3 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
Balancing Quality and Variation: Spam Filtering Distorts Data Label Distributions
Eve Fleisig, Matthias Orlikowski, Philipp Cimiano +1
For machine learning datasets to accurately represent diverse opinions in a population, they must preserve variation in data labels while filtering out spam or low-quality response…
Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discrimination
Eve Fleisig, Genevieve Smith, Madeline Bossi +3
We present a large-scale study of linguistic bias exhibited by ChatGPT covering ten dialects of English (Standard American English, Standard British English, and eight widely spoke…
Incorporating Worker Perspectives into MTurk Annotation Practices for NLP
Olivia Huang, Eve Fleisig, Dan Klein
Current practices regarding data collection for natural language processing on Amazon Mechanical Turk (MTurk) often rely on a combination of studies on data quality and heuristics…