1 citations · 1 across the 4 of their papers we have counts for
5 papers
Robust Workflow Generation via Adversarial Learning for Audio Deepfake Detection
Xiang Li, Pin-Yu Chen, Wenqi Wei
The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security risks in practical applications…
Aegis: Towards Governance, Integrity, and Security of AI Voice Agents
Xiang Li, Pin-Yu Chen, Wenqi Wei
With the rapid advancement and adoption of Audio Large Language Models (ALLMs), voice agents are now being deployed in high-stakes domains such as banking, customer service, and IT…
Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption
Xiang Li, Pin-Yu Chen, Wenqi Wei
Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio deepfakes are particularly alarming d…
Where are we in audio deepfake detection? A systematic analysis over generative and detection models
Xiang Li, Pin-Yu Chen, Wenqi Wei
Recent advances in Text-to-Speech (TTS) and Voice-Conversion (VC) using generative Artificial Intelligence (AI) technology have made it possible to generate high-quality and realis…
AutoJailbreak: Exploring Jailbreak Attacks and Defenses through a Dependency Lens
Lin Lu, Hai Yan, Zenghui Yuan +4
Jailbreak attacks in large language models (LLMs) entail inducing the models to generate content that breaches ethical and legal norm through the use of malicious prompts, posing a…