Work

Your fairness may vary: Group fairness of pretrained language models in toxic text classification.

Year: 2021

Type: preprint

Abstract: We study the performance-fairness trade-off in more than a dozen fine-tuned LMs for toxic text classification. We empirically show that no blanket statement can be made with respect to the bias of large versus regular versus compressed models. Moreover, we find that focusing on fairness-agnostic performance metrics can lead to models with varied fairness characteristics.

Source: arXiv (Cornell University)

Authors: Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Reduced inequalities

Open Access status: green

OpenAlex ID: W3190655802

Cites: 20

Cited by: 1

Related to: 10