
The 42× number that should change how you scope annotation projects
If you’ve worked on NLP for low-resource languages — Yoruba, Quechua, Tigrinya, Hmong — you know the math is brutal. Native speakers with domain expertise are scarce. Their time is
Booth 21-25 | AI Data Management Zone | Tokyo Big Sight

If you’ve worked on NLP for low-resource languages — Yoruba, Quechua, Tigrinya, Hmong — you know the math is brutal. Native speakers with domain expertise are scarce. Their time is

A 34-author survey led by Yu Xia at UC San Diego — with collaborators across Adobe Research and nine other labs — was accepted to ACL 2025, and it’s worth your time if you build data pipelines. The title carries the whole argument: “From Selection to Generation.” For most of
