How to Reduce Hallucinations in RAG Systems
From better retrieval to answer inspection before delivery Retrieval-Augmented Generation was introduced as a practical answer to one of the central weaknesses of large language models: their ability to produce fluent, confident text even when they do not know the answer. The core idea is straightforward. Before the model answers, the system retrieves relevant documents. … Read more









