Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

arXiv:2404.07103v1 Announce Type: cross
Abstract: Large language models (LLMs), while exhibiting exceptional performance, suffer from hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment LLMs with individual text units retrieved from external knowledge corpora to alleviate the issue. However, in many domains, texts are interconnected (e.g., academic papers in a bibliographic graph are linked by citations and co-authorships) which form a (text-attributed) graph. The knowledge in such graphs is encoded not only in single texts/nodes but also in their …

arxiv cs.cl cs.ir cs.lg graph graphs language language models large language large language models reasoning thought type