MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark

research work·benchmark study·active

Research work examining evaluation benchmark, music/audio understanding.

Recorded facts

Official site	https://arxiv.org/abs/2410.19168 ↗
Geography	Global
arxiv	2410.19168
venue	Project Website: https://sakshi113.github.io/mmau_homepage/
authors	S Sakshi; Utkarsh Tyagi; Sonal Kumar; Ashish Seth; Ramaneswaran Selvakumar; Oriol Nieto; Ramani Duraiswami; Sreyan Ghosh; Dinesh Manocha
methods	benchmark evaluation; language modeling
code urls	unknown
demo urls	unknown
exact title	MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark
project urls	https://sakshi113.github.io/mmau_homepage/
original title	unknown
citation counts	unknown
research topics	evaluation benchmark; music/audio understanding
peer review status	not established from abstract metadata
disclosed conflicts	unknown
stated contribution	Presents or evaluates the system, method, benchmark, or analysis identified in the paper title.
us market scope basis	Included as a materially relevant public research artifact in the US-facing AI-music ecosystem; direct affiliation varies.
funding acknowledgements	unknown
affiliations at publication	unknown
publication or preprint date	2024-10-24
abstract level neutral summary	The work studies evaluation benchmark, music/audio understanding; methods and evaluation details are in the official abstract.
datasets benchmarks models tools used	unknown
correction withdrawal retraction status	No withdrawal marker observed in captured arXiv metadata.