AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Results show that LLM-agent organization can emerge and adapt through repeated execution of a learned local law, and Swarm-Consistent Distillation (SCD), combining anonymous-orbit consistency with rollout-grounded prediction of the next local coordination field, with no added inference-time components.
LLM agents require reliable step-level evaluation to compare candidate branches and allocate computation effectively. However, lightweight evaluation remains challenging. External verifiers introduce additional inference cost, while agent-produced confidence or self-evaluation scores can be miscalibrated, especially wh...
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