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by aesthesia 34 days ago
Looking at your experiment code, it seems like the retrieval experiments are done with the reconstructed vectors of dimension D rather than the compressed vectors of dimension d, which doesn't have any direct performance improvements. Later on in the post you indicate that the real advantage is that the residuals are more isotropic and therefore you can quantize the pair (p, V_resid) with less quality degradation, but I don't see any experiments actually verifying that retrieval quality holds up in this setting. Also, it's not quite clear to me how you efficiently compute cosine similarity for vectors encoded in this form. Doesn't the V_resid part of the computation require something significantly more complex than a dot product?
1 comments

I agree that we don't want to reconstruct the whole vector while retrieval and it makes poly-AE toy-like at the current state non production ready. My main interest here in the just taking more recall pp in closed form. And then think about how to make it fast. In all threads I got a good intermediate thoughts about the topic which may help me to bring to closer to production form