When Is 0.1% Enough? Analyzing the Combined Effects of Dimensionality Reduction and Quantization on Text Embedding Compression

Recent high-performing text embedding models often produce high-dimensional real-valued vectors, resulting in substantial storage and computational costs. To address this issue, embedding compression methods based on dimensionality reduction or quantization have been proposed; however, the effects o