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05/02/2023
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging
In this paper, we examine computational approaches for measuring the "fa...
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03/10/2023
Overcoming Bias in Pretrained Models by Manipulating the Finetuning Dataset
Transfer learning is beneficial by allowing the expressive features of m...
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06/18/2022
Gender Artifacts in Visual Datasets
Gender biases are known to exist within large-scale visual datasets and ...
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06/14/2022
Measuring Representational Harms in Image Captioning
Previous work has largely considered the fairness of image captioning sy...
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05/10/2022
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Research in machine learning fairness has historically considered a sing...
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06/16/2021
Understanding and Evaluating Racial Biases in Image Captioning
Image captioning is an important task for benchmarking visual reasoning ...
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02/24/2021
Directional Bias Amplification
Mitigating bias in machine learning systems requires refining our unders...
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02/02/2021
The Limits of Global Inclusion in AI Development
Those best-positioned to profit from the proliferation of artificial int...
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04/16/2020
ViBE: A Tool for Measuring and Mitigating Bias in Image Datasets
Machine learning models are known to perpetuate the biases present in th...
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05/11/2019
Learning Robotic Manipulation through Visual Planning and Acting
Planning for robotic manipulation requires reasoning about the changes a...
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11/22/2017