AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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RAISE is introduced, which trains policy synthesizers from formal verification in two stages, verified supervised fine-tuning (SFT) followed by a reinforcement learning (RL) stage that learns from verifier signal, and it is found that SFT succeeds largely by letting models express authorization logic they already have.
Large Language Models are increasingly used to turn natural-language requirements into code. In access control, that shortcut is dangerous: a generated policy can compile and read correctly while granting access that no one approved. The difficulty is not only writing policy code. It is fixing what the requirements mea...
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