Papers by Tzu-Yao Chiu

1 papers
AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists (2025.emnlp-main)

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Challenge: AutoSDT-5K is the only automatically collected and the largest open dataset for data-driven scientific discovery.
Approach: They propose an automatic pipeline that collects high-quality coding tasks in real-world data-driven discovery workflows.
Outcome: The proposed pipeline synthesizes accurate tasks and tasks from a dataset of 5,404 tasks covering four scientific disciplines and 756 Python packages.

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