SOURCE-LINKED INTELLIGENCE

Robust Workflow Generation via Adversarial Learning for Audio Deepfake Detection

arXiv · Artificial Intelligence · article · Sep 17, 2026 · UTC

The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security risks in practical applications. While existing detection methods achieve strong performance under controlled conditions, they often fail to generalize under real-world perturbations and corruptions. In this paper, we propose ROGUE, a framework that dynamically constructs robust detection workflows by orchestrating multiple detection tools. ROGUE formulates workflow generation as a sequential decision-making problem and introduces a dual-agent par

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recordType: paper
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Evidence & attribution

arXiv · Artificial Intelligence · 2026-09-17T11:14:58.000Z
arXiv · AI, language, vision and robotics · 2026-09-17T11:14:58.000Z

First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.