The Sequence Knowledge #487: A RAG that Assesses Itself
A technique for robust RAG implementations.
Today we will Discuss:
An overview of SELF-RAG, a technique for self-assessing retrieval augmentation methods.
The original SELF-RAG paper from Google Deepmind.
💡 AI Concept of the Day: Understanding Self-RAG
Continuing our series about RAG techniques, today I would like to discuss one of the most intriguing ones.
Self-Reflective Retrieval-Augmented Generation (SELF-RAG) is an advanced framework that enhances traditional Retrieval-Augmented Generation (RAG) by incorporating self-assessment mechanisms into the retrieval and generation processes. Unlike standard RAG, which often retrieves passages indiscriminately, SELF-RAG employs a more sophisticated approach by introducing reflection tokens that guide the language model (LM) in determining when to retrieve information and how to critique its own output.