AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Optimo is proposed, a multi-level LLM-based code optimization approach built on a novel Mixture-of-Prompts (MoP) architecture that achieves up to 57.48% opt%, and consistently outperforms the best baseline by up to 96.51% in terms of opt%.
This initial study demonstrates that directly prompting off-the-shelf code LLMs remains ineffective; even advanced prompting strategies cannot compensate for the lack of task-specific knowledge, and fine-tuning proves highly effective, with pseudo-code representation consistently yielding the best performance.
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