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Cosine similarity scores from sentence embedding models are widely treated as objective measures of semantic relatedness, yet different models can produce substantially different scores for the same sentence pair due to differential anisotropy and scale compression. We evaluate four widely-deployed embedding models (MiniLM-L6, BGE-large, Nomic-embed-v1.

Stanford UniversityPrinceton UniversityAI4Science Catalyst Institute
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