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arXiv · 2506.13001

Adaptable Symbolic Music Infilling with MIDI-RWKV

Christian Zhou-Zheng·Philippe Pasquier
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Abstract

Existing work in automatic music generation has mostly focused on end-to-end systems that generate either entire compositions or continuations of pieces, which are difficult for composers to iterate on. The area of computer-assisted composition, where generative models integrate into existing creative workflows, remains comparatively underexplored. In this study, we address the tasks of model style adaptation and multi-track, long-context, and controllable symbolic music infilling to enhance the process of computer-assisted composition. We present MIDI-RWKV, a small foundation model based on the RWKV-7 linear architecture, to enable efficient and coherent musical cocreation on edge devices. We also demonstrate that MIDI-RWKV admits an effective method of finetuning its initial state for style adaptation in the very-low-sample regime. We evaluate MIDI-RWKV and its state tuning on several quantitative and qualitative metrics with respect to existing models, and release model weights and code at https://github.com/christianazinn/MIDI-RWKV.

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BibTeXRIS

Christian Zhou-Zheng, Philippe Pasquier. 2025-06-16. Adaptable Symbolic Music Infilling with MIDI-RWKV. https://arxiv.org/abs/2506.13001

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