AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Modern LLM post-training composes supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and on-policy distillation (OPD) into multi-stage pipelines, yet these stages are typically designed and evaluated in isolation. We show that this composition is consequential: a stage that improves th...
These findings expose a critical weakness in current LLM agents: even when they initially reason correctly, they can be steered toward false conclusions by optimized natural language influence, which positions persuasion robustness as a necessary safety criterion for multi-agent and human-AI decision-making systems.
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