arxiv
PublishedJuly 14, 2026 at 4:00 AM
—neutral
Lifelong Representations: A Survey on Continual Self-Supervised Learning for Vision Models
Publisher summary· verbatim
arXiv:2607.09785v1 Announce Type: cross Abstract: Traditionally, continual learning has assumed access to labeled data, yet many real-world applications -- such as lifelong robotics -- require models to adapt continuously from unlabeled streams. This has led to the development of continual self-supe
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Originally published on arxiv ↗