Retrieval-augmented generation
- A technique that grants generative artificial intelligence models information retrieval capabilities. RAG modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data. This allows LLMs to use domain-specific or updated information. ← Wikipedia
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