AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is found that Astra exhibits token-efficient directed reasoning, selecting a correct trajectory earlier, while resolving elementary steps internally and externalizing only crucial reasoning, which provides a behavioral lens on frontier-model reasoning beyond benchmark scores.
The results show that colluding semi-honest nodes can recover the original local updates of honest nodes, enabling downstream reconstruction of private training data, and demonstrate that SA alone does not guarantee privacy in DFL when local aggregation induces asymmetric observations.
A trust-aware post-routing framework is proposed that reweights clients using returned-evidence feedback, including retrieval relevance, profile consistency, and cross-client agreement, and online experiments show that it suppresses persistent hijacking over recurring queries and transfers to a learned neural router.
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