3 citations · 6 across the 5 of their papers we have counts for
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cs.AI2026
The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation
Sheza Munir, Benjamin Mah, Krisha Kalsi +5
In machine learning, "ground truth" refers to the assumed correct labels used to train and evaluate models. However, the foundational "ground truth" paradigm rests on a positivisti…
cs.AI2024★ 3 cited
Discipline and Label: A WEIRD Genealogy and Social Theory of Data Annotation
Andrew Smart, Ding Wang, Ellis Monk +4
Data annotation remains the sine qua non of machine learning and AI. Recent empirical work on data annotation has begun to highlight the importance of rater diversity for fairness,…