there’s no incentive for the geometry to form up nicely under the typical training objectives. So they won’t. And then MUVERA and SMVE will break
But with LSH-aware training (or finetuning), like Antoine proposes, the model is explicitly nudged to protect against this issue
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Some models are unlucky in the sense that their latent space is unsuitable for LSH. This is unfortunate, because the geometry then works against a core mechanism allowing fast ANN.
Make your own luck, says @antoine_chaffin
Party is over, time to regularize ColBERT models to fix efficient ANN
MUVERA and SMVE promised to simplify multi-vector retrieval infrastructure but broke on modern ColBERT models
We found a fix, and it does the exact opposite of what we expected
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