177 citations · 403 across the 10 of their papers we have counts for
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cs.LG2021★ 8 cited
Causally motivated Shortcut Removal Using Auxiliary Labels
Maggie Makar, Ben Packer, Dan Moldovan +3
Shortcut learning, in which models make use of easy-to-represent but unstable associations, is a major failure mode for robust machine learning. We study a flexible, causally-motiv…
cs.LG2021★ 22 cited
Measuring Recommender System Effects with Simulated Users
Sirui Yao, Yoni Halpern, Nithum Thain +6
Imagine a food recommender system -- how would we check if it is \emph{causing} and fostering unhealthy eating habits or merely reflecting users' interests? How much of a user's ex…