Unsupervised embedding translation via universal latent geometry

This method enables translating text embeddings between disparate vector spaces without paired data or encoders by leveraging a universal semantic structure. The technique preserves geometry across different architectures and parameter counts, enabling high cosine similarity between previously incompatible models.