LLMs need structured reasoning frameworks with evidence grounding to reliably diagnose telecom network faults—vanilla LLMs hallucinate and produce unstable reasoning without domain-specific constraints and verifiable decision paths.
This paper addresses root cause analysis (RCA) in telecom networks by proposing a structured reasoning framework for LLMs that reduces hallucination and improves diagnostic accuracy. The approach organizes network data into canonical contexts, enforces decision-path reasoning, and grounds explanations in evidence, demonstrating improvements on 5G network datasets.