Retrieval Augmented Generation

Technique in natural language processing that enhances the output of large language models by incorporating information retrieved from an authoritative knowledge base. This approach combines the strengths of both retrieval-based and generation-based methods, improving the relevance and quality of the generated text by grounding it in factual sources. Retrieval Augmented Generation is particularly useful for tasks that require up-to-date and precise information, benefiting researchers, developers, and businesses seeking accurate and contextually appropriate responses.

Retrieval Augmented Generation was discovered on April 16th 2024 and it currently has a search volume of 49.5K with a growth of +99X+.