1 citations · 1 across the 8 of their papers we have counts for
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Investigating Safety Vulnerabilities of Large Audio-Language Models Under Speaker Emotional Variations
Bo-Han Feng, Chien-Feng Liu, Yu-Hsuan Li Liang +9
Large audio-language models (LALMs) extend text-based LLMs with auditory understanding, offering new opportunities for multimodal applications. While their perception, reasoning, a…
SAKE: Towards Editing Auditory Attribute Knowledge of Large Audio-Language Models
Chih-Kai Yang, Yen-Ting Piao, Tzu-Wen Hsu +8
Knowledge editing enables targeted updates without retraining, but prior work focuses on textual or visual facts, leaving abstract auditory perceptual knowledge underexplored. We i…
Detecting the Undetectable: Assessing the Efficacy of Current Spoof Detection Methods Against Seamless Speech Edits
Sung-Feng Huang, Heng-Cheng Kuo, Zhehuai Chen +6
Neural speech editing advancements have raised concerns about their misuse in spoofing attacks. Traditional partially edited speech corpora primarily focus on cut-and-paste edits,…