arXiv AI By Haoyu Gu, Lekai Qian, Haowu Zhou, Qi Liu, Shuai Wang

BeatEdit: Symbolic Music Generation as Explicit Editing

Read the original on arXiv AI →

arXiv:2607. 11124v1 Announce Type: cross Abstract: Music creation is fundamentally a process of revision.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

Hugging Face Trending Papers
Jul 20

FlowSonic: Stable Zero-Shot Music Editing via High-Order Trajectory Integration

Zero-shot text-guided editing of real-world music recordings requires balancing semantic modification with faithful preservation of the original musical structure. Although recent diffusion transformers trained with rectified flow have achieved remarkable success in text-to-music generation, extending them to edit existing recordings remains challenging because editing requires accurate deterministic inversion, reliable structural preservation, and numerically stable integration throughout the inversion and generation processes.

arXiv AI
Jul 16

From Prediction to Collaboration: Interactive Symbolic Music Analysis

arXiv:2607. 13587v1 Announce Type: cross Abstract: Automatic symbolic music analysis has made substantial progress, yet existing systems are typically designed for a single mode of use, such as full-score prediction, and therefore do not match the broader range of operations that arise in analysis workflows, including partial completion, local correction, and iterative refinement.

By Emmanouil Karystinaios, Johannes Hentschel, Markus Neuwirth, Gerhard Widmer
Hugging Face Trending Papers
Jul 27

MusiChat: Vibe Composing for Music Creation

Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts. However, most existing systems follow a prompt-and-regenerate paradigm, making iterative refinement difficult because users must repeatedly recreate compositions instead of directly evolving existing musical ideas.