Papers by Dora Zhao
Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes (2024.emnlp-main)
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Yusuke Hirota, Jerone Andrews, Dora Zhao, Orestis Papakyriakopoulos, Apostolos Modas, Yuta Nakashima, Alice Xiang
| Challenge: | Traditional approaches only target labeled attributes, ignoring biases from unlabeled ones. |
| Approach: | They propose a method that ensures protected group independence from all attributes and mitigates inpainting biases through data filtering. |
| Outcome: | The proposed approach achieves an average reduction of 46.1% in leakage-based bias metrics for multi-label classification and 74.8% for image captioning. |
SPHERE: An Evaluation Card for Human-AI Systems (2025.findings-acl)
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Dora Zhao, Qianou Ma, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, Tongshuang Wu
| Challenge: | Existing evaluation methods and standards for human-AI systems are unclear, especially for large language models. |
| Approach: | They propose an evaluation card SPHERE which provides a template for evaluation protocols . they outline current evaluation practices and areas for improvement . |
| Outcome: | The evaluation card provides a template for designing evaluation protocols . it outlines current evaluation practices and areas for improvement . |