Effective query-independent vector pruning for dense retrieval
This work addresses the problem of ranking dimensions of dense vectors by proposing and evaluating methods coming from different conceptual backgrounds and shows that the first dimensions contribute the most to total effectiveness performance when ranking the dimensions with the best-performing methods.