TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs

Girma M. Yilma, Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez

Abstract

Large Language Models (LLMs) have immense potential to transform the telecommunications industry. They could help professionals understand complex standards, generate code, and accelerate development. However, traditional LLMs struggle with the precision and source verification essential for telecom work. To address this, specialized LLM-based solutions tailored to telecommunication standards are needed. This Editorial Note showcases how Retrieval-Augmented Generation (RAG) can offer a way to create precise, factual answers. In particular, we show how to build a Telecommunication Standards Assistant that provides accurate, detailed, and verifiable responses. We show a usage example of this framework using 3GPP Release 16 and Release 18 specification documents. We believe that the application of RAG can bring significant value to the telecommunications field.

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