A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces

@article{Lauscher2020AGF,
  title={A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces},
  author={Anne Lauscher and Goran Glavas and Simone Paolo Ponzetto and Ivan Vulic},
  journal={ArXiv},
  year={2020},
  volume={abs/1909.06092}
}
  • Anne Lauscher, Goran Glavas, +1 author Ivan Vulic
  • Published 2020
  • Computer Science
  • ArXiv
  • Distributional word vectors have recently been shown to encode many of the human biases, most notably gender and racial biases, and models for attenuating such biases have consequently been proposed. [...] Key Method We then propose three debiasing models that operate on explicit or implicit bias specifications, and that can be composed towards more robust debiasing. Finally, we devise a full-fledged evaluation framework in which we couple existing bias metrics with newly proposed ones. Experimental findings…Expand Abstract
    9 Citations

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