Feb. 9, 2024, 5:43 a.m. | Bryan Perozzi Bahare Fatemi Dustin Zelle Anton Tsitsulin Mehran Kazemi Rami Al-Rfou Jonathan Halcrow

cs.LG updates on arXiv.org arxiv.org

How can we best encode structured data into sequential form for use in large language models (LLMs)? In this work, we introduce a parameter-efficient method to explicitly represent structured data for LLMs. Our method, GraphToken, learns an encoding function to extend prompts with explicit structured information. Unlike other work which focuses on limited domains (e.g. knowledge graph representation), our work is the first effort focused on the general encoding of structured data to be used for various reasoning tasks. We …

cs.ai cs.lg cs.si data data for llms encode encoding form function graph information language language models large language large language models llms prompts stat.ml structured data work

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