30 citations · 77 across the 12 of their papers we have counts for
5 papers · 1 filter
Advancing Molecular Graph-Text Pre-training via Fine-grained Alignment
Yibo Li, Yuan Fang, Mengmei Zhang +1
Understanding molecular structure and related knowledge is crucial for scientific research. Recent studies integrate molecular graphs with their textual descriptions to enhance mol…
Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?
Zhongjian Zhang, Xiao Wang, Huichi Zhou +4
Graph neural networks (GNNs) are vulnerable to adversarial attacks, especially for topology perturbations, and many methods that improve the robustness of GNNs have received consid…
Minimum Topology Attacks for Graph Neural Networks
Mengmei Zhang, Xiao Wang, Chuan Shi +3
With the great popularity of Graph Neural Networks (GNNs), their robustness to adversarial topology attacks has received significant attention. Although many attack methods have be…
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks
Mengmei Zhang, Mingwei Sun, Peng Wang +6
Large language models (LLMs) like ChatGPT, exhibit powerful zero-shot and instruction-following capabilities, have catalyzed a revolutionary transformation across diverse fields, e…
Endowing Pre-trained Graph Models with Provable Fairness
Zhongjian Zhang, Mengmei Zhang, Yue Yu +3
Pre-trained graph models (PGMs) aim to capture transferable inherent structural properties and apply them to different downstream tasks. Similar to pre-trained language models, PGM…