63 citations · 111 across the 22 of their papers we have counts for
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cs.CL2022★ 1 cited
Controlling Bias Exposure for Fair Interpretable Predictions
Zexue He, Yu Wang, Julian McAuley +1
Recent work on reducing bias in NLP models usually focuses on protecting or isolating information related to a sensitive attribute (like gender or race). However, when sensitive in…
cs.LG2022★ 2 cited
Differentiable Invariant Causal Discovery
Yu Wang, An Zhang, Xiang Wang +3
Learning causal structure from observational data is a fundamental challenge in machine learning. However, the majority of commonly used differentiable causal discovery methods are…
cs.LG2022★ 21 cited
Improving Out-of-Distribution Robustness via Selective Augmentation
Huaxiu Yao, Yu Wang, Sai Li +4
Machine learning algorithms typically assume that training and test examples are drawn from the same distribution. However, distribution shift is a common problem in real-world app…