Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Lewis, Perez, Piktus, Petroni et al. · NeurIPS · 2020

Abstract

Combines a parametric language model with a non-parametric retriever over a document index, letting the model ground its answers in fetched passages rather than memorized weights.

Why it matters

The origin of "RAG". Explains why bolting a retriever onto a model beats fine-tuning for fast-changing knowledge — the pattern behind most production AI search today.

ragretrievalgrounding

Read the source

https://arxiv.org/abs/2005.11401

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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

The AI space moves fast.Nybble™ is how you keep up — and stay sharp.

The AI space moves fast.
Nybble^™ is how you keep up — and stay sharp.