SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback

Understand

RAG systems consist of multiple modules to work together.

• However, these modules are usually separately trained.
• We argue that a system like RAG that incorporates multiple modules should be jointly optimized to achieve optimal performance.
• To demonstrate this, we design a specific pipeline called \textbf{SmartRAG} that includes a policy network and a retriever.