gaoj0017 commented on PR #14078:
URL: https://github.com/apache/lucene/pull/14078#issuecomment-2562753433

   @benwtrent Thanks for your reply. 
   
   First, in the blog - [Better Binary Quantization at Elastic and 
Lucene](https://www.elastic.co/search-labs/blog/better-binary-quantization-lucene-elasticsearch)
 - the BBQ method is a variant of our RaBitQ with no major differences. The 
claimed major features of BBQ all originate from our RaBitQ paper (as we have 
explained in our last reply). There is only one attribution to our method, 
where it is mentioned (in one sentence) that BBQ is based on some inspirations 
from RaBitQ. We think this attribution is not sufficient - it should be made 
clear that the mentioned features of BBQ all originate from RaBitQ.
   
   Second, for the new method described in this pull request, there is no 
attribution to our extended RaBitQ method at all - we note that we shared with 
your team the extended RaBitQ paper more than 2 months ago. To our 
understanding, the method is highly similar to our extended RaBitQ at its core 
(which also supports quantizing a vector to 1-bit, 2-bit, ... per dimension). 
They share the major idea of optimizing the scalar quantization method by 
trying different parameters. In your new blog, it is mentioned that “Although 
the RaBitQ approach is conceptually rather different to scalar quantization, we 
were inspired to re-evaluate whether similar performance could be unlocked for 
scalar quantization.” This is not true since our extended RaBitQ corresponds to 
an optimized scalar quantization method.
   
   Given that our extended RaBitQ method is a prior art of the method 
introduced in the blog and our method was known to your team more than 2 months 
ago, you should not have ignored it. Discussions on the differences between two 
methods if any should be clearly explained and experiments of comparing the two 
methods should be provided as well.
   


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