Universal Geometry of Embeddings: Unsupervised Translation Across Vector Spaces

The paper introduces an unsupervised method for translating text embeddings between vector spaces without paired data, leveraging a universal latent representation. It highlights security risks for vector databases, enabling adversaries to infer sensitive information from embeddings.

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