Comment by NaiveEmpiricist
20 hours ago
It looks like another difference with RAGs is that instead of reranking the doc vectors and taking the top 5 or so, this paper mixes all the docs (weighted by relevance) into a fixed number of "memory tokens".
It looks like this helps avoid a problem I've had with RAG - when a fact isn't local to a single patch of text.
Is this a problem, though? Vector similarity should surface the relevant, related patches.
But only in documents that make it through RAG’s hard cutoff. There’s an explanation of this on the related Stanford site at https://memory.stanford.edu/ (see “How MEMORILLA differs from RAG”)
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