JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

arXiv:2404.01318v1 Announce Type: cross
Abstract: Jailbreak attacks cause large language models (LLMs) to generate harmful, unethical, or otherwise objectionable content. Evaluating these attacks presents a number of challenges, which the current collection of benchmarks and evaluation techniques do not adequately address. First, there is no clear standard of practice regarding jailbreaking evaluation. Second, existing works compute costs and success rates in incomparable ways. And third, numerous works are not reproducible, as they withhold adversarial prompts, involve closed-source code, or rely …

abstract arxiv attacks benchmark benchmarks challenges clear collection cs.cr cs.lg current evaluation generate jailbreak jailbreaking language language models large language large language models llms practice robustness standard type