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News/Understanding Self-Supervised Learning via Latent Distribution Matching
arxiv
PublishedMay 28, 2026 at 4:00 AM
—neutral

Understanding Self-Supervised Learning via Latent Distribution Matching

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arXiv:2605.03517v3 Announce Type: replace Abstract: Self-supervised learning (SSL) excels at finding general-purpose latent representations from complex data, yet lacks a unifying theoretical framework that explains the diverse existing methods and guides the design of new ones. We cast SSL as laten

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