Corrective RAG (CRAG) improves RAG systems by inserting a Retrieval Evaluator that validates retrieved context quality before generation, leading to three paths: Correct (refining content), Incorrect (triggering external search like Tavily), or Ambiguous (combining internal and external knowledge).

Authors

• Person: Sumit Umbardand Organization: LinkedIn
  RAG Hallucinations: Retrieval Success ≠ Generation Accuracy

Sources

• RAG Hallucinations: Retrieval Success ≠ Generation Accuracy www.linkedin.com Sumit Umbardand · LinkedIn via serper

Referenced by nodes (1)

• Retrieval-Augmented Generation (RAG) concept