6 citations · 12 across the 3 of their papers we have counts for
3 papers
Socially Responsible Data for Large Multilingual Language Models
Andrew Smart, Ben Hutchinson, Lameck Mbangula Amugongo +12
Large Language Models (LLMs) have rapidly increased in size and apparent capabilities in the last three years, but their training data is largely English text. There is growing int…
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,…
Assessing LLMs for Moral Value Pluralism
Noam Benkler, Drisana Mosaphir, Scott Friedman +2
The fields of AI current lacks methods to quantitatively assess and potentially alter the moral values inherent in the output of large language models (LLMs). However, decades of s…