25 citations · 55 across the 12 of their papers we have counts for
5 papers · 1 filter
Biased Attention: Do Vision Transformers Amplify Gender Bias More than Convolutional Neural Networks?
Abhishek Mandal, Susan Leavy, Suzanne Little
Deep neural networks used in computer vision have been shown to exhibit many social biases such as gender bias. Vision Transformers (ViTs) have become increasingly popular in compu…
Gender Bias in Multimodal Models: A Transnational Feminist Approach Considering Geographical Region and Culture
Abhishek Mandal, Suzanne Little, Susan Leavy
Deep learning based visual-linguistic multimodal models such as Contrastive Language Image Pre-training (CLIP) have become increasingly popular recently and are used within text-to…
Industrial Memories: Exploring the Findings of Government Inquiries with Neural Word Embedding and Machine Learning
Susan Leavy, Emilie Pine, Mark T Keane
We present a text mining system to support the exploration of large volumes of text detailing the findings of government inquiries. Despite their historical significance and potent…
Curatr: A Platform for Semantic Analysis and Curation of Historical Literary Texts
Susan Leavy, Gerardine Meaney, Karen Wade +1
The increasing availability of digital collections of historical and contemporary literature presents a wealth of possibilities for new research in the humanities. The scale and di…
Multimodal Composite Association Score: Measuring Gender Bias in Generative Multimodal Models
Abhishek Mandal, Susan Leavy, Suzanne Little
Generative multimodal models based on diffusion models have seen tremendous growth and advances in recent years. Models such as DALL-E and Stable Diffusion have become increasingly…