# MusiChat: Vibe Composing for Music Creation

arXiv: https://arxiv.org/abs/2607.24873 · HTML: https://mlsanity.com/paper/2607.24873/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 17 references that are in the map.
- First posted on arXiv 27 Jul 2026.

## Builds on (most cited first, 10 of 10)

- [Jukebox: A Generative Model for Music](https://mlsanity.com/paper/2005.00341/) (2020)
- [LLMs Get Lost In Multi-Turn Conversation](https://mlsanity.com/paper/2505.06120/) (2025)
- [A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://mlsanity.com/paper/2402.18013/) (2024)
- [MelodyGLM: Multi-task Pre-training for Symbolic Melody Generation](https://mlsanity.com/paper/2309.10738/) (2023)
- [SongComposer: A Large Language Model for Lyric and Melody Generation in Song Composition](https://mlsanity.com/paper/2402.17645/) (2024)
- [MeloTrans: A Text to Symbolic Music Generation Model Following Human Composition Habit](https://mlsanity.com/paper/2410.13419/) (2024)
- [Automatic Time Signature Determination for New Scores Using Lyrics for Latent Rhythmic Structure](https://mlsanity.com/paper/2311.15480/) (2023)
- [Relationships between Keywords and Strong Beats in Lyrical Music](https://mlsanity.com/paper/2412.04202/) (2024)
- [SongGLM: Lyric-to-Melody Generation with 2D Alignment Encoding and Multi-Task Pre-Training](https://mlsanity.com/paper/2412.18107/) (2024)
- [MusicAIR: A Multimodal AI Music Generation Framework Powered by an Algorithm-Driven Core](https://mlsanity.com/paper/2511.17323/) (2025)

## Built on by (most cited first, 1 of 1)

- [From One-Shot Generation to Incremental Music Composition: Adapting a General-Purpose Instruction LLM for Persistent Symbolic Editing](https://mlsanity.com/paper/2609.34994/) (2026)

## Abstract (arXiv)

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. We present MusiChat, a conversational vibe composing system that enables collaborative human-AI music creation through natural-language interaction and iterative refinement. At the core of MusiChat is a hierarchical controllable music generation framework that separates lyric-aligned musical structure generation from expressive surface realization, allowing flexible stylistic transformations and structure-preserving edits. The system integrates a large language model with a hybrid symbolic music engine through a memory-augmented architecture that maintains the active composition state and user history across interactions. A hybrid intent-routing mechanism further enables efficient interpretation of both precise musical edits and open-ended creative requests. Rather than regenerating compositions from scratch, MusiChat incrementally transforms an evolving musical artifact while preserving relevant musical structure and user intent. We evaluate MusiChat through objective analysis and human studies, achieving 95.31% and 100% accuracy for single- and multi-turn interactions, respectively, and obtaining like-to-dislike ratios of 2:1 for melody naturalness and 3:1 for musical quality. Our results demonstrate that MusiChat supports coherent multi-turn music authoring and interactive human-AI co-creation through a conversational interface.