Document search needs fewer vectors: Hugging Face experiment cuts the count by a factor of 4

In a Nov 11 experiment, a model retained 97.8% of its original retrieval score on NanoBEIR while reducing the number of document vectors by a factor of 4. The author trained the model for retrieval with subsequent compression in mind: similar vectors are merged to take up less space.