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Measuring Gender Bias in Contextualized Embeddings
KTH. Peltarion AB.ORCID iD: 0000-0002-1747-3707
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering. (Information Science and Engineering (ISE))ORCID iD: 0000-0002-0862-1333
Peltarion AB.
2022 (English)In: Computer Sciences and Mathematics Forum, MDPI AG , 2022, Vol. 3Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
MDPI AG , 2022. Vol. 3
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Engineering and Technology
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URN: urn:nbn:se:kth:diva-312474DOI: 10.3390/cmsf2022003003OAI: oai:DiVA.org:kth-312474DiVA, id: diva2:1659113
Conference
AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD)
Note

QC 20220601

Available from: 2022-05-19 Created: 2022-05-19 Last updated: 2023-12-05Bibliographically approved

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Katsarou, StylianiRodríguez Gálvez, Borja

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