AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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SIAGXC, a prediction-augmented graph framework for XMLC that leverages auxiliary relational signals derived from an upstream XMLC model, demonstrates that prediction-derived auxiliary relations provide an effective way to enhance graph-based XMLC.
A unified framework is introduced that distills intermediate representations that explicitly encode the physical modeling process and adopt a two-stage post-training strategy, where supervised fine-tuning establishes structured modeling, and reinforcement learning with rubric-based feedback improves the quality of the...
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