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Researchers develop HUGO framework to extract cold spray data from literature

By PulseAugur Editorial · [1 sources] ·

Researchers have developed HUGO-CS, a novel dataset containing 4,383 cold-spray experiments extracted from scientific literature. This dataset significantly expands upon previous efforts, being over 30 times larger than the prior largest dataset. To create HUGO-CS, a framework called HUGO was employed, which combines automated LLM-based labeling with manual refinement to ensure accuracy and efficiency in data extraction from complex experimental results. AI

IMPACT This dataset could accelerate research and optimization in cold spray manufacturing by providing a large, structured source of experimental data.

RANK_REASON This is a research paper detailing a new dataset and extraction framework. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Researchers develop HUGO framework to extract cold spray data from literature

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This is a research paper detailing a new dataset and extraction framework. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Stephen Price, Kyle Miller, Marco Musto, Kenneth Kroenlein, James Saal, Kyle Tsaknopoulos, Elke A. Rundensteiner, Danielle L. Cote ·

    HUGO-CS: A Hybrid-Labeled, Uncertainty-Aware, General-Purpose, Observational Dataset for Cold Spray

    arXiv:2605.04257v1 Announce Type: new Abstract: Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However, process optimization remains difficult due to many interdependent parameters and…

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