AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Frontier LLM agents perform complex interactive tasks, but their inference costs motivate transferring their experience to smaller open-source agents. Distillation and latent communication typically require target-model training or access to source-model internals. We study how textual frontier-model trajectories can p...
This work recasts vulnerability discovery as an input-prediction task with a closed, deterministic ground truth, and decomposes discovery into three task modes over 22 real-world C/C++ programs spanning 15 domains, finding constraint inference, not navigation, is the dominant bottleneck.
Results support treating PHD as a distinct target for evaluating how LLMs formulate investigative directions when final conclusions are withheld, with gains for several lower-performing models on HypoArena but regressions for other systems, including a top-performing model.
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