Toward Scalable, Robust, and Open-Ended LLM-EC Integration
摘要
Issues of scale fundamentally condition the interaction between LLMs and EC. When LLMs are used as components within EC pipelines—whether as optimizers, evaluators, generators, or controllers—the cost and feasibility of training and inference, the reliability of reasoning, and the ability to ingest and act upon long optimization histories all become central.