AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces $\mathrm{ASR}_{\mathrm{STEP}}$, which penalizes additional victim-model calls while retaining binary success judgments, and considers GCG, PAIR with a step budget, and a single-step PAP baseline on JailBreakBench across three model families.
The results show that the two recipes recover partially overlapping geometry and that direction based defences should be calibrated separately for each language decoder family.
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