AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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EviGraph, which distinguishes critical decision requirements from information that can remain unresolved in a temporal knowledge graph, is introduced, suggesting that reliable evidence-based navigation depends on specifying what must be established for a decision, rather than simply adding more verification.
Offline replay should estimate what a discovery system could retrieve at a historical point, yet freezing the corpus leaves interaction memory unconstrained. We formalize point-in-time (PIT) discovery through historical state $(D_t, \theta_t, M_{<i})$ and introduce a paired replay that changes only memory availability....
A large language model (LLM) agent can follow more graph paths without acquiring more independent evidence. GraphEcho tests whether agents mistake these repeated encounters for additional corroboration. The benchmark varies path counts and evidential origins while holding evidence content fixed, and evaluates both judg...
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