code generation, yet they remain prone to producing security vulnerabilities. Existing approaches commonly suf…
Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs
Tianyu Zhang, Chengbin Hou, Rui Jiang +4
Node Importance Estimation (NIE) is a task of inferring importance scores of the nodes in a graph. Due to the availability of richer data and knowledge, recent research interests o…
Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews
Chengbin Hou, Xinyu Lin, Hanhui Huang +4
Identification of fossil species is crucial to evolutionary studies. Recent advances from deep learning have shown promising prospects in fossil image identification. However, the…
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Bingzhe Wu, Jintang Li, Junchi Yu +17
Deep graph learning has achieved remarkable progresses in both business and scientific areas ranging from finance and e-commerce, to drug and advanced material discovery. Despite t…
Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack
Jintang Li, Bingzhe Wu, Chengbin Hou +5
Deep graph learning (DGL) has achieved remarkable progress in both business and scientific areas ranging from finance and e-commerce to drug and advanced material discovery. Despit…
Adaptive Hypergraph Convolutional Network for No-Reference 360-degree Image Quality Assessment
Jun Fu, Chen Hou, Wei Zhou +2
In no-reference 360-degree image quality assessment (NR 360IQA), graph convolutional networks (GCNs), which model interactions between viewports through graphs, have achieved impre…