3 citations · 5 across the 27 of their papers we have counts for
4 papers · 1 filter
CS-Eval: A Comprehensive Large Language Model Benchmark for CyberSecurity
Zhengmin Yu, Jiutian Zeng, Siyi Chen +7
Over the past year, there has been a notable rise in the use of large language models (LLMs) for academic research and industrial practices within the cybersecurity field. However,…
SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models
Zonghao Ying, Aishan Liu, Siyuan Liang +5
Multimodal Large Language Models (MLLMs) are showing strong safety concerns (e.g., generating harmful outputs for users), which motivates the development of safety evaluation bench…
Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks
Zonghao Ying, Aishan Liu, Xianglong Liu +1
The recent release of GPT-4o has garnered widespread attention due to its powerful general capabilities. While its impressive performance is widely acknowledged, its safety aspects…
Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt
Zonghao Ying, Aishan Liu, Tianyuan Zhang +4
In the realm of large vision language models (LVLMs), jailbreak attacks serve as a red-teaming approach to bypass guardrails and uncover safety implications. Existing jailbreaks pr…