
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

Researchers built a study to answer a question that sounds simple: can people tell whether a scientific abstract was written by an LLM or a human? The answer, for people with machine-learning expertise, was mostly: no. This result is interesting on its own. The implications for how we build annotation
