In this paper, we study temporal bias in biomedical research articles by measuring gender differences in word embeddings.
In this paper, we look at the temporal change of gender bias in biomedical research. To study social biases, we make use of word embeddings trained on different�...
2020. pdf bib abs. Quantifying 60 Years of Gender Bias in Biomedical Research with Word Embeddings � Anthony Rios | Reenam Joshi | Hejin Shin
This paper applies the WEAT bias detection method to four sets of word embeddings trained on corpora from four different domains: news, social networking,�...
Quantifying 60 Years of Gender Bias in Biomedical Research with Word Embeddings � no code implementations • WS 2020 • Anthony Rios, Reenam Joshi, Hejin Shin.
Dec 16, 2021 � Quantifying 60 years of gender bias in biomedical research with word embeddings. In: Proceedings of the 19th SIGBioMed Workshop on�...
In this paper, we develop a framework to demonstrate how the temporal dynamics of the embedding helps to quantify changes in stereotypes and attitudes toward�...
Aug 4, 2024 � Quantifying 60 years of gender bias in biomedical research with word embeddings. In Proceedings of the 19th SIGBioMed Workshop on Biomed�...
Rios et al. (2020) quantified 60 years of gender bias in biomedical research with skip-gram model of word embeddings. In the clinical context, studies.
Apr 11, 2022 � Our study focuses on the detection and measurement of stereotypical biases associated with gender in the embeddings of T5 and mT5.
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