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On Bias and Fairness in NLP: Investigating the Impact of Bias and
  Debiasing in Language Models on the Fairness of Toxicity Detection

On Bias and Fairness in NLP: Investigating the Impact of Bias and Debiasing in Language Models on the Fairness of Toxicity Detection

22 May 2023
Fatma Elsafoury
Stamos Katsigiannis
ArXivPDFHTML

Papers citing "On Bias and Fairness in NLP: Investigating the Impact of Bias and Debiasing in Language Models on the Fairness of Toxicity Detection"

2 / 2 papers shown
Title
Quantifying Social Biases Using Templates is Unreliable
Quantifying Social Biases Using Templates is Unreliable
P. Seshadri
Pouya Pezeshkpour
Sameer Singh
49
33
0
09 Oct 2022
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based
  Bias in NLP
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP
Timo Schick
Sahana Udupa
Hinrich Schütze
257
374
0
28 Feb 2021
1