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BERT embeddings occupy narrow cone, challenging cosine similarity assumptions

By PulseAugur Editorial · [1 sources] ·

A recent analysis suggests that mean-pooled BERT embeddings exhibit a high cosine similarity of 0.99 between semantically unrelated pairs. This phenomenon indicates that embeddings may occupy a narrow cone, a characteristic that standard cosine similarity metrics do not account for. The paper proposes that this is not an error in retrieval systems but an inherent property of how these embeddings are structured. AI

IMPACT Highlights a potential limitation in how semantic similarity is measured for embeddings, impacting retrieval and NLP tasks.

RANK_REASON Academic paper discussing a technical aspect of embeddings and similarity metrics. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

BERT embeddings occupy narrow cone, challenging cosine similarity assumptions

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Academic paper discussing a technical aspect of embeddings and similarity metrics. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Towards AI TIER_1 English(EN) · Aqeel Abbas ·

    Your Embeddings Occupy a Narrow Cone. Cosine Similarity Assumes They Don’t.

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://pub.towardsai.net/your-embeddings-occupy-a-narrow-cone-cosine-similarity-assumes-they-dont-3fc9a367f6a1?source=rss----98111c9905da---4"><img src="https://cdn-images-1.medium.com/max/2600/0*4UJo2JsTKNlviLf…

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