3 citations · 5 across the 4 of their papers we have counts for
4 papers
Towards Explainable Vulnerability Detection with Large Language Models
Qiheng Mao, Zhenhao Li, Xing Hu +3
Software vulnerabilities pose significant risks to the security and integrity of software systems. Although prior studies have explored vulnerability detection using deep learning…
Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques
Qiheng Mao, Zemin Liu, Chenghao Liu +2
The integration of Large Language Models (LLMs) with Graph Representation Learning (GRL) marks a significant evolution in analyzing complex data structures. This collaboration harn…
ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt
Mouxiang Chen, Zemin Liu, Chenghao Liu +3
Recent research has demonstrated the efficacy of pre-training graph neural networks (GNNs) to capture the transferable graph semantics and enhance the performance of various downst…
HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer
Qiheng Mao, Zemin Liu, Chenghao Liu +1
Recent studies have highlighted the limitations of message-passing based graph neural networks (GNNs), e.g., limited model expressiveness, over-smoothing, over-squashing, etc. To a…