Counter-intuitive: Large Language Models Can Better Understand Knowledge Graphs Than We Thought

arXiv:2402.11541v1 Announce Type: new
Abstract: Although the method of enhancing large language models' (LLMs') reasoning ability and reducing their hallucinations through the use of knowledge graphs (KGs) has received widespread attention, the exploration of how to enable LLMs to integrate the structured knowledge in KGs on-the-fly remains inadequate. Researchers often co-train KG embeddings and LLM parameters to equip LLMs with the ability of comprehending KG knowledge. However, this resource-hungry training paradigm significantly increases the model learning cost and is also …

abstract arxiv attention cs.ai cs.cl exploration fly graphs hallucinations knowledge knowledge graphs language language models large language large language models llms reasoning thought through type