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Spend Less, Fit Better: Budget-Efficient Scaling Law Fitting via Active Experiment Selection

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学术前沿 6.0 分 — Useful for ML infrastructure planning: active experiment selection for scaling law fitting. Niche but valuable.
原文: arxiv.org

评分 6 · 来源: · 发布于 2026-04-27

评分依据:Useful for ML infrastructure planning: active experiment selection for scaling law fitting. Niche but valuable.