1 citations · 1 across the 4 of their papers we have counts for
4 papers
Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis
Zhonghao Zhan, Huichi Zhou, Hamed Haddadi
Graph Neural Networks (GNNs) show great promise for Network Intrusion Detection Systems (NIDS), particularly in IoT environments, but suffer performance degradation due to distribu…
EfficientLLM: Efficiency in Large Language Models
Zhengqing Yuan, Weixiang Sun, Yixin Liu +13
Large Language Models (LLMs) have driven significant progress, yet their growing parameter counts and context windows incur prohibitive compute, energy, and monetary costs. We intr…
Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge
Wenhan Mu, Ling Xu, Shuren Pei +2
The widespread adoption of code language models in software engineering tasks has exposed vulnerabilities to adversarial attacks, especially the identifier substitution attacks. Al…
MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
Fangyuan Zhang, Huichi Zhou, Shuangjiao Li +1
Deep neural networks have been proven to be vulnerable to adversarial examples and various methods have been proposed to defend against adversarial attacks for natural language pro…