2025
AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists
EMNLP 2025
Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-quality data for training and evaluation. To tackle this data scarcity issue, we present AutoSDT, an automatic pipeline that collects high-quality coding task