Bio

Theodora (Teddi) Worledge is a PhD student in Computer Science at Stanford University, where she works on making machine learning models more reliable and trustworthy. Her research focuses on developing interpretability and attribution tools that help users verify and understand language model outputs. She is advised by Carlos Guestrin and supported by the NSF Graduate Research Fellowship. Before Stanford, she earned her BA in Computer Science from UC Berkeley.

Contact

  • Academic
    University - Student Department: Computer Science Position: Graduate

Additional Info

  • Mail Code: 9025

Links

All Publications

  • Unifying Corroborative and Contributive Attributions in Large Language Models Worledge, T., Shen, J., Meister, N., Winston, C., Guestrin, C., IEEE COMPUTER SOC IEEE COMPUTER SOC. 2024: 665-683

    View details for DOI 10.1109/SaTML59370.2024.00039

    View details for Web of Science ID 001227324000014

  • Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data Rolf, E., Worledge, T., Recht, B., Jordan, M. edited by Meila, M., Zhang, T. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2021

    View details for Web of Science ID 000768182705018