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Measuring and Mitigating Gender Bias in Legal Contextualized Language Models
16 references·0 citing·33 second hop
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References

  • 2019HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case16,511 cited
  • 1998Measuring individual differences in implicit cognition: The implicit association test.9,206 cited
  • 2017Semantics derived automatically from language corpora contain human-like biases2,845 cited
  • 2020LEGAL-BERT: The Muppets straight out of Law School1,065 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2016Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective812 cited
  • 2018AI can be sexist and racist — it’s time to make it fair764 cited
  • 2017A general approach for predicting the behavior of the Supreme Court of the United States530 cited
  • 2019On Measuring Social Biases in Sentence Encoders461 cited
  • 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems384 cited
  • 2020How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence377 cited
  • 2023Biases in Large Language Models: Origins, Inventory, and Discussion364 cited
  • 2019Neural Legal Judgment Prediction in English350 cited
  • 2019Measuring Bias in Contextualized Word Representations348 cited

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2019
Gender Bias in Contextualized Word Embeddings
334 cited
  • 2021WELFake: Word Embedding Over Linguistic Features for Fake News Detection315 cited
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