12 citations · 21 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 1 cited
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach
Zhao Wang, Kai Shu, Aron Culotta
Recent work has raised concerns on the risk of spurious correlations and unintended biases in statistical machine learning models that threaten model robustness and fairness. In th…
cs.LG2020★ 12 cited
Robustness to Spurious Correlations in Text Classification via Automatically Generated Counterfactuals
Zhao Wang, Aron Culotta
Spurious correlations threaten the validity of statistical classifiers. While model accuracy may appear high when the test data is from the same distribution as the training data,…
cs.LG2020★ 8 cited
Identifying Spurious Correlations for Robust Text Classification
Zhao Wang, Aron Culotta
The predictions of text classifiers are often driven by spurious correlations -- e.g., the term `Spielberg' correlates with positively reviewed movies, even though the term itself…