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Fair Machine Learning in Healthcare: A Review



Qizhang Feng , Mengnan Du , Na Zou , Xia Hu


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Accelerating Shapley Explanation via Contributive Cooperator Selection



Guanchu Wang , Yu-Neng Chuang , Mengnan Du , Fan Yang , Quan Zhou , Pushkar Tripathi , Xuanting Cai , Xia Hu


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Unveiling Project-Specific Bias in Neural Code Models



Zhiming Li , Yanzhou Li , Tianlin Li , Mengnan Du , Bozhi Wu , Yushi Cao , Xiaofei Xie , Yi Li , Yang Liu


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What do Compressed Large Language Models Forget? Robustness Challenges in Model Compression



Mengnan Du , Subhabrata Mukherjee , Yu Cheng , Milad Shokouhi , Xia Hu , Ahmed Hassan Awadallah


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Fairness via Representation Neutralization



Mengnan Du , Subhabrata Mukherjee , Guanchu Wang , Ruixiang Tang , Ahmed Hassan Awadallah , Xia Hu


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A General Taylor Framework for Unifying and Revisiting Attribution Methods



Huiqi Deng , Na Zou , Mengnan Du , Weifu Chen , Guocan Feng , Xia Hu


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Learning Disentangled Representations for Time Series



Yuening Li , Zhengzhang Chen , Daochen Zha , Mengnan Du , Denghui Zhang , Haifeng Chen , Xia Hu


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Interpretable Time-series Representation Learning With Multi-Level Disentanglement



Yuening Li , Zhengzhang Chen , Daochen Zha , Mengnan Du , Denghui Zhang , Haifeng Chen , Xia Hu


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Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution



Huiqi Deng , Na Zou , Weifu Chen , Guocan Feng , Mengnan Du , Xia Hu


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Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models



Mengnan Du , Varun Manjunatha , Rajiv Jain , Ruchi Deshpande , Franck Dernoncourt , Jiuxiang Gu , Tong Sun , Xia Hu

* Accepted by NAACL 2021 

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