activity
20172023
most citedMen Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints

124 citations · 243 across the 12 of their papers we have counts for

collaborators

13 papers

cs.LG20221 cited

Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN

Anaelia Ovalle, Sunipa Dev, Jieyu Zhao +2

Auditing machine learning-based (ML) healthcare tools for bias is critical to preventing patient harm, especially in communities that disproportionately face health inequities. Gen…

cs.CL2022

Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers

Jieyu Zhao, Xuezhi Wang, Yao Qin +2

Large pre-trained language models have shown remarkable performance over the past few years. These models, however, sometimes learn superficial features from the dataset and cannot…

cs.CL20228 cited

DisinfoMeme: A Multimodal Dataset for Detecting Meme Intentionally Spreading Out Disinformation

Jingnong Qu, Liunian Harold Li, Jieyu Zhao +2

Disinformation has become a serious problem on social media. In particular, given their short format, visual attraction, and humorous nature, memes have a significant advantage in…

cs.CL20201 cited

LOGAN: Local Group Bias Detection by Clustering

Jieyu Zhao, Kai-Wei Chang

Machine learning techniques have been widely used in natural language processing (NLP). However, as revealed by many recent studies, machine learning models often inherit and ampli…

cs.IR202017 cited

Fairness-Aware Explainable Recommendation over Knowledge Graphs

Zuohui Fu, Yikun Xian, Ruoyuan Gao +8

There has been growing attention on fairness considerations recently, especially in the context of intelligent decision making systems. Explainable recommendation systems, in parti…

cs.CL20201 cited

Mitigating Gender Bias Amplification in Distribution by Posterior Regularization

Shengyu Jia, Tao Meng, Jieyu Zhao +1

Advanced machine learning techniques have boosted the performance of natural language processing. Nevertheless, recent studies, e.g., Zhao et al. (2017) show that these techniques…