AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work audits 22 frontier models on 12 molecular regression datasets in a zero-shot setting, assessed against a molecule-blind reference derived from each dataset's labels, finding significant retrieval is concentrated on 5 datasets, with isolated flagged LLMs elsewhere.
This work introduces the first multi-agent LLM-driven approach for constitutive model generation: a Creator agent proposes a model tailored to the data, while an Inspector agent critically audits each proposal against nine physical constraints and returns it for refinement whenever a violation is detected.
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