Personalizable Long-Context Symbolic Music Infilling with MIDI-RWKV
Existing work in automatic music generation has primarily focused on
end-to-end systems that produce complete compositions or continuations.
However, because musical composition is typically an iterative process, such
systems make it difficult to engage in the back-and-forth between human and
machine that is essential to computer-assisted creativity. In this study, we
address the task of personalizable, multi-track, long-context, and controllable
symbolic music infilling to enhance the process of computer-assisted
composition. We present MIDI-RWKV, a novel 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 personalization in the very-low-sample regime.
We evaluate MIDI-RWKV and its state tuning on several quantitative and
qualitative metrics, and release model weights and code at
https://github.com/christianazinn/MIDI-RWKV.
685209ec0164cd1316710433
Christian Zhou-Zheng
extracted_pending
2025-06-18T00:35:57.447Z
6584f042b378d311dccea501
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/vkq1AQhcuZwIjpFDkdgPQ.png
Christian Zhou-Zheng
user
ChristianAzinn
685209ec0164cd1316710434
Philippe Pasquier
extracted_confirmed
2025-06-18T09:14:00.382Z
66342b6b0797618ea4e0bd54
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/msWLNWjX6XIlYRi5iG8Ys.jpeg
Philippe  Pasquier
user
MetacreationLab
Personalizable Long-Context Symbolic Music Infilling with MIDI-RWKV
Existing work in automatic music generation has primarily focused on
end-to-end systems that produce complete compositions or continuations.
However, because musical composition is typically an iterative process, such
systems make it difficult to engage in the back-and-forth between human and
machine that is essential to computer-assisted creativity. In this study, we
address the task of personalizable, multi-track, long-context, and controllable
symbolic music infilling to enhance the process of computer-assisted
composition. We present MIDI-RWKV, a novel 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 personalization in the very-low-sample regime.
We evaluate MIDI-RWKV and its state tuning on several quantitative and
qualitative metrics, and release model weights and code at
https://github.com/christianazinn/MIDI-RWKV.
MIDI-RWKV, a novel RWKV-7 based model, enables efficient and coherent musical infilling on edge devices with personalizable initial states, enhancing the computer-assisted composition process.
symbolic music infilling RWKV-7 MIDI-RWKV musical cocreation edge devices fine-tuning initial state personalization very-low-sample regime