gaoj0017 commented on PR #14078: URL: https://github.com/apache/lucene/pull/14078#issuecomment-2573030521
Hi @msokolov , the discussion here is not only about the blog posts but also related to the pull request here. In this pull request (and its related blogs), it claims a new method without properly acknowledging the contributions/inspirations from our extended RaBitQ method as we have explained in our last reply. Besides, we believe this discussion is relevant to the Lucene community because Lucene is a collaborative project, used and contributed to by many teams beyond Elastic. Thanks @mikemccand for your kind words - we truly appreciate them! It is also an honor to us that RaBitQ and the extended RaBitQ are seen as impactful in improving industry productivity. Our responses to @benwtrent are as follows. Point 1 in our last reply: This has been ignored in Ben’s reply. We would like to emphasize once again that the so-called “BBQ” method from Elastic is largely based on our RaBitQ method, with only minor modifications - this can be reflected in the previous PRs. Yet Elastic has repeatedly referred to BBQ as their new algorithm without acknowledging RaBitQ. For example, in a [press release](https://www.elastic.co/blog/whats-new-elasticsearch-platform-8-16-0 ), Elastic states that "Elasticsearch’s new BBQ algorithm redefines vector quantization," omitting any reference to RaBitQ. This is unacceptable and particularly unfair to other teams who have openly acknowledged their use of RaBitQ. We request that our RaBitQ method should be properly credited in all existing and future blogs, press releases, pull requests, and other communications regarding the “BBQ” method. Point 2 in our last reply: In the related blog that describes the method in this pull request, it states “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 this target has already been achieved by our extended RaBitQ method. Your team should not have made this mis-claim by ignoring our extended RaBitQ method since we circulated our extended RaBitQ paper to your team more than three months ago. In addition, our extended RaBitQ method proposed the idea of searching for the optimal parameters of scalar quantization for each vector (for details, please refer to our [blog](https://dev.to/gaoj0017/extended-rabitq-an-optimized-scalar-quantization-method-83m)). The method in this pull request has adopted a highly similar idea. For this reason, we request that in any existing and potentially future channels of introducing t he method in this PR, proper acknowledgement of our extended RaBitQ method should be made. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For additional commands, e-mail: issues-h...@lucene.apache.org
