ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networks
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Abstract (arXiv)
Large Language Models (LLMs) can revolutionize how we deploy and operate Open Radio Access Networks (O-RAN) by enhancing network analytics, anomaly detection, and code generation and significantly increasing the efficiency and reliability of a plethora of O-RAN tasks. In this paper, we present ORAN-Bench-13K, the first comprehensive benchmark designed to evaluate the performance of Large Language Models (LLMs) within the context of O-RAN. Our benchmark consists of 13,952 meticulously curated multiple-choice questions generated from 116 O-RAN specification documents. We leverage a novel three-stage LLM framework, and the questions are categorized into three distinct difficulties to cover a wide spectrum of ORAN-related knowledge. We thoroughly evaluate the performance of several state-of-the-art LLMs, including Gemini, Chat-GPT, and Mistral. Additionally, we propose ORANSight, a Retrieval-Augmented Generation (RAG)-based pipeline that demonstrates superior performance on ORAN-Bench-13K compared to other tested closed-source models. Our findings indicate that current popular LLM models are not proficient in O-RAN, highlighting the need for specialized models. We observed a noticeable performance improvement when incorporating the RAG-based ORANSight pipeline, with a Macro Accuracy of 0.784 and a Weighted Accuracy of 0.776, which was on average 21.55% and 22.59% better than the other tested LLMs.
Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 18 of its 37 references that are in the map. First posted on arXiv 8 Jul 2024.
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18 of 37 references.
References · 18
- 2020Language Models are Few-Shot Learnerscited by 32,199
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Citing papers per year: 2024: 2; 2025: 10; 2026: 10.
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- 2025ORANSight-2.0: Foundational LLMs for O-RANcited by 13
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- 2025Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systems23 Dec 2025
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10 more
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- 2025Accurate and Energy Efficient: Local Retrieval-Augmented Generation Models Outperform Commercial Large Language Models in Medical Tasks24 Jun 2025
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- 2025Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing31 May 2025
- 2025Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generation31 Mar 2025
- 2025ORANSight-2.0: Foundational LLMs for O-RAN7 Mar 2025
- 2025Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation10 Feb 2025
- 2024TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Network4 Nov 2024
- 2024Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards21 Aug 2024
- 2024Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standardscited by 8
- 2026Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generationcited by 3
- 2024TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Networkcited by 2
- 2025Accurate and Energy Efficient: Local Retrieval-Augmented Generation Models Outperform Commercial Large Language Models in Medical Taskscited by 2
- 2025Benchmarking Vector, Graph and Hybrid Retrieval Augmented Generation (RAG) Pipelines for Open Radio Access Networks (ORAN)cited by 2
- 2025Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generationcited by 1
- 2026Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generation19 Feb 2026
- 2025Benchmarking Vector, Graph and Hybrid Retrieval Augmented Generation (RAG) Pipelines for Open Radio Access Networks (ORAN)4 Jul 2025
- 2025Accurate and Energy Efficient: Local Retrieval-Augmented Generation Models Outperform Commercial Large Language Models in Medical Tasks24 Jun 2025
- 2025Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generation31 Mar 2025
- 2024TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Network4 Nov 2024
- 2024Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards21 Aug 2024
- 2025Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluationcited by 27
- 2026TeleResilienceBench: Quantifying Resilience for LLM Reasoning in Telecommunicationscited by 2
- 2026TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stackcited by 0
- 2026CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RANcited by 0
- 2026TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Taskscited by 0
- 2026TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Tasks21 Sep 2026
- 2026CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RAN1 Sep 2026
- 2026TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack22 Jun 2026
- 2026TeleResilienceBench: Quantifying Resilience for LLM Reasoning in Telecommunications11 May 2026
- 2025Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation10 Feb 2025
- 2025ORANSight-2.0: Foundational LLMs for O-RANcited by 13
- 2025ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicingcited by 3
- 2025Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicingcited by 2
- 2025Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systemscited by 2
- 2025Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmapcited by 1
- 2025How to Discover Knowledge for FutureG: Contextual RAG and LLM Prompting for O-RANcited by 1
- 2026Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensemblingcited by 0
- 2026TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunicationscited by 0
- 2026TelcoAgent: A Scalable 5G Multi-KPM Forecasting With 3GPP-Grounded Explainabilitycited by 0
- 2026CTBench: Evaluating Troubleshooting Capabilities of AI Agents in Realistic Telecom Network Operationscited by 0
- 2026Free-Text Evaluation of LLMs for 5G Domain Knowledge and Fault Analysis using LLM-as-Judgecited by 0
- 2026Free-Text Evaluation of LLMs for 5G Domain Knowledge and Fault Analysis using LLM-as-Judge21 Aug 2026
- 2026CTBench: Evaluating Troubleshooting Capabilities of AI Agents in Realistic Telecom Network Operations12 Aug 2026
- 2026TelcoAgent: A Scalable 5G Multi-KPM Forecasting With 3GPP-Grounded Explainability18 Jun 2026
- 2026TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications20 Apr 2026
- 2026Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensembling14 Apr 2026
- 2025Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systems23 Dec 2025
- 2025How to Discover Knowledge for FutureG: Contextual RAG and LLM Prompting for O-RAN18 Dec 2025
- 2025Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmap26 Aug 2025
- 2025ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing31 May 2025
- 2025Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing31 May 2025
- 2025ORANSight-2.0: Foundational LLMs for O-RAN7 Mar 2025
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