Apple trains small offline nets to route RAG queries, trading upfront cost for faster retrieval
petrusenko_max · x · 2026-11-12
An Apple ML Research approach to RAG retrieval: production queries are typically short and drawn from a stable, well-characterized mix, while keys are long and curated. Apple trains small neural networks once, offline, on a fixed key set so each query routes directly to its best match.
The trade-off: pay an upfront training cost once, get faster and more accurate retrieval at query time without expensive online matching.
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