5 Techniques to Prevent Hallucinations in Your RAG Question Answering

Hallucinations in Large Language Models are a critical problem, as they produce false information and decrease user confidence in the system. To prevent them, one can implement an LLM judge for verification, enhance the Retrieval-Augmented Generation (RAG) pipeline for better document retrieval, and refine system prompts to prevent the model from using its pre-trained knowledge. Other techniques focus on mitigating the damage of hallucinations when they do occur. These methods include citing the sources used to generate an answer and guiding the user on the system's specific strengths and weaknesses to manage expectations.