mlsanityData to 7 Oct 2026

Understanding Telecom Language Through Large Language Models

arXiv 2306.07933 ↗First posted 9 Jun 2023cs.CL cs.AIcited by 32

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Abstract (arXiv)

The recent progress of artificial intelligence (AI) opens up new frontiers in the possibility of automating many tasks involved in Telecom networks design, implementation, and deployment. This has been further pushed forward with the evolution of generative artificial intelligence (AI), including the emergence of large language models (LLMs), which is believed to be the cornerstone toward realizing self-governed, interactive AI agents. Motivated by this, in this paper, we aim to adapt the paradigm of LLMs to the Telecom domain. In particular, we fine-tune several LLMs including BERT, distilled BERT, RoBERTa and GPT-2, to the Telecom domain languages, and demonstrate a use case for identifying the 3rd Generation Partnership Project (3GPP) standard working groups. We consider training the selected models on 3GPP technical documents (Tdoc) pertinent to years 2009-2019 and predict the Tdoc categories in years 2020-2023. The results demonstrate that fine-tuning BERT and RoBERTa model achieves 84.6% accuracy, while GPT-2 model achieves 83% in identifying 3GPP working groups. The distilled BERT model with around 50% less parameters achieves similar performance as others. This corroborates that fine-tuning pretrained LLM can effectively identify the categories of Telecom language. The developed framework shows a stepping stone towards realizing intent-driven and self-evolving wireless networks from Telecom languages, and paves the way for the implementation of generative AI in the Telecom domain.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). Builds on 10 of its 24 references that are in the map. First posted on arXiv 9 Jun 2023.

Builds on

10 of 24 references.

References · 10

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  3. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  4. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
  5. 2019How to Fine-Tune BERT for Text Classification?cited by 409
  6. 2020AraBERT: Transformer-based Model for Arabic Language Understandingcited by 359
  7. 2023On the Road to 6G: Visions, Requirements, Key Technologies and Testbedscited by 75
  8. 2019Zero-shot Text Classification With Generative Language Modelscited by 55
  9. 2020Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognitioncited by 35
  10. 2021Multi-class Text Classification using BERT-based Active Learningcited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 16; 2025: 9; 2026: 3.

32 papers.

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  1. 2024Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunitiescited by 83
  2. 2023TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledgecited by 62
  3. 2023Large Language Models for Telecom: Forthcoming Impact on the Industrycited by 44
  4. 2024WirelessLLM: Empowering Large Language Models Towards Wireless Intelligencecited by 43
  5. 2024TelecomGPT: A Framework to Build Telecom-Specfic Large Language Modelscited by 38
  6. 2024TSpec-LLM: An Open-source Dataset for LLM Understanding of 3GPP Specificationscited by 26
  7. 2024At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligencecited by 25
  8. 2024Tele-LLMs: A Series of Specialized Large Language Models for Telecommunicationscited by 25
  9. 2023AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systemscited by 19
  10. 2023Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networkscited by 16
  11. 2024GenAINet: Enabling Wireless Collective Intelligence via Knowledge Transfer and Reasoningcited by 13
  12. 2024Using Large Language Models to Understand Telecom Standardscited by 13
20 more
  1. 2024Linguistic Intelligence in Large Language Models for Telecommunicationscited by 11
  2. 2024Can LLMs Understand Computer Networks? Towards a Virtual System Administratorcited by 11
  3. 2025Advanced Architectures Integrated with Agentic AI for Next-Generation Wireless Networkscited by 11
  4. 2024Telecom Language Models: Must They Be Large?cited by 10
  5. 2024Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standardscited by 8
  6. 2025MoE2: Optimizing Collaborative Inference for Edge Large Language Modelscited by 6
  7. 2025Chat3GPP: An Open-Source Retrieval-Augmented Generation Framework for 3GPP Documentscited by 5
  8. 2024LLM Agents as 6G Orchestrator: A Paradigm for Task-Oriented Physical-Layer Automationcited by 3
  9. 2024TelcoLM: collecting data, adapting, and benchmarking language models for the telecommunication domaincited by 3
  10. 2025ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicingcited by 3
  11. 2024TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Networkcited by 2
  12. 2025Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicingcited by 2
  13. 2025Evaluating Open-Source Large Language Models for Technical Telecom Question Answeringcited by 1
  14. 2026TeleDoCTR: Domain-Specific and Contextual Troubleshooting for Telecommunicationscited by 1
  15. 2024Convolutional vs Large Language Models for Software Log Classification in Edge-Deployable Cellular Network Testingcited by 0
  16. 2025Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecomcited by 0
  17. 2025An LLM-Powered AI Agent Framework for Holistic IoT Traffic Interpretationcited by 0
  18. 2025MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applicationscited by 0
  19. 2026Agentic-V2X: Small Language Model Agents for Deadline-Aware V2X Scheduling in 5G/6G Networkscited by 0
  20. 2026SpecMind: Enabling Spectrum Intelligence via Multi-Agent Hybrid Retrieval-Augmented Generationcited by 0