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Chong Jing

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#artificial intelligence Preprint Sep 2026

CPR: Combining global composing, local performing and full-sequence refining in piano rendering with continuous autoregressive modelling

Prompt-conditioned piano MIDI-to-Music rendering aims to faithfully render target notes while reproducing the timbre of a reference recording. Existing approaches primarily follow two paradigms: autoregressive (AR) modeling and flow matching (or diffusion). Discrete-codec AR models provide causal temporal modeling, but...

Chong Jing, Ju-Nan Zhang, Zhi-Zheng Wu · 0 citations
Preprint Aug 2026

P-MUSE: Prompt-MIDI-Optional Model for Unified Instrumental Music Synthesis and Editing

MIDI-to-Music system renders the melody and rhythm of a target MIDI sequence into musical segment while cloning instrument timbre from a prompt recording. Existing systems typically adopt one of two distinct paradigms: conditional generation with prompt audio alone, which remains applicable when aligned prompt MIDI is...

Chong Jing, Junan Zhang, Jing Yang et al. · 0 citations

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