Preventing Data Hallucinations in Agentic AI for Optical Network Troubleshooting
Presented as a demo at the 52nd European Conference on Optical Communication (ECOC 2026)
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.
兴趣：multi-agent systems and LLM agents