no code implementations • 1 Mar 2024 • Yuqi Chen, Sixuan Li, Ying Li, Mohammad Atari
In this work, we develop a pipeline for historical-psychological text analysis in classical Chinese.
no code implementations • 11 Oct 2022 • Ali Omrani, Brendan Kennedy, Mohammad Atari, Morteza Dehghani
Existing word embedding debiasing methods require social-group-specific word pairs (e. g., "man"-"woman") for each social attribute (e. g., gender), which cannot be used to mitigate bias for other social groups, making these methods impractical or costly to incorporate understudied social groups in debiasing.
no code implementations • 28 Oct 2021 • Aida Mostafazadeh Davani, Mohammad Atari, Brendan Kennedy, Morteza Dehghani
Social stereotypes negatively impact individuals' judgements about different groups and may have a critical role in how people understand language directed toward minority social groups.
no code implementations • ACL (WOAH) 2021 • Aida Mostafazadeh Davani, Ali Omrani, Brendan Kennedy, Mohammad Atari, Xiang Ren, Morteza Dehghani
By applying logit pairing to equalize outcomes on the restricted set of counterfactuals for each instance, we improve fairness metrics while preserving model performance on hate speech detection.
no code implementations • 24 Oct 2020 • Aida Mostafazadeh Davani, Ali Omrani, Brendan Kennedy, Mohammad Atari, Xiang Ren, Morteza Dehghani
Counterfactual token fairness for a mentioned social group evaluates the model's predictions as to whether they are the same for (a) the actual sentence and (b) a counterfactual instance, which is generated by changing the mentioned social group in the sentence.
1 code implementation • IJCNLP 2019 • Aida Mostafazadeh Davani, Leigh Yeh, Mohammad Atari, Brendan Kennedy, Gwenyth Portillo-Wightman, Elaine Gonzalez, Natalie Delong, Rhea Bhatia, Arineh Mirinjian, Xiang Ren, Morteza Dehghani
Official reports of hate crimes in the US are under-reported relative to the actual number of such incidents.