Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings

ACM Conference on Health, Inference, and Learning (CHIL), 2020

11 March 2020

H. Zhang

Amy X. Lu

Mohamed Abdalla

Matthew B. A. McDermott

Marzyeh Ghassemi

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Papers citing "Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings"

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Gender bias in (non)-contextual clinical word embeddings for stereotypical medical categories Gizem Sogancioglu Fabian Mijsters Amar van Uden Jelle Peperzak 113 3 0 02 Aug 2022
BigBIO: A Framework for Data-Centric Biomedical Natural Language ProcessingNeural Information Processing Systems (NeurIPS), 2022 Jason Alan Fries Leon Weber Natasha Seelam Gabriel Altay Debajyoti Datta ... Minh Chien Vu Trishala Neeraj Jonas Golde Albert Villanova del Moral Benjamin Beilharz LM&MA 200 53 0 30 Jun 2022
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Richer Countries and Richer RepresentationsFindings (Findings), 2022 Kaitlyn Zhou Kawin Ethayarajh Dan Jurafsky 133 9 0 10 May 2022
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Theories of "Gender" in NLP Bias ResearchConference on Fairness, Accountability and Transparency (FAccT), 2022 Hannah Devinney Jenny Björklund H. Björklund AI4CE 162 83 0 05 May 2022