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
Most AI text detectors look good in testing. They’re trained and evaluated on specific models, specific prompt styles, specific domains — and they perform well within that distribution. Then they get deployed into the real world, which has different models, different prompting patterns, different domains, and the performance drops. This
