RAG
retrieval-augmented generation, retrieval augmented generation, grounding
In one sentence
Retrieval-augmented generation: searching your own documents at question time and pasting the passages that look relevant into the prompt.
Why it matters
Retrieve first, then generate. The model never learns your documents; it is handed the three passages that looked relevant and told to answer from them. Hence a RAG system can cite its sources, and yesterday's document is available immediately. Its weakest link is retrieval: if the search misses the right passage, no amount of model quality rescues the answer.
Sources
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