PCA-based static dimension pruning of dense document embeddings reduces storage and latency by about half with under 5% NDCG@10 loss on MS MARCO and BEIR COVID.
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Static Pruning in Dense Retrieval using Matrix Decomposition
PCA-based static dimension pruning of dense document embeddings reduces storage and latency by about half with under 5% NDCG@10 loss on MS MARCO and BEIR COVID.