3 papers
cs.SD2026
SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models
Yuanhe Zhang, Jiayu Tian, Yibo Zhang +5
Large Audio Language Models (LALMs) have been widely applied in real-time scenarios, such as in-car assistants and online meeting comprehension. In practice, audio inputs are often…
cs.SD2026
RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios
Yibo Zhang, Liang Lin, Kaiwen Luo +8
While Audio Large Models (ALMs) have achieved remarkable proficiency, their robustness remains brittle in real-world deployment. Existing evaluations largely rely on synthetic Gaus…
cs.SD2025
ERIS: Evolutionary Real-world Interference Scheme for Jailbreaking Audio Large Models
Yibo Zhang, Liang Lin
Existing Audio Large Models (ALMs) alignment focuses on clean inputs, neglecting security risks in complex environments. We propose ERIS, a framework transforming real-world interf…