AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Large Language Models (LLMs) treat all context tokens uniformly, lacking explicit separation between executable instructions and passive data. This leads to prompt injection vulnerabilities, ambiguous instruction binding, and unreliable execution control. We present a post-training methodology using LLMON (LLM Object N...
It is argued that explanation privacy should be evaluated as an end-to-end disclosure problem, with defenses matched to the acquisition path and protected asset, with defenses matched to the acquisition path and protected asset.
A cost-effective label-only MIA framework based on transferability and model extraction, which removes the restriction that defines the label-only setting, and characterize how leakage transfer depends on surrogate fidelity.
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