Article

Self-Supervised Learning Principles Challenges and Emerging Directions

2025-02-24

Abstract excerpt

Self-supervised learning (SSL) has emerged as a transformative paradigm in machine learning, enabling models to learn meaningful representations from vast amounts of unlabeled data. By leveraging pretext tasks that generate supervisory signals intrinsically from data, SSL has significantly reduced the need for costly human annotations and has demonstrated remarkable performance across diverse domains, including co...

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Literature Corpus work: 958857ff-46f9-5b9c-b0d4-4a4fe4c1f8dd
DOI: 10.20944/preprints202502.1894.v1

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