AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is found that defenses rarely improve downstream capability, but instead vary in how they trade safety gains against usability and efficiency as well as performance impact, over-refusal on benign inputs, and inference cost.
This work proposes MoEGen, an adaptation framework that shifts MoE-based PEFT from expert selection to expert-conditioned parameter generation, and decouples expert capacity from adapter storage while enabling instance-conditioned adaptation.
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