Yilin Xiao, Junnan Dong, Chuang Zhou, Su Dong, Qianwen Zhang, Di Yin, Xing Sun, Xiao Huang
GraphRAG-Bench is a new benchmark designed to rigorously evaluate the reasoning capabilities of Graph Retrieval Augmented Generation models using challenging, domain-specific questions across diverse tasks.
GraphRAG-Bench is a new tool created to test advanced language models that use graph-based structures to improve their reasoning skills. Unlike previous tests, which often focus on simple question-answering, GraphRAG-Bench uses complex, college-level questions that require deeper understanding and reasoning. The benchmark covers a wide range of tasks and subjects, ensuring that models are evaluated on their ability to handle difficult and varied problems. This new approach helps researchers understand how well these models can think through problems, not just find the right answers.
