When LLMs Sit Above Diagnostic Tools: Unrealized Complementarity in Industrial Fault Diagnosis
Large language models are increasingly used as integration layers above specialized tools, but a stronger component does not necessarily produce a stronger combined system. Across five diagnostic datasets (bearing vibration, process monitoring, semiconductor equipment), we study whether an LLM can reliably use external diagnostic information; paired repeat calls separate advice effects from output instability. In all five, conflicting external information overturned initially correct LLM judgments. Among the four datasets with direct integration comparisons, none showed a consistent advantage for implicit LLM integration over the stronger standalone source. On a Tennessee Eastman confirma...
| Authors | Donghwan Kim |
|---|---|
| Primary category | cs.CL |
| Published | 4 October 2026 |
| Last updated at source | 8 October 2026 |
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