Telco-RAG: Navigating the challenges of retrieval-augmented language models for telecommunications

[PDF] arxiv.org

Automatic Retrieval-Augmented Generation of 6G Network Specifications for Use Cases

Y Tang, W Guo - IEEE Communications Magazine, 2024 - ieeexplore.ieee.org
6G open radio access networks (O-RAN) promises to open data interfaces to enable plug-
andplay service apps, many of which are consumer and business-facing. Opening up 6G …
被引用次数：1 相关文章 所有 2 个版本
[PDF] arxiv.org

WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence

J Shao, J Tong, Q Wu, W Guo, Z Li, Z Lin… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid evolution of wireless technologies and the growing complexity of network
infrastructures necessitate a paradigm shift in how communication networks are designed …
被引用次数：21 相关文章 所有 2 个版本

A primer on generative AI for telecom: From theory to practice

X Lin, L Kundu, C Dick, MAC Galdon… - arXiv preprint arXiv …, 2024 - arxiv.org
The rise of generative artificial intelligence (GenAI) is transforming the telecom industry.
GenAI models, particularly large language models (LLMs), have emerged as powerful tools …
被引用次数：3 相关文章 所有 2 个版本
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Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards

O Erak, N Alabbasi, O Alhussein, I Lotfi… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent studies show that large language models (LLMs) struggle with technical standards in
telecommunications. We propose a fine-tuned retrieval-augmented generation (RAG) …
被引用次数：1 相关文章 所有 3 个版本
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Hermes: A Large Language Model Framework on the Journey to Autonomous Networks

F Ayed, A Maatouk, N Piovesan… - arXiv preprint arXiv …, 2024 - arxiv.org
The drive toward automating cellular network operations has grown with the increasing
complexity of these systems. Despite advancements, full autonomy currently remains out of …
被引用次数：1 相关文章 所有 2 个版本
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ColBERT Retrieval and Ensemble Response Scoring for Language Model Question Answering

A Gichamba, TK Idris, B Ebiyau, E Nyberg… - arXiv preprint arXiv …, 2024 - arxiv.org
Domain-specific question answering remains challenging for language models, given the
deep technical knowledge required to answer questions correctly. This difficulty is amplified …
被引用次数：1 相关文章 所有 3 个版本
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TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Network

N Alabbasi, O Erak, O Alhussein, I Lotfi… - arXiv preprint arXiv …, 2024 - arxiv.org
The telecommunications industry's rapid evolution demands intelligent systems capable of
managing complex networks and adapting to emerging technologies. While large language …
相关文章 所有 2 个版本
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TSpec-LLM: An Open-source Dataset for LLM Understanding of 3GPP Specifications

R Nikbakht, M Benzaghta, G Geraci - arXiv preprint arXiv:2406.01768, 2024 - arxiv.org
Understanding telecom standards involves sorting through numerous technical documents,
such as those produced by the 3rd Generation Partnership Project (3GPP), which is time …
被引用次数：10 相关文章 所有 2 个版本
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First Token Probability Guided RAG for Telecom Question Answering

T Chen, J Chen, Z Zhao, H Chen, L Zhang… - arXiv preprint arXiv …, 2025 - arxiv.org
Large Language Models (LLMs) have garnered significant attention for their impressive
general-purpose capabilities. For applications requiring intricate domain knowledge …
相关文章 所有 2 个版本
[PDF] arxiv.org

Telco-DPR: A Hybrid Dataset for Evaluating Retrieval Models of 3GPP Technical Specifications

T Saraiva, M Sousa, P Vieira, A Rodrigues - arXiv preprint arXiv …, 2024 - arxiv.org
This paper proposes a Question-Answering (QA) system for the telecom domain using 3rd
Generation Partnership Project (3GPP) technical documents. Alongside, a hybrid dataset …
相关文章 所有 3 个版本