AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The need for more user-centered studies to measure LLMs'ability to help users while preserving privacy, and for improving alignment between LLMs and users in estimating perceived privacy and utility, is discussed.
This work explores the application of pre-trained time-series foundation models (FMs) for detecting anomalies in industrial processes and introduces a new time-series forecasting method that filters out suspicious data and uses previously predicted data as input, called Forecast Fallback (FF).
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