AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Predicting whether an LLM agent will fail has emerged as a promising direction for supporting intervention during execution. Recent approaches report strong predictive performance, often with AUROC values between 0.85 and 0.94. However, predictors are typically trained by pooling runs from many tasks. We hypothesize th...
PyMOP is presented, a generic, extensible, and more efficient Python RV tool that supports five logics, implements five monitoring algorithms, ships with 81 specs, and supports three instrumentation strategies that help find hundreds of bugs by monitoring test executions against formal specifications.
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