AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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DIP is proposed, a context-optimization algorithm based on average verified confidence that dynamically ranks and inserts in-context examples during generation, rather than providing all examples up front.
Multi-Objective In-context Knowledge Editing (MO-IKE), a multi-objective RL algorithm that formulates prompt construction for in-context knowledge editing as a Constrained Markov Decision Process, enabling more balanced and globally coherent prompt construction.
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