Web: http://arxiv.org/abs/2201.12091

Jan. 31, 2022, 2:11 a.m. | Shauli Ravfogel, Michael Twiton, Yoav Goldberg, Ryan Cotterell

cs.LG updates on arXiv.org arxiv.org

Modern neural models trained on textual data rely on pre-trained
representations that emerge without direct supervision. As these
representations are increasingly being used in real-world applications, the
inability to \emph{control} their content becomes an increasingly important

We formulate the problem of identifying and erasing a linear subspace that
corresponds to a given concept, in order to prevent linear predictors from
recovering the concept. We model this problem as a constrained, linear minimax
game, and show that existing solutions are …


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