273 citations · 332 across the 5 of their papers we have counts for
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cs.CV2022★ 4 cited
Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness
Caner Hazirbas, Yejin Bang, Tiezheng Yu +9
Developing robust and fair AI systems require datasets with comprehensive set of labels that can help ensure the validity and legitimacy of relevant measurements. Recent efforts, t…
cs.LG2022★ 1 cited
Adaptive Sampling Strategies to Construct Equitable Training Datasets
William Cai, Ro Encarnacion, Bobbie Chern +4
In domains ranging from computer vision to natural language processing, machine learning models have been shown to exhibit stark disparities, often performing worse for members of…