232 citations · 300 across the 7 of their papers we have counts for
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cs.CL2019★ 232 cited
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data
Divyansh Kaushik, Eduard Hovy, Zachary C. Lipton
Despite alarm over the reliance of machine learning systems on so-called spurious patterns, the term lacks coherent meaning in standard statistical frameworks. However, the languag…
cs.LG2019★ 57 cited
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Yifan Wu, Ezra Winston, Divyansh Kaushik +1
Domain adaptation addresses the common problem when the target distribution generating our test data drifts from the source (training) distribution. While absent assumptions, domai…