The RAG approach offers several benefits, including:
- Improved accuracy: By leveraging existing knowledge from the corpus, RAG models can generate more accurate and informative text, particularly for tasks that require domain-specific knowledge or precise information. This is because the model can draw upon a vast repository of knowledge, rather than relying solely on its internal patterns.
- Increased diversity: RAG models can generate a wider range of responses by combining different passages and adapting them to the context. This is achieved by retrieving multiple relevant passages and then generating new text that incorporates the key points from each passage.