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AutoSG features three core innovations: a retrieval-augmented solver generation module strictly grounding code in verified literature; a one-step self-refinement operator introducing task-specific improvements while preserving critical structural components; and an inst","title":"AutoSG: LLM-Driven Solver Generation Solely from Task Prompts for Expensive Optimization","url":"https://arxiv.org/abs/2605.25658","vendor":"arxiv_cs_ai"},"summary":"arXiv:2605.25658v1 Announce Type: cross \nAbstract: Expensive optimization tasks are ubiquitous in real-world applications, demanding highly specialized solvers. 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