5 citations · 9 across the 3 of their papers we have counts for
3 papers
Annotator in the Loop: A Case Study of In-Depth Rater Engagement to Create a Bridging Benchmark Dataset
Sonja Schmer-Galunder, Ruta Wheelock, Scott Friedman +3
With the growing prevalence of large language models, it is increasingly common to annotate datasets for machine learning using pools of crowd raters. However, these raters often w…
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,…
From Unstructured Text to Causal Knowledge Graphs: A Transformer-Based Approach
Scott Friedman, Ian Magnusson, Vasanth Sarathy +1
Qualitative causal relationships compactly express the direction, dependency, temporal constraints, and monotonicity constraints of discrete or continuous interactions in the world…