Feb. 8, 2024, 5:10 a.m. | Lijun Li Bowen Dong Ruohui Wang Xuhao Hu Wangmeng Zuo Dahua Lin Yu Qiao Jing Shao

cs.CR updates on arXiv.org arxiv.org

In the rapidly evolving landscape of Large Language Models (LLMs), ensuring robust safety measures is paramount. To meet this crucial need, we propose \emph{SALAD-Bench}, a safety benchmark specifically designed for evaluating LLMs, attack, and defense methods. Distinguished by its breadth, SALAD-Bench transcends conventional benchmarks through its large scale, rich diversity, intricate taxonomy spanning three levels, and versatile functionalities.SALAD-Bench is crafted with a meticulous array of questions, from standard queries to complex ones enriched with attack, defense modifications and …

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