LLark: A Multimodal Instruction-Following Language Model for Music

research work·research paper·active

Research work examining music/audio understanding.

Verified facts

Official sitehttps://arxiv.org/abs/2310.07160
GeographyGlobal
arxiv2310.07160
venueICML camera-ready version
authorsJosh Gardner; Simon Durand; Daniel Stoller; Rachel M. Bittner
methodslanguage modeling
code urlshttps://github.com/spotify-research/llark
demo urlsunknown
exact titleLLark: A Multimodal Instruction-Following Language Model for Music
project urlshttps://bit.ly/llark
original titleunknown
citation countsunknown
research topicsmusic/audio understanding
peer review statusvenue or acceptance claim recorded in arXiv comment
disclosed conflictsunknown
stated contributionPresents or evaluates the system, method, benchmark, or analysis identified in the paper title.
us market scope basisIncluded as a materially relevant public research artifact in the US-facing AI-music ecosystem; direct affiliation varies.
funding acknowledgementsunknown
affiliations at publicationGoogle Research
publication or preprint date2023-10-11
abstract level neutral summaryThe work studies music/audio understanding; methods and evaluation details are in the official abstract.
datasets benchmarks models tools usedunknown
correction withdrawal retraction statusNo withdrawal marker observed in captured arXiv metadata.

Current

affiliated withGoogle Research 2023-10-11now

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