Competing at Every Price Point with Agentic Evolution over a Menu of LLMs
This paper shows a path to multi-LLM Python agents with Pareto domination of both the top-scoring and the lowest-cost competing points by evolving multi-LLM Python agents from training pools of at most 100 examples.
Andrew Borthwick
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