Knowledge-Jailbreak Dataset

该数据集是一个大规模的数据集，包含了12,974个知识逃逸对，用于评估大型语言模型（LLM）在运用领域知识时的安全性。数据集分为已知领域和未知领域，其中未知领域包含6个领域的91个数据点，用于测试。已知领域则按照8:2的比例分为训练集和测试集。该数据集的任务是通过知识驱动的逃逸生成来评估LLM的安全性。

This is a large-scale dataset comprising 12,974 knowledge escape pairs, developed to evaluate the safety of Large Language Models (LLMs) when leveraging domain-specific knowledge. The dataset is divided into known domains and unknown domains. The unknown domains include 91 data points across 6 domains for testing LLMs. The known domains are split into training and test sets at an 8:2 ratio. The task of this dataset is to evaluate the safety of LLMs via knowledge-driven escape generation.