mlsanityData to 7 Oct 2026

MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music Audio Representation Learning

arXiv 2212.02508 ↗First posted 5 Dec 2022cs.SD cs.AI cs.LGcited by 22

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Abstract (arXiv)

The deep learning community has witnessed an exponentially growing interest in self-supervised learning (SSL). However, it still remains unexplored how to build a framework for learning useful representations of raw music waveforms in a self-supervised manner. In this work, we design Music2Vec, a framework exploring different SSL algorithmic components and tricks for music audio recordings. Our model achieves comparable results to the state-of-the-art (SOTA) music SSL model Jukebox, despite being significantly smaller with less than 2% of parameters of the latter. The model will be released on Huggingface(Please refer to: https://huggingface.co/m-a-p/music2vec-v1)

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 10 of its 15 references that are in the map. First posted on arXiv 5 Dec 2022.

Builds on

10 of 15 references.

References · 10

  1. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,712
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,486
  4. 2022data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Languagecited by 718
  5. 2020Jukebox: A Generative Model for Musiccited by 535
  6. 2021Contrastive Learning of Musical Representationscited by 81
  7. 2021Codified audio language modeling learns useful representations for music information retrievalcited by 61
  8. 2019musicnn: Pre-trained convolutional neural networks for music audio taggingcited by 49
  9. 2017Transfer learning for music classification and regression taskscited by 36
  10. 2022Learning Music Representations with wav2vec 2.0cited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 6; 2025: 5; 2026: 4.

22 papers.

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  1. 2023MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Trainingcited by 175
  2. 2023MARBLE: Music Audio Representation Benchmark for Universal Evaluationcited by 38
  3. 2025Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Surveycited by 38
  4. 2024Foundation Models for Music: A Surveycited by 34
  5. 2024Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Surveycited by 27
  6. 2023LyricWhiz: Robust Multilingual Zero-shot Lyrics Transcription by Whispering to ChatGPTcited by 15
  7. 2024MuChin: A Chinese Colloquial Description Benchmark for Evaluating Language Models in the Field of Musiccited by 15
  8. 2024Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Modelcited by 13
  9. 2023On the Effectiveness of Speech Self-supervised Learning for Musiccited by 5
  10. 2023MERTech: Instrument Playing Technique Detection Using Self-Supervised Pretrained Model With Multi-Task Finetuningcited by 4
  11. 2025A Survey on Music Generation from Single-Modal, Cross-Modal, and Multi-Modal Perspectivescited by 4
  12. 2025Universal Music Representations? Evaluating Foundation Models on World Music Corporacited by 3
10 more
  1. 2023Unsupervised Musical Object Discovery from Audiocited by 2
  2. 2023Toward Leveraging Pre-Trained Self-Supervised Frontends for Automatic Singing Voice Understanding Tasks: Three Case Studiescited by 1
  3. 2024Towards Training Music Taggers on Synthetic Datacited by 1
  4. 2025Real-world Music Plagiarism Detection With Music Segment Transcription Systemcited by 1
  5. 2025Segment Transformer: AI-Generated Music Detection via Music Structural Analysiscited by 1
  6. 2026Fusion Segment Transformer: Bi-Directional Attention Guided Fusion Network for AI-Generated Music Detectioncited by 1
  7. 2024Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Modelscited by 0
  8. 2026Auditing Training Data in Generative Music Models via Black-Box Membership Inferencecited by 0
  9. 2026Multimodal Music Recommendation System using LLMscited by 0
  10. 2026TrueMuse: A Benchmark for Data Attribution in Text-to-Music Modelscited by 0