1 citations · 1 across the 5 of their papers we have counts for
5 papers
Improved Generation of Adversarial Examples Against Safety-aligned LLMs
Qizhang Li, Yiwen Guo, Wangmeng Zuo +1
Adversarial prompts generated using gradient-based methods exhibit outstanding performance in performing automatic jailbreak attacks against safety-aligned LLMs. Nevertheless, due…
Intrusion Detection at Scale with the Assistance of a Command-line Language Model
Jiongliang Lin, Yiwen Guo, Hao Chen
Intrusion detection is a long standing and crucial problem in security. A system capable of detecting intrusions automatically is on great demand in enterprise security solutions.…
UniTSyn: A Large-Scale Dataset Capable of Enhancing the Prowess of Large Language Models for Program Testing
Yifeng He, Jiabo Huang, Yuyang Rong +3
The remarkable capability of large language models (LLMs) in generating high-quality code has drawn increasing attention in the software testing community. However, existing code L…
Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly
Qizhang Li, Yiwen Guo, Wangmeng Zuo +1
The adversarial vulnerability of deep neural networks (DNNs) has drawn great attention due to the security risk of applying these models in real-world applications. Based on transf…
The Program Testing Ability of Large Language Models for Code
Weimin Xiong, Yiwen Guo, Hao Chen
Recent development of large language models (LLMs) for code like CodeX and CodeT5+ demonstrates tremendous promise in achieving code intelligence. Their ability of synthesizing cod…