Combining dimensionality reduction and quantization compresses text embeddings to 0.1% size with minimal performance loss on MTEB tasks, outperforming either technique alone.
Taehee Jeong
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
When Is 0.1% Enough? Analyzing the Combined Effects of Dimensionality Reduction and Quantization on Text Embedding Compression
Combining dimensionality reduction and quantization compresses text embeddings to 0.1% size with minimal performance loss on MTEB tasks, outperforming either technique alone.