1 citations · 1 across the 2 of their papers we have counts for
3 papers
Who Do Perspectivist Models Predict Well? Annotator Agreement, Sparsity, and Performance
London Lowmanstone, Vaagishwaran Sivakumar, Anwesha Samaddar +3
Successful completion of perspectivist natural language processing (NLP) annotation tasks requires algorithms to be aligned across diverse perspectives in order to predict how diff…
Annotation Imputation to Individualize Predictions: Initial Studies on Distribution Dynamics and Model Predictions
London Lowmanstone, Ruyuan Wan, Risako Owan +2
Annotating data via crowdsourcing is time-consuming and expensive. Due to these costs, dataset creators often have each annotator label only a small subset of the data. This leads…
SIERRA: A Modular Framework for Research Automation
John Harwell, London Lowmanstone, Maria Gini
Modern intelligent systems researchers employ the scientific method: they form hypotheses about system behavior, and then run experiments using one or more independent variables to…