AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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QuAD, a framework for quantitative pre-analysis assessment of qualitative response datasets, is introduced and a content-aware multi-agent system with two-stage instruction generation and adaptive anchors to improve scoring consistency is proposed.
RegulAR models task instructions as a hierarchical dependency graph and combines this structure with a Multimodal Large Language Model (MLLM) to interpret egocentric observations during execution and enables RegulAR to track progress, identify deviations by error type, estimate their impact on later steps, and deliver...
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