Efficient Neural Music Generation

research work·research paper·active

Research work examining music generation.

Verified facts

Official site	https://arxiv.org/abs/2305.15719 ↗
Geography	Global
arxiv	2305.15719
venue	arXiv preprint
authors	Max W. Y. Lam; Qiao Tian; Tang Li; Zongyu Yin; Siyuan Feng; Ming Tu; Yuliang Ji; Rui Xia; Mingbo Ma; Xuchen Song; Jitong Chen; Yuping Wang; Yuxuan Wang
methods	diffusion modeling
code urls	unknown
demo urls	unknown
exact title	Efficient Neural Music Generation
project urls	https://Efficient-MeLoDy.github.io/
original title	unknown
citation counts	unknown
research topics	music generation
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	2023-05-25
abstract level neutral summary	The work studies music generation; methods and evaluation details are in the official abstract.
datasets benchmarks models tools used	MusicLM
correction withdrawal retraction status	No withdrawal marker observed in captured arXiv metadata.