Adapting Network Information Into Semantics for Generalizable and Plug-and-Play Multi-Scenario Network Diagnosis
Leveraging large language models (LLMs) for fault diagnosis in communication networks is considered a promising direction. However, communication-network faults often manifest as cross-layer degradations and are reflected in heterogeneous observations, making them difficult to directly represent for LLM reasoning. This...