111 citations · 645 across the 33 of their papers we have counts for
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cs.CL2023★ 5 cited
"I'm" Lost in Translation: Pronoun Missteps in Crowdsourced Data Sets
Katie Seaborn, Yeongdae Kim
As virtual assistants continue to be taken up globally, there is an ever-greater need for these speech-based systems to communicate naturally in a variety of languages. Crowdsourci…
cs.CL2023★ 16 cited
Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts
Katie Seaborn, Shruti Chandra, Thibault Fabre
Critical scholarship has elevated the problem of gender bias in data sets used to train virtual assistants (VAs). Most work has focused on explicit biases in language, especially a…