NH-CROP introduces a robust online pricing method for governed language data with uncertain costs, using a selective verification gate that improves or matches baselines without relying heavily on paid information acquisition.
Documenting large webtext corpora: A case study on the colossal clean crawled corpus
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NH-CROP: Robust Pricing for Governed Language Data Assets under Cost Uncertainty
NH-CROP introduces a robust online pricing method for governed language data with uncertain costs, using a selective verification gate that improves or matches baselines without relying heavily on paid information acquisition.