Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey

arXiv:2311.07914v2 Announce Type: replace-cross
Abstract: The contemporary LLMs are prone to producing hallucinations, stemming mainly from the knowledge gaps within the models. To address this critical limitation, researchers employ diverse strategies to augment the LLMs by incorporating external knowledge, aiming to reduce hallucinations and enhance reasoning accuracy. Among these strategies, leveraging knowledge graphs as a source of external information has demonstrated promising results. In this survey, we comprehensively review these knowledge-graph-based augmentation techniques in LLMs, focusing on their efficacy in …

abstract accuracy arxiv cs.cl cs.lg diverse graphs hallucinations knowledge knowledge graphs llms reasoning reduce researchers stemming strategies survey type