208 citations · 303 across the 5 of their papers we have counts for
6 papers
Mitigating Extrinsic Gender Bias for Bangla Classification Tasks
Sajib Kumar Saha Joy, Arman Hassan Mahy, Meherin Sultana +4
In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languages. To assess this bias, we construct…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
They, Them, Theirs: Rewriting with Gender-Neutral English
Tony Sun, Kellie Webster, Apu Shah +2
Responsible development of technology involves applications being inclusive of the diverse set of users they hope to support. An important part of this is understanding the many wa…
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation
Jwala Dhamala, Tony Sun, Varun Kumar +4
Recent advances in deep learning techniques have enabled machines to generate cohesive open-ended text when prompted with a sequence of words as context. While these models now emp…
Towards Understanding Gender Bias in Relation Extraction
Andrew Gaut, Tony Sun, Shirlyn Tang +8
Recent developments in Neural Relation Extraction (NRE) have made significant strides towards Automated Knowledge Base Construction (AKBC). While much attention has been dedicated…
Mitigating Gender Bias in Natural Language Processing: Literature Review
Tony Sun, Andrew Gaut, Shirlyn Tang +7
As Natural Language Processing (NLP) and Machine Learning (ML) tools rise in popularity, it becomes increasingly vital to recognize the role they play in shaping societal biases an…