# PDMX: A Large-Scale Public Domain MusicXML Dataset for Symbolic Music Processing

arXiv: https://arxiv.org/abs/2409.10831 · HTML: https://mlsanity.com/paper/2409.10831/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 38 references that are in the map.
- First posted on arXiv 17 Sep 2024.

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

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Deduplicating Training Data Makes Language Models Better](https://mlsanity.com/paper/2107.06499/) (2021)
- [MusicLM: Generating Music From Text](https://mlsanity.com/paper/2301.11325/) (2023)
- [Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset](https://mlsanity.com/paper/1810.12247/) (2018)
- [Fast Timing-Conditioned Latent Audio Diffusion](https://mlsanity.com/paper/2402.04825/) (2024)
- [MusicLDM: Enhancing Novelty in Text-to-Music Generation Using Beat-Synchronous Mixup Strategies](https://mlsanity.com/paper/2308.01546/) (2023)
- [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)
- [DITTO: Diffusion Inference-Time T-Optimization for Music Generation](https://mlsanity.com/paper/2401.12179/) (2024)
- [MT3: Multi-Task Multitrack Music Transcription](https://mlsanity.com/paper/2111.03017/) (2021)
- [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)
- [SongMASS: Automatic Song Writing with Pre-training and Alignment Constraint](https://mlsanity.com/paper/2012.05168/) (2020)
- [MusPy: A Toolkit for Symbolic Music Generation](https://mlsanity.com/paper/2008.01951/) (2020)
- [Anticipatory Music Transformer](https://mlsanity.com/paper/2306.08620/) (2023)
- [Symphony Generation with Permutation Invariant Language Model](https://mlsanity.com/paper/2205.05448/) (2022)
- [Multitrack Music Transformer](https://mlsanity.com/paper/2207.06983/) (2022)
- [Compose & Embellish: Well-Structured Piano Performance Generation via A Two-Stage Approach](https://mlsanity.com/paper/2209.08212/) (2022)

## Built on by (most cited first, 15 of 15)

- [Barbarians at the Gate: How AI is Upending Systems Research](https://mlsanity.com/paper/2510.06189/) (2025)
- [LEGATO: Large-scale End-to-end Generalizable Approach to Typeset OMR](https://mlsanity.com/paper/2506.19065/) (2025)
- [Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training](https://mlsanity.com/paper/2512.02652/) (2025)
- [From Generality to Mastery: Composer-Style Symbolic Music Generation via Large-Scale Pre-training](https://mlsanity.com/paper/2506.17497/) (2025)
- [MuseTok: Symbolic Music Tokenization for Generation and Semantic Understanding](https://mlsanity.com/paper/2510.16273/) (2025)
- [BMdataset: A Musicologically Curated LilyPond Dataset](https://mlsanity.com/paper/2604.10628/) (2026)
- [PianoCoRe: Combined and Refined Piano MIDI Dataset](https://mlsanity.com/paper/2605.06627/) (2026)
- [Transcoda: End-to-End Zero-Shot Optical Music Recognition via Data-Centric Synthetic Training](https://mlsanity.com/paper/2605.10835/) (2026)
- [Optical Music Recognition for Real-World Manuscripts with Synthetic Data](https://mlsanity.com/paper/2606.09479/) (2026)
- [MusPyExpress: Extending MusPy with Enhanced Expression Text Support](https://mlsanity.com/paper/2608.21678/) (2026)
- [Rubato: Transcribing Piano Music with Timestamps](https://mlsanity.com/paper/2605.24291/) (2026)
- [LEGATO 2: Toward Multimodal Sheet Music Recognition and Understanding](https://mlsanity.com/paper/2607.05769/) (2026)
- [Local Multimodal Music Alignment from Global Supervision](https://mlsanity.com/paper/2607.10023/) (2026)
- [Integrating Contextual Embeddings into Evaluation of Expressive MIDI Piano Performances](https://mlsanity.com/paper/2607.27909/) (2026)
- [A Dataset and Benchmark for Optical Music Recognition of String Quartet Scores](https://mlsanity.com/paper/2608.10978/) (2026)

## Abstract (arXiv)

The recent explosion of generative AI-Music systems has raised numerous concerns over data copyright, licensing music from musicians, and the conflict between open-source AI and large prestige companies. Such issues highlight the need for publicly available, copyright-free musical data, in which there is a large shortage, particularly for symbolic music data. To alleviate this issue, we present PDMX: a large-scale open-source dataset of over 250K public domain MusicXML scores collected from the score-sharing forum MuseScore, making it the largest available copyright-free symbolic music dataset to our knowledge. PDMX additionally includes a wealth of both tag and user interaction metadata, allowing us to efficiently analyze the dataset and filter for high quality user-generated scores. Given the additional metadata afforded by our data collection process, we conduct multitrack music generation experiments evaluating how different representative subsets of PDMX lead to different behaviors in downstream models, and how user-rating statistics can be used as an effective measure of data quality. Examples can be found at https://pnlong.github.io/PDMX.demo/.