Re:Faster Retrieval for Better, More Efficient RAG
by comandillos on Wednesday November 11, 2026 @01:07PM
(#50456477)
I feel like retrieval approaches, despite how good your ranking mechanisms are, end up biasing LLMs into what a heuristics-based system with way worse understanding of the domain says. I guess is a trade off between speed and quality, but letting the LLM explore without a bias (based on my personal experience) seems to generally provide much better results in terms of quality for the final output.
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Re:Faster Retrieval for Better, More Efficient RAG
by WhitneyLand on Wednesday November 11, 2026 @09:12PM
(#50462199)
Good point and it’s an often overlooked.
RAG can take the intelligence of an LLM and dumb it down to old school Google search results.
Re:Faster Retrieval for Better, More Efficient RAG
by Terr_ on Wednesday November 11, 2026 @11:17PM
(#50463020)
[delayed]
Re:Faster Retrieval for Better, More Efficient RAG
by refactor_master on Wednesday November 11, 2026 @11:31PM
(#50463098)
The trade-off between speed and quality is everything though. I've found that semantic searching everything that might be relevant and dump the top N into the model is way faster at getting a workable result.