# Music Plagiarism Detection: Problem Formulation and a Segment-based Solution

arXiv: https://arxiv.org/abs/2601.21260 · HTML: https://mlsanity.com/paper/2601.21260/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 20 references that are in the map.
- First posted on arXiv 29 Jan 2026.

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

- [MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training](https://mlsanity.com/paper/2306.00107/) (2023)
- [Hybrid Transformers for Music Source Separation](https://mlsanity.com/paper/2211.08553/) (2022)
- [All-In-One Metrical And Functional Structure Analysis With Neighborhood Attentions on Demixed Audio](https://mlsanity.com/paper/2307.16425/) (2023)
- [Melody transcription via generative pre-training](https://mlsanity.com/paper/2212.01884/) (2022)
- [Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning](https://mlsanity.com/paper/2010.11910/) (2020)
- [ByteCover3: Accurate Cover Song Identification on Short Queries](https://mlsanity.com/paper/2303.11692/) (2023)
- [CoverHunter: Cover Song Identification with Refined Attention and Alignments](https://mlsanity.com/paper/2306.09025/) (2023)
- [MelodySim: Measuring Melody-aware Music Similarity for Plagiarism Detection](https://mlsanity.com/paper/2505.20979/) (2025)
- [Fine-Grained Music Plagiarism Detection: Revealing Plagiarists through Bipartite Graph Matching and a Comprehensive Large-Scale Dataset](https://mlsanity.com/paper/2107.09889/) (2021)
- [Real-world Music Plagiarism Detection With Music Segment Transcription System](https://mlsanity.com/paper/2509.08282/) (2025)

## Built on by (most cited first, 2 of 2)

- [On the Human and Computer Alignment of Attribute-Based Music Matches](https://mlsanity.com/paper/2609.00987/) (2026)
- [Towards AI-Generated Music Plagiarism Detection as a Version Identification Problem](https://mlsanity.com/paper/2610.09075/) (2026)

## Abstract (arXiv)

Recently, the problem of music plagiarism has emerged as an even more pressing social issue. As music information retrieval research advances, there is a growing effort to address issues related to music plagiarism. However, many studies, including our previous work, have conducted research without clearly defining what the music plagiarism detection task actually involves. This lack of a clear definition has slowed research progress and made it hard to apply results to real-world scenarios. To fix this situation, we defined how Music Plagiarism Detection is different from other MIR tasks and explained what problems need to be solved. We introduce the Similar Music Pair dataset to support this newly defined task. In addition, we propose a method based on segment transcription as one way to solve the task. Our demo and dataset are available at https://github.com/Mippia/ICASSP2026-MPD.