Large Language Model

Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models
(USENIX Security 2024) This is a systematic study on jailbreak attacks against commercial large language model (LLM) systems. We analyzed existing jailbreak prompts, examined their contributing factors, and conducted user studies to explore human behavioral patterns during jailbreak attempts.
Zhiyuan Yu, Xiaogeng Liu, Shunning Liang, Zach Cameron, Chaowei Xiao, Ning Zhang
Code Dataset Distinguished Paper Award Artifact Badges - Available, Functional, Results Reproduced Press DOI Website PDF
Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
(ICML 2023) This is an intersting and timely research investigating the potential IP violation of outputs from LLM-based code generation models (such as GitHub Copilot). We developed the first benchmark toolkit to quantify the extent of IP infringement of LLM models, which has been used by companies like Microsoft, and we also proposed several mitigation methods.
Zhiyuan Yu, Yuhao Wu, Ning Zhang, Chenguang Wang, Yevgeniy Vorobeychik, Chaowei Xiao
Code Dataset Website DOI Press PDF
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models