Backend
Preventing Data Hallucinations in Agentic AI for Optical Network Troubleshooting
arXiv cs.NI0 views
arXiv:2610.23252v1 Announce Type: new 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.
Source：https://arxiv.org/abs/2610.23252PreviousFast BSS Transition for Multi-PSK Community Wi-Fi in MDU Networks: Fragmented RADIUS Key Delivery, Server-Derived PMK-R0/PMK-R1 Distribution through a Cloud Management API, and Lease-Driven Key RevocaNextFluid-Spatiotemporal Stochastic Geometry for Information Flow in Non-Stationary Fields: Kinematics and Field Reconstruction
Related posts
Convert PNG to JPEG or WebP in the Browser: What Happens to Transparency
0dev.to
How I Built a Privacy-Focused Loan Calculator with Pure JavaScript and Chart.js
0dev.to
Game Development for Startups: From MVP to Launch
0dev.to
Integrate App Event Logging Without Advanced Infrastructure — A Rollback-Safe Checkout API
0dev.to
Password Reset Deliveries: 3 Receipt Template Controls for Email Domain Reputation
0dev.to
Base64 in the Browser: UTF-8 Bytes, Padding and a Round Trip You Can Check
0dev.to