AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes ATLAS, a dual-horizon diagnostic evaluation framework for industrial tool-use agents that instantiates LLM judge interfaces as executable signals with explicit evidence scopes and decision boundaries, and evaluates ATLAS on Meituan Xiaotuan production traffic.
This work proposes SAFE-G, a Structure-Aware Faithful Evidence-guided Generation framework, which enables precise evidence localization and trustworthy reasoning and introduces a reinforcement learning strategy with an evidence-grounded reward that assigns credit to correct answers only when the selected evidence is correct.
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