Rethinking Representation Geometry in Supervised Contrastive Learning under Long-Tailed Data
arXiv:2610.32039v1 Announce Type: cross 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 re…
Read the full story at arXiv stat.ML ↗
Timeline · 1 report
- 2026-10-26 04:00 · arXiv stat.ML
Rethinking Representation Geometry in Supervised Contrastive Learning under Long-Tailed Data