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
problem.


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 …

arxiv

More from arxiv.org / cs.LG updates on arXiv.org

Senior Data Engineer

@ DAZN | Hammersmith, London, United Kingdom

Sr. Data Engineer, Growth

@ Netflix | Remote, United States

Data Engineer - Remote

@ Craft | Wrocław, Lower Silesian Voivodeship, Poland

Manager, Operations Data Science

@ Binance.US | Vancouver

Senior Machine Learning Researcher for Copilot

@ GitHub | Remote - Europe

Sr. Marketing Data Analyst

@ HoneyBook | San Francisco, CA