AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is found that the evidence state improves performance over in-context accumulation, and it also matters what is stored in it.
This case study reveals a systematic gap that LLM quality metrics do not predict human learning outcomes and point to explanation complexity relative to task difficulty as a key factor, and calls for explanation methods and evaluation criteria grounded in human cognitive constraints rather than LLM preference.
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