AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The VEX-Bench is introduced, a unified benchmark for evaluating the verification complexity of LLM-generated misinformation, as perceived during screening, across models and generation methods, and shows that no single method dominates all dimensions, underscoring the need for multi-dimensional evaluation.
The benchmark evaluates whether agents can recognize and interrupt harm arising from accumulated context, repeated tool use, intermediate actions, and dependencies across steps, and indicates that current systems remain highly vulnerable.
This survey examines the protective paradigm that has grown around this intervention point, and finds that most protections are still validated mainly against static or weakly adaptive adversaries, while evidence beyond controlled benchmarks remains scarce.
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