May 15, 2024, 4:42 a.m. | Edison Jair Bejarano Sepulveda, Nicolai Potes Hector, Santiago Pineda Montoya, Felipe Ivan Rodriguez, Jaime Enrique Orduy, Alec Rosales Cabezas, Danny

cs.LG updates on

arXiv:2405.08792v1 Announce Type: new
Abstract: This paper explores the potential of large language models (LLMs) to make the Aeronautical Regulations of Colombia (RAC) more accessible. Given the complexity and extensive technicality of the RAC, this study introduces a novel approach to simplifying these regulations for broader understanding. By developing the first-ever RAC database, which contains 24,478 expertly labeled question-and-answer pairs, and fine-tuning LLMs specifically for RAC applications, the paper outlines the methodology for dataset assembly, expert-led annotation, and model training. …

abstract accessibility arxiv colombia complexity cs.lg datasets ever language language models large language large language models llms novel paper regulations simplifying study type understanding

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