Whole-Piece Training for Symbolic Music Language Models via Full-Horizon Compressed Recurrence
Findings show that preserving the temporal extent of recurrent history is important for efficient whole-piece modeling, and that memory cost can instead be reduced through KV representation compression.
Yungang Yi, Weihua Li, Matthew Kuo et al.
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