Anchor Divergence for Semantic Geometry in Contrastive Learning
arXiv:2610.06919v1 Announce Type: new Abstract: This paper concerns how semantic context determines geometry in learned vector representations. Similarity is typically measured using cosine similarity, which provides a single fixed geometry. Semantic similarity, however, is inherently context depen…
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- 2026-10-07 04:00 · arXiv cs.AI
Anchor Divergence for Semantic Geometry in Contrastive Learning