Xunlong Zou — accepted AI-conference papers

2025

AudioBench: A Universal Benchmark for Audio Large Language Models

Bin Wang, Xunlong Zou, Geyu Lin, Shuo Sun, Zhuohan Liu, Wenyu Zhang +3

NAACL 2025long

We introduce AudioBench, a universal benchmark designed to evaluate Audio Large Language Models (AudioLLMs). It encompasses 8 distinct tasks and 26 datasets, among which, 7 are newly proposed datasets. The evaluation targets three main aspects: speech understanding, audio scene understanding, and vo…

Cited by 44 Source ↗PDF ↗code ↗Scholar ↗

2025

MoWE-Audio: Multitask AudioLLMs with Mixture of Weak Encoders

Wenyu Zhang, Shuo Sun, Bin Wang, Xunlong Zou, Zhuohan Liu, Yingxu He +3

ICASSP 2025accepted

The rapid advancements in large language models (LLMs) have significantly enhanced natural language processing capabilities, facilitating the development of AudioLLMs that process and understand speech and audio inputs alongside text. Existing AudioLLMs typically combine a pre-trained audio encoder…

Cited by 0 Source ↗Scholar ↗