Local Multimodal Music Alignment from Global Supervision

research work·research paper·active

Research work examining music retrieval, music/audio understanding.

Recorded facts

Official site	https://arxiv.org/abs/2607.10023 ↗
Geography	Global
arxiv	2607.10023
venue	ISMIR 2026
authors	Irmak Bukey; Zachary Novack; Jongmin Jung; Dasaem Jeong; Chris Donahue
methods	contrastive learning; retrieval
code urls	unknown
demo urls	unknown
exact title	Local Multimodal Music Alignment from Global Supervision
project urls	unknown
original title	unknown
citation counts	unknown
research topics	music retrieval; 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	unknown
publication or preprint date	2026-07-10
abstract level neutral summary	The work studies music retrieval, music/audio understanding; methods and evaluation details are in the official abstract.
datasets benchmarks models tools used	CLAP
correction withdrawal retraction status	No withdrawal marker observed in captured arXiv metadata.