AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Since compact, interpretable classifiers correspond to simple programs, it is natural to ask if LLM-based coding agents can be used to learn interpretable models from data. In this paper we present a simple harness that repeatedly prompts a coding LLM to produce the next rule in a rule set, given a sample of labeled ex...
This paper describes an agent framework that enables designers to enforce modularity in agentic systems, by defining pseudo-tools that call LLMs recursively on a restricted context, and proposes novel learning methods for the agentic components required by this framework, namely pseudo-tools and fixed workflows.
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