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The document introduces Graph-Grounded LLMs, a system designed to enhance the performance of Large Language Models (LLMs) in graph-related tasks by integrating a graph library with function-calling capabilities. This approach aims to minimize hallucinations and improve mathematical accuracy, as demonstrated through rigorous evaluation using the NLGraph benchmark and a disaster response application. Key contributions include reduced computational overhead, scalability for larger graphs, and robust error hand

Author

1049933755

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EN