Anchor divergence for semantic geometry in contrastive learning
Read the original at arxiv.org→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...
Original headline: "Anchor Divergence for Semantic Geometry in Contrastive Learning"
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- Oct 7, 04:00 UTC arXiv cs.AI lead source Anchor Divergence for Semantic Geometry in Contrastive Learning