Core Concepts
Large Language Models (LLMs) can be effectively used as digital assistants to provide efficient reference to telecom standards, such as those published by 3GPP, by answering questions and retrieving relevant information from the extensive technical documentation.
Abstract
The paper investigates the capabilities and limitations of state-of-the-art LLMs in serving as Question Answering (QA) assistants for telecom standards, specifically those published by the Third Generation Partnership Project (3GPP).
Key highlights:
Evaluation of performance of foundation LLMs, including GPT-3.5 Turbo, GPT-4, LLaMA-2, and Falcon, on the TeleQuAD benchmark dataset containing 3GPP-related QA pairs.
Introduction of TeleRoBERTa, a domain-adapted extractive QA model that performs on par with the highest-performing foundation models while having significantly fewer parameters.
Data preprocessing and fine-tuning techniques to improve LLM performance on telecom-specific content, addressing issues such as technical jargon, table-based information, and cross-referencing.
Development of the TelcoGenAI system, which leverages Retrieval Augmented Generation (RAG) to provide efficient access to 3GPP standards through LLM-powered QA.
Insights on the potential applications of LLM-based telecom assistants, including troubleshooting, maintenance, network operations, and software development.
The findings demonstrate that LLMs can be a credible reference tool for telecom technical documents, paving the way for various applications that can enhance productivity and efficiency in the telecom industry.
Stats
The number of tokens (words) in 3GPP specifications has increased significantly over time, from Release 8 (2006-01-23) to Release 17 (2018-06-15), as shown in Figure 1.
Quotes
"The Third Generation Partnership Project (3GPP) has successfully introduced standards for global mobility. However, the volume and complexity of these standards has increased over time, thus complicating access to relevant information for vendors and service providers."
"Use of Generative Artificial Intelligence (AI) and in particular Large Language Models (LLMs), may provide faster access to relevant information."