Root Cause Analysis Method Based on Large Language Models with Residual Connection Structures

This research proposes a novel root cause analysis method that leverages large language models (LLMs) enhanced with residual connection structures. The approach aims to improve the accuracy and efficiency of identifying the underlying causes of complex system failures, offering significant potential for applications in IT operations, manufacturing diagnostics, and complex engineering systems.