<ul><li>Ultra-Quantisation method involves replacing high-dimensional floating point vectors with {-1, 0, 1} elements for efficient embedding search.</li><li>Quantisation helps in reducing data representation size and comparison speed in high-dimensional vector scenarios.</li><li>Utilizing convex polytopes in high-dimensional space enables significant space and metric evaluation cost savings in embedding searches.</li><li>The approach maintains a strong correlation for similarity measurements despite the extreme quantisation of vectors.</li></ul>

Ultra-Quantisation: Efficient Embedding Search via 1.58-bit Encodings

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