# PianoBART: Symbolic Piano Music Generation and Understanding with Large-Scale Pre-Training

arXiv: https://arxiv.org/abs/2407.03361 · HTML: https://mlsanity.com/paper/2407.03361/

## Key facts

- Cited by 12 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 26 Jun 2024.

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

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Scaling Language-Image Pre-training via Masking](https://mlsanity.com/paper/2212.00794/) (2022)
- [Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset](https://mlsanity.com/paper/1810.12247/) (2018)
- [Music Transformer](https://mlsanity.com/paper/1809.04281/) (2018)
- [Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs](https://mlsanity.com/paper/2101.02402/) (2021)
- [MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training](https://mlsanity.com/paper/2106.05630/) (2021)
- [POP909: A Pop-song Dataset for Music Arrangement Generation](https://mlsanity.com/paper/2008.07142/) (2020)
- [PopMAG: Pop Music Accompaniment Generation](https://mlsanity.com/paper/2008.07703/) (2020)
- [The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-composed Music through Quantitative Measures](https://mlsanity.com/paper/2008.01307/) (2020)
- [EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation](https://mlsanity.com/paper/2108.01374/) (2021)
- [GiantMIDI-Piano: A large-scale MIDI dataset for classical piano music](https://mlsanity.com/paper/2010.07061/) (2020)
- [Finding the Missing Data: A BERT-inspired Approach Against Package Loss in Wireless Sensing](https://mlsanity.com/paper/2403.12400/) (2024)
- [Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm](https://mlsanity.com/paper/2404.00836/) (2024)
- [Large-Scale MIDI-based Composer Classification](https://mlsanity.com/paper/2010.14805/) (2020)
- [Composer Style Classification of Piano Sheet Music Images Using Language Model Pretraining](https://mlsanity.com/paper/2007.14587/) (2020)
- [A Convolutional Approach to Melody Line Identification in Symbolic Scores](https://mlsanity.com/paper/1906.10547/) (2019)

## Built on by (most cited first, 12 of 12)

- [An overview of domain-specific foundation model: key technologies, applications and challenges](https://mlsanity.com/paper/2409.04267/) (2024)
- [ABC-Eval: Benchmarking Large Language Models on Symbolic Music Understanding and Instruction Following](https://mlsanity.com/paper/2509.23350/) (2025)
- [Let Network Decide What to Learn: Symbolic Music Understanding Model Based on Large-scale Adversarial Pre-training](https://mlsanity.com/paper/2407.08306/) (2024)
- [Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?](https://mlsanity.com/paper/2506.01482/) (2025)
- [Diffusion-based Symbolic Music Generation with Structured State Space Models](https://mlsanity.com/paper/2507.20128/) (2025)
- [On the de-duplication of the Lakh MIDI dataset](https://mlsanity.com/paper/2509.16662/) (2025)
- [Efficient Long-Sequence Diffusion Modeling for Symbolic Music Generation](https://mlsanity.com/paper/2603.00576/) (2026)
- [PianoCoRe: Combined and Refined Piano MIDI Dataset](https://mlsanity.com/paper/2605.06627/) (2026)
- [Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction](https://mlsanity.com/paper/2507.04776/) (2025)
- [Zero-Effort Image-to-Music Generation: An Interpretable RAG-based VLM Approach](https://mlsanity.com/paper/2509.22378/) (2025)
- [BERT-APC: A Reference-free Framework for Automatic Pitch Correction via Musical Context Inference](https://mlsanity.com/paper/2511.20006/) (2025)
- [MeloBottleneck: Self-Supervised Melody Skeleton Extraction with a Latent Subsequence Bottleneck](https://mlsanity.com/paper/2607.10233/) (2026)

## Abstract (arXiv)

Learning musical structures and composition patterns is necessary for both music generation and understanding, but current methods do not make uniform use of learned features to generate and comprehend music simultaneously. In this paper, we propose PianoBART, a pre-trained model that uses BART for both symbolic piano music generation and understanding. We devise a multi-level object selection strategy for different pre-training tasks of PianoBART, which can prevent information leakage or loss and enhance learning ability. The musical semantics captured in pre-training are fine-tuned for music generation and understanding tasks. Experiments demonstrate that PianoBART efficiently learns musical patterns and achieves outstanding performance in generating high-quality coherent pieces and comprehending music. Our code and supplementary material are available at https://github.com/RS2002/PianoBart.