RAG and RAU: A Survey on Retrieval-Augmented

2 points by kovezd 1 year ago | 1 comment
  • kovezd 1 year ago
    What I found interesting was the fifth section that describes the strategies to improve RAG performance. Basically:

    1. Quality control. What documents to include?

    2. Timing. When to query?

    3. Pre & post processing. Improve LLM outputs based on retrieved data.

    4. End to end training. Expensive, and data intensive but possibly the best long-term approach.

    5. Controller. An interesting idea with similarities to Reinforcement Learning.

    I wonder what are your thoughts. Which one is most promising? What has been your experience when building RAG apps? Also, is RAG the leading architecture for building applications?