Shao: Scaling Acoustic Token Language Models Toward High-Fidelity Music Generation
A common design pattern in high-quality music generation is to handle structure and fidelity in different representation spaces: a generator first models high-level structure, followed by diffusion-based or neural decoding stages that reconstruct fine details. In this work, we explore an alternative view: both may be progressively modeled within a single deep acoustic-token hierarchy. To study this, we build a 64-layer residual vector quantization (RVQ) acoustic representation and propose a two-stage coarse-to-fine generation framework. A backbone model first generates coarse acoustic tokens for the full track, and a super-resolution model then completes finer tokens within the same acous...
| Authors | Jiafeng Liu, Yuanliang Dong, Hongjia Liu et al. |
|---|---|
| Primary category | cs.SD |
| Published | 3 May 2026 |
| Last updated at source | 6 July 2026 |
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