I read the paper MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings, and I reproduced it myself in C++ and Python. I was also surprised to find that weaviate also implemented this paper.
But I found that weaviate’s recall rate is much higher than my code implementation and other code implementations on github. I encode the multi-vector into a single vector and add it to the vector index such as HNSW. I want to know whether weaviate has made other optimizations besides the solution in the paper.