arxiv
PublishedOctober 27, 2026 at 4:00 AM
Rethinking Representation Geometry in Supervised Contrastive Learning under Long-Tailed Data
Publisher summary· verbatim
arXiv:2610.32039v1 Announce Type: new Abstract: Supervised contrastive learning and its balanced variants have demonstrated their effectiveness for representation learning under long-tailed distributions. However, although prior analyses suggest that their optimal representations may exhibit a regul
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Originally published on arxiv ↗