LLark: A Multimodal Instruction-Following Language Model for Music

research work·research paper·active

Research work examining music/audio understanding.

Recorded facts

Official site	https://arxiv.org/abs/2310.07160 ↗
Geography	Global
arxiv	2310.07160
venue	ICML camera-ready version
authors	Josh Gardner; Simon Durand; Daniel Stoller; Rachel M. Bittner
methods	language modeling
code urls	https://github.com/spotify-research/llark
demo urls	unknown
exact title	LLark: A Multimodal Instruction-Following Language Model for Music
project urls	https://bit.ly/llark
original title	unknown
citation counts	unknown
research topics	music/audio understanding
peer review status	venue or acceptance claim recorded in arXiv comment
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	Google Research
publication or preprint date	2023-10-11
abstract level neutral summary	The work studies 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.