3 citations · 6 across the 5 of their papers we have counts for
6 papers
Cost-Efficient Subjective Task Annotation and Modeling through Few-Shot Annotator Adaptation
Preni Golazizian, Alireza S. Ziabari, Ali Omrani +1
In subjective NLP tasks, where a single ground truth does not exist, the inclusion of diverse annotators becomes crucial as their unique perspectives significantly influence the an…
Towards a Unified Framework for Adaptable Problematic Content Detection via Continual Learning
Ali Omrani, Alireza S. Ziabari, Preni Golazizian +2
Detecting problematic content, such as hate speech, is a multifaceted and ever-changing task, influenced by social dynamics, user populations, diversity of sources, and evolving la…
Social-Group-Agnostic Word Embedding Debiasing via the Stereotype Content Model
Ali Omrani, Brendan Kennedy, Mohammad Atari +1
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…
The Moral Foundations Reddit Corpus
Jackson Trager, Alireza S. Ziabari, Elnaz Rahmati +15
Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational…
Improving Counterfactual Generation for Fair Hate Speech Detection
Aida Mostafazadeh Davani, Ali Omrani, Brendan Kennedy +3
Bias mitigation approaches reduce models' dependence on sensitive features of data, such as social group tokens (SGTs), resulting in equal predictions across the sensitive features…
Fair Hate Speech Detection through Evaluation of Social Group Counterfactuals
Aida Mostafazadeh Davani, Ali Omrani, Brendan Kennedy +3
Approaches for mitigating bias in supervised models are designed to reduce models' dependence on specific sensitive features of the input data, e.g., mentioned social groups. Howev…