AI RESEARCH
NH-CROP: Robust Pricing for Governed Language Data Assets under Cost Uncertainty
arXiv CS.CL
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ArXi:2605.01745v1 Announce Type: cross Language data are increasingly acquired and governed as assets, yet platforms often price candidate resources before knowing their true privacy or access costs. We study online pricing for governed language data assets under cost uncertainty. At each round, a platform observes an NLP task, a candidate asset, and a coarse cost estimate, may pay for a refined cost signal, posts a price, and receives safe net revenue.