16 citations · 29 across the 4 of their papers we have counts for
4 papers
Model-based Counterfactual Generator for Gender Bias Mitigation
Ewoenam Kwaku Tokpo, Toon Calders
Counterfactual Data Augmentation (CDA) has been one of the preferred techniques for mitigating gender bias in natural language models. CDA techniques have mostly employed word subs…
How Far Can It Go?: On Intrinsic Gender Bias Mitigation for Text Classification
Ewoenam Tokpo, Pieter Delobelle, Bettina Berendt +1
To mitigate gender bias in contextualized language models, different intrinsic mitigation strategies have been proposed, alongside many bias metrics. Considering that the end use o…
Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models
Pieter Delobelle, Ewoenam Kwaku Tokpo, Toon Calders +1
An increasing awareness of biased patterns in natural language processing resources, like BERT, has motivated many metrics to quantify `bias' and `fairness'. But comparing the resu…
Finding Robust Itemsets Under Subsampling
Nikolaj Tatti, Fabian Moerchen, Toon Calders
Mining frequent patterns is plagued by the problem of pattern explosion making pattern reduction techniques a key challenge in pattern mining. In this paper we propose a novel theo…