Understanding and Mitigating the Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks
Published in ACL 2026, Oral, 2026
This work studies bias inheritance in LLM-based data augmentation. It analyzes how different types of bias appear at varying augmentation ratios and evaluates mitigation strategies across classification and generation tasks.
Recommended citation: Miaomiao Li, Hao Chen, Yang Wang, Tingyuan Zhu, Weijia Zhang, Kaijie Zhu, Kam-Fai Wong, and Jindong Wang. (2026). "Understanding and Mitigating the Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks." ACL 2026. Oral.
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