6 papers
Resurfacing Paralinguistic Awareness in Large Audio Language Models
Hao Yang, Minghan Wang, Tongtong Wu +3
Large Audio Language Models (LALMs) have expanded the interaction with human to speech modality, which introduces great interactive potential, due to the paralinguistic cues implic…
Continual Speech Learning with Fused Speech Features
Guitao Wang, Jinming Zhao, Hao Yang +3
Rapid growth in speech data demands adaptive models, as traditional static methods fail to keep pace with dynamic and diverse speech information. We introduce continuous speech lea…
Reshaping Representation Space to Balance the Safety and Over-rejection in Large Audio Language Models
Hao Yang, Lizhen Qu, Ehsan Shareghi +1
Large Audio Language Models (LALMs) have extended the capabilities of Large Language Models (LLMs) by enabling audio-based human interactions. However, recent research has revealed…
Audio Is the Achilles' Heel: Red Teaming Audio Large Multimodal Models
Hao Yang, Lizhen Qu, Ehsan Shareghi +1
Large Multimodal Models (LMMs) have demonstrated the ability to interact with humans under real-world conditions by combining Large Language Models (LLMs) and modality encoders to…
Double Mixture: Towards Continual Event Detection from Speech
Jingqi Kang, Tongtong Wu, Jinming Zhao +6
Speech event detection is crucial for multimedia retrieval, involving the tagging of both semantic and acoustic events. Traditional ASR systems often overlook the interplay between…
Jigsaw Puzzles: Splitting Harmful Questions to Jailbreak Large Language Models
Hao Yang, Lizhen Qu, Ehsan Shareghi +1
Large language models (LLMs) have exhibited outstanding performance in engaging with humans and addressing complex questions by leveraging their vast implicit knowledge and robust…