Researchers develop HUGO framework to extract cold spray data from literature

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

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

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

在 arXiv cs.LG 阅读 →

• HUGO
• LLM

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