1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 1 cited
BiasJailbreak:Analyzing Ethical Biases and Jailbreak Vulnerabilities in Large Language Models
Isack Lee, Haebin Seong
Although large language models (LLMs) demonstrate impressive proficiency in various tasks, they present potential safety risks, such as `jailbreaks', where malicious inputs can coe…
cs.CL2024
WalledEval: A Comprehensive Safety Evaluation Toolkit for Large Language Models
Prannaya Gupta, Le Qi Yau, Hao Han Low +8
WalledEval is a comprehensive AI safety testing toolkit designed to evaluate large language models (LLMs). It accommodates a diverse range of models, including both open-weight and…