arXiv cs.AI· Jeremias D\"otterl, Martin Kuipers·· 12 小时前AI 评分22
面向光网络故障排查的智能体 AI：通过数据引用防止数据幻觉
Preventing Data Hallucinations in Agentic AI for Optical Network Troubleshooting
AI 导读
一个用于光通信网络自动故障排查的智能体 AI 系统，通过在智能体架构中集成数据引用防止数据幻觉，提升了根因识别与推理的可解释性和可信度。该系统以 demo 形式在 ECOC 2026 展示。
正文 · 原文
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.
| Comments: | Presented as a demo at the 52nd European Conference on Optical Communication (ECOC 2026) |
| Subjects: | Networking and Internet Architecture (cs.NI); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.23252 [cs.NI] |
| (or arXiv:2610.23252v1 [cs.NI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.23252 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Jeremias Dötterl [view email]
[v1]
Fri, 16 Oct 2026 10:25:35 UTC (194 KB)
来源：arXiv cs.AI · arxiv.org