arXiv Machine Learning By Sepehr Dehdashtian, Jacob H Seidman, Vishnu N Boddeti, Gaurav Bharaj

FoeGlass: Simple In-Context Learning Is Enough for Red Teaming Audio Deepfake Detectors

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arXiv:2606. 05101v1 Announce Type: cross Abstract: Audio deepfake detection (ADD) models are critical for countering the malicious use of text-to-speech (TTS) models.

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arXiv AI
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ARENA: Automated Red-Teaming for Large Audio Language Models

arXiv:2608. 15578v1 Announce Type: cross Abstract: Large audio-language models (LALMs) make it possible to interact with language models through speech, music, and environmental sound, but they also introduce a safety surface that is difficult to expose with text-only red-teaming.

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Spectral Masking and Interpolation Attack (SMIA): A Black-box Adversarial Attack against Voice Authentication and Anti-Spoofing Systems

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arXiv AI
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Teffic-Audio: Tell Fact from Fiction

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