# Music Proofreading with RefinPaint: Where and How to Modify Compositions given Context

arXiv: https://arxiv.org/abs/2407.09099 · HTML: https://mlsanity.com/paper/2407.09099/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 30 references that are in the map.
- First posted on arXiv 12 Jul 2024.

## Builds on (most cited first, 19 of 19)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Music Transformer](https://mlsanity.com/paper/1809.04281/) (2018)
- [BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model](https://mlsanity.com/paper/1902.04094/) (2019)
- [A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music](https://mlsanity.com/paper/1803.05428/) (2018)
- [DeepBach: a Steerable Model for Bach Chorales Generation](https://mlsanity.com/paper/1612.01010/) (2016)
- [Image inpainting: A review](https://mlsanity.com/paper/1909.06399/) (2019)
- [Improved Masked Image Generation with Token-Critic](https://mlsanity.com/paper/2209.04439/) (2022)
- [MMM : Exploring Conditional Multi-Track Music Generation with the Transformer](https://mlsanity.com/paper/2008.06048/) (2020)
- [Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation](https://mlsanity.com/paper/2210.10349/) (2022)
- [Counterpoint by Convolution](https://mlsanity.com/paper/1903.07227/) (2019)
- [Theme Transformer: Symbolic Music Generation with Theme-Conditioned Transformer](https://mlsanity.com/paper/2111.04093/) (2021)
- [Anticipatory Music Transformer](https://mlsanity.com/paper/2306.08620/) (2023)
- [miditok: A Python package for MIDI file tokenization](https://mlsanity.com/paper/2310.17202/) (2023)
- [The Piano Inpainting Application](https://mlsanity.com/paper/2107.05944/) (2021)
- [Byte Pair Encoding for Symbolic Music](https://mlsanity.com/paper/2301.11975/) (2023)
- [Compose & Embellish: Well-Structured Piano Performance Generation via A Two-Stage Approach](https://mlsanity.com/paper/2209.08212/) (2022)
- [Vector Quantized Contrastive Predictive Coding for Template-based Music Generation](https://mlsanity.com/paper/2004.10120/) (2020)
- [Generating Music with a Self-Correcting Non-Chronological Autoregressive Model](https://mlsanity.com/paper/2008.08927/) (2020)
- [A Contextual Latent Space Model: Subsequence Modulation in Melodic Sequence](https://mlsanity.com/paper/2111.11703/) (2021)

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

- [Evaluating Music Context Preservation: A Multi-facet Framework for Music Editing Systems](https://mlsanity.com/paper/2512.14629/) (2025)

## Abstract (arXiv)

Autoregressive generative transformers are key in music generation, producing coherent compositions but facing challenges in human-machine collaboration. We propose RefinPaint, an iterative technique that improves the sampling process. It does this by identifying the weaker music elements using a feedback model, which then informs the choices for resampling by an inpainting model. This dual-focus methodology not only facilitates the machine's ability to improve its automatic inpainting generation through repeated cycles but also offers a valuable tool for humans seeking to refine their compositions with automatic proofreading. Experimental results suggest RefinPaint's effectiveness in inpainting and proofreading tasks, demonstrating its value for refining music created by both machines and humans. This approach not only facilitates creativity but also aids amateur composers in improving their work.