Preventing Data Hallucinations in Agentic AI for Optical Network Troubleshooting

arXiv:2610.23252v1 Announce Type: cross
Abstract: An agentic AI system for automated troubleshooting in optical communication networks is demonstrated that integrates data references into the agent architecture to prevent data hallucinations, improving the interpretability and trustworthiness of root-cause identification and reasoning.

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