AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces EXAM, an EXtremist Agent Modeling framework that capable of configuring extremist agents for specific tasks and precisely controlling their population proportion, spatial distribution, interaction protocols, and measurement interfaces.
NGM-RAG is introduced, a novel framework that leverages graph structures to effectively capture and utilize relational knowledge for improved retrieval and answer generation and proposes a neural graph matching approach that combines text-based matching with Graph Neural Networks (GNNs).
This work introduces a generalizable evaluation framework that maps native MAS traces into a shared space of unified collaboration graphs, enabling different methods to be evaluated under the same representation, reference set, and metric panel.
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