RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search — mentioned by cigrainger

Wed, 25 Mar 2026 08:00:53 GMT

I haven't given binary vectors a lot of thought, but I'm exploring RaBitQ[1]. [1] https://arxiv.org/abs/2405.12497

Paper and discussion history. A mention is not an endorsement.

RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search — mentioned by kingcauchy

Tue, 17 Mar 2026 17:00:04 GMT

Not strictly google but microsoft/bing too, here's the top ones from my notes: https://arxiv.org/abs/2410.14452 spfresh, https://arxiv.org/abs/2111.08566 spann, https://arxiv.org/abs/2405.12497 rabitq, https://arxiv.org/abs/2509.06046 diskann, I have a variety of blogs that I used too and reference implementations! It's a Rabit[Q]uantized Hierchical Balanced Clustering algorithm we use for the vector index and we use a chunked segment index for the sparse index if you're curious! Happy to discuss more!

Paper and discussion history. A mention is not an endorsement.

RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search · HackerPapers discussions

RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search — mentioned by cigrainger

RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search — mentioned by kingcauchy