AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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System One models choose an agent's next action by scoring a supplied set of options in a single pass. This makes them fast and cheap, but when they choose wrongly there is nothing to inspect: did the model misread what the agent has seen, or read it correctly and still act wrongly? We answer behaviorally. On a frozen...
Standard accuracy flatters all ten models the authors evaluate and reorders their ranking, and prompting fixes that look effective largely vanish under paired scoring.
LLM-as-a-judge scales evaluation, but reasoning judges are slow and costly. We study JEV-as-a-Judge: evaluation with JEV, a decision-only judge that returns label probabilities instead of text, and whose confidence decides whether to accept its verdict or escalate to a reasoning judge. Against sixteen generative and re...
A taxonomy-driven survey asks how dynamic skill libraries change over time in large language model agents, and synthesizes dynamic skill systems as lifecycle-managed, verified, evolving artifact stores.
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