60 citations · 111 across the 12 of their papers we have counts for
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eess.AS2023★ 23 cited
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
Yunfei Chu, Jin Xu, Xiaohuan Zhou +5
Recently, instruction-following audio-language models have received broad attention for audio interaction with humans. However, the absence of pre-trained audio models capable of h…
cs.SD2023★ 18 cited
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
Zhihao Du, Jiaming Wang, Qian Chen +12
Generative Pre-trained Transformer (GPT) models have achieved remarkable performance on various natural language processing tasks, and have shown great potential as backbones for a…