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Libretto: Giving LLM Agents a Sense of Musical Structure

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Papers
arxiv:2606.22708

Libretto: Giving LLM Agents a Sense of Musical Structure

Published on Jun 21
· Submitted by
Yichen Xu
on Jun 23
Authors:

Abstract

Libretto provides a structured framework for symbolic music generation and revision using LLM-native grammar and statistical evaluation across musical dimensions.

Generative music systems can now produce impressive audio from text prompts, but audio outputs are difficult to inspect, edit, and diagnose as musical structure. We introduce Libretto, an agent-facing framework for symbolic music generation and revision. Libretto uses an LLM-native grammar with explicit onset slots, voices, and bar-level organization, then evaluates each piece in a corpus-calibrated statistical space over rhythm, harmony, melody, texture, form, and variation. The same structural axes support retrieval, diagnosis, copy-risk control, and iterative self-revision. Across gap filling, reference-guided full-piece generation, gradual morphing, and educational music generation, Libretto turns symbolic music from a raw token sequence into a measurable and editable object for language-model agents.

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Paper submitter about 9 hours ago

This is a project trying to enable LLM to generate 100 bars multi-instrument music validated by the statistical cloud

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