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cs.AI2026
CTBench: Evaluating Troubleshooting Capabilities of AI Agents in Realistic Telecom Network Operations
Xingyu Yan, Tingting Dai, Antonio De Domenico +16
While autonomous agents show promise for network operations, existing telecom troubleshooting evaluations fail to capture the partial observability and heterogeneity of real-world…
cs.AI2025
Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks
Mohamed Sana, Nicola Piovesan, Antonio De Domenico +4
Root Cause Analysis (RCA) in mobile networks remains a challenging task due to the need for interpretability, domain expertise, and causal reasoning. In this work, we propose a lig…
cs.AI2025
TeleMath: A Benchmark for Large Language Models in Telecom Mathematical Problem Solving
Vincenzo Colle, Mohamed Sana, Nicola Piovesan +3
The increasing adoption of artificial intelligence in telecommunications has raised interest in the capability of Large Language Models (LLMs) to address domain-specific, mathemati…