FoeGlass is a black-box red-teaming method that leverages LLM in-context learning with diversity-based prompting to generate adversarial audio samples, raising false negative rates of ADD models by up to 94% over baselines.
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FoeGlass: Simple In-Context Learning Is Enough for Red Teaming Audio Deepfake Detectors
FoeGlass is a black-box red-teaming method that leverages LLM in-context learning with diversity-based prompting to generate adversarial audio samples, raising false negative rates of ADD models by up to 94% over baselines.