THREAT uses coordinated LLMs in an iterative optimization loop to generate jailbreak prompts that achieve higher success rates and lower detection rates than previous methods across tested models and datasets.
In: Proc of the Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track)
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Adversarial Reframing: A Framework for Targeted Generation in Language Models
THREAT uses coordinated LLMs in an iterative optimization loop to generate jailbreak prompts that achieve higher success rates and lower detection rates than previous methods across tested models and datasets.