The application of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems in the telecommunication domain presents unique challenges, primarily due to the complex nature of telecom standard documents and the rapid evolution of the field. The paper introduces Telco-RAG, an open-source RAG framework designed to handle the specific needs of telecommunications standards, particularly 3rd Generation Partnership Project (3GPP) documents. Telco-RAG addresses the critical challenges of implementing a RAG pipeline on highly technical content, paving the way for applying LLMs in telecommunications and offering guidelines for RAG implementation in other technical domains.
@article{arxiv.2404.15939,
title = {Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications},
author = {Andrei-Laurentiu Bornea and Fadhel Ayed and Antonio De Domenico and Nicola Piovesan and Ali Maatouk},
journal= {arXiv preprint arXiv:2404.15939},
year = {2024}
}
Comments
6 pages, 5 Figure, 4 Tables, accepted to IEEE Globecom 2024 (see https://github.com/netop-team/telco-rag)