Connecting Graph Science and LLMs

This chapter explores the intersections between graph science and large language models, focusing on how the graph of thoughts can enhance reasoning processes. It introduces methodologies like chain of thought, tree of thought, and their applications in improving problem-solving capabilities within LLMs. The chapter also evaluates the efficiency of these frameworks in breaking down complex tasks and optimizing outcomes.