mlsanityData to 7 Oct 2026

TSpec-LLM: An Open-source Dataset for LLM Understanding of 3GPP Specifications

arXiv 2406.01768 ↗First posted 3 Jun 2024cs.NI cs.IT eess.SPcited by 26

On the map: Retrieval-augmented generation → RAG pipeline design and evaluation

Abstract (arXiv)

Understanding telecom standards involves sorting through numerous technical documents, such as those produced by the 3rd Generation Partnership Project (3GPP), which is time-consuming and labor-intensive. While large language models (LLMs) can assist with the extensive 3GPP knowledge base, an inclusive dataset is crucial for their effective pre-training and fine-tuning. In this paper, we introduce textitTSpec-LLM, an open-source comprehensive dataset covering all 3GPP documents from Release 8 to Release 19 (1999--2023). To evaluate its efficacy, we first select a representative sample of 3GPP documents, create corresponding technical questions, and assess the baseline performance of various LLMs. We then incorporate a retrieval-augmented generation (RAG) framework to enhance LLM capabilities by retrieving relevant context from the textitTSpec-LLM dataset. Our evaluation shows that using a naive-RAG framework on textitTSpec-LLM improves the accuracy of GPT-3.5, Gemini 1.0 Pro, and GPT-4 from 44%, 46%, and 51% to 71%, 75%, and 72%, respectively.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Placed in RAG pipeline design and evaluation, one of 15 directions in Retrieval-augmented generation. Builds on 21 of its 31 references that are in the map. First posted on arXiv 3 Jun 2024.

Builds on

21 of 31 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications24 Apr

Other references · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2023GPT-4 Technical Reportcited by 18,132
  4. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  5. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,970
  6. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,883
  7. 2024Mixtral of Expertscited by 1,785
  8. 2022Large Language Models Struggle to Learn Long-Tail Knowledgecited by 452
  9. 2023Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunitiescited by 89
  10. 2023TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledgecited by 62
  11. 2023Large Language Models Empowered Autonomous Edge AI for Connected Intelligencecited by 55
  12. 2023Large Language Models for Telecom: Forthcoming Impact on the Industrycited by 44
8 more
  1. 2024WirelessLLM: Empowering Large Language Models Towards Wireless Intelligencecited by 43
  2. 2023Understanding Telecom Language Through Large Language Modelscited by 32
  3. 2024Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6Gcited by 30
  4. 2023SPEC5G: A Dataset for 5G Cellular Network Protocol Analysiscited by 20
  5. 2023The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platformscited by 20
  6. 2023AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systemscited by 19
  7. 2024Telecom Language Models: Must They Be Large?cited by 10
  8. 2023Adapting Foundation Models for Information Synthesis of Wireless Communication Specificationscited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 15; 2026: 6.

26 papers.

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  1. 2025SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Mergingcited by 25
  2. 2024ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networkscited by 22
  3. 2025AgentRAN: An Agentic AI Architecture for Autonomous Control of Open 6G Networkscited by 15
  4. 2025ORANSight-2.0: Foundational LLMs for O-RANcited by 13
  5. 2024Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standardscited by 8
  6. 2025TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretationcited by 5
  7. 2024Telco-DPR: A Hybrid Dataset for Evaluating Retrieval Models of 3GPP Technical Specificationscited by 3
  8. 2025AI5GTest: AI-Driven Specification-Aware Automated Testing and Validation of 5G O-RAN Componentscited by 3
  9. 2026Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generationcited by 3
  10. 2024TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Networkcited by 2
  11. 2025Towards a Foundation Model for Communication Systemscited by 2
  12. 2026TeleResilienceBench: Quantifying Resilience for LLM Reasoning in Telecommunicationscited by 2
14 more
  1. 2026GENESIS: Harnessing AI Agents for Autonomous 6G RAN Synthesis, Research, and Testingcited by 2
  2. 2025Distilling Large Language Models for Network Active Queue Managementcited by 1
  3. 2025Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generationcited by 1
  4. 2025From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communicationscited by 1
  5. 2025How to Discover Knowledge for FutureG: Contextual RAG and LLM Prompting for O-RANcited by 1
  6. 2026TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications?cited by 1
  7. 2024Rephrase and Contrast: Fine-Tuning Language Models for Enhanced Understanding of Communication and Computer Networkscited by 0
  8. 2025SafeCOMM: A Study on Safety Degradation in Fine-Tuned Telecom Large Language Modelscited by 0
  9. 2025Concept-Level AI for Telecom: Moving Beyond Large Language Modelscited by 0
  10. 2025DeepSpecs: Expert-Level Questions Answering in 5Gcited by 0
  11. 2025MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applicationscited by 0
  12. 2025TelcoAI: Advancing 3GPP Technical Specification Search through Agentic Multi-Modal Retrieval-Augmented Generationcited by 0
  13. 2026Customized Generative AI Agent for Transportation Engineering Practice: A Development and Continued Pre-training Guidelinecited by 0
  14. 2026TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Taskscited by 0

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  1. 2024TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs
  2. 2024Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities
  3. 2025Chat3GPP: An Open-Source Retrieval-Augmented Generation Framework for 3GPP Documents
  4. 2026TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack
  5. 2026Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensembling
  6. 2024Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
  7. 2024ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
  8. 2026TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications