Real-Time Language Model Jamming: A Case Study for Live Music Accompaniment Generation
research work·research paper·active
Research work examining automatic accompaniment.
Verified facts
| Official site | https://arxiv.org/abs/2606.11886 ↗ |
|---|---|
| Geography | Global |
| arxiv | 2606.11886 |
| venue | Accepted to RTAS 2026. 14 pages, 5 figures, 3 tables |
| authors | Bowen Zheng; Andrew H. Yang; Jiaqi Ruan; Jia He; Xinyue Li; Yuan-Hsin Chen; Ziyu Wang; Xiaosong Ma |
| methods | language modeling |
| code urls | unknown |
| demo urls | https://stream-muse-webpage.vercel.app/#audio-library |
| exact title | Real-Time Language Model Jamming: A Case Study for Live Music Accompaniment Generation |
| project urls | https://stream-muse-webpage.vercel.app/#audio-library |
| original title | unknown |
| citation counts | unknown |
| research topics | automatic accompaniment |
| 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 | 2026-06-10 |
| abstract level neutral summary | The work studies automatic accompaniment; 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. |
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0d ago · highhow verification works
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