AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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StalePO is introduced, an objective derived from three requirements this regime imposes that improves the fraction of segments passing all LLM-as-judge MQM quality checks by 14.9 and 4.6 percentage points, respectively, with gains concentrated on style and fluency.
This work recognizes the involved Key Postures (KPs) and motions in the Adavu using Convolutional Neural Network (CNN) and Support Vector Machine (SVM), respectively, and compares these KP and motion sequences with the ground truth to find the best match using the Edit Distance algorithm.
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