Self Correcting Rag With Answer Validation

via “self-correcting-rag-with-answer-validation”

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

Unique: Implements Self-RAG and CRAG techniques that validate generated answers against retrieved context and trigger self-correction (re-retrieval and regeneration) if validation fails, creating an internal feedback loop that detects and corrects hallucinations without external validators

vs others: More proactive than post-hoc fact-checking because it validates during generation and corrects immediately, and more practical than requiring external validators because it uses the LLM itself for validation