2 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
Reliable but Design-Sensitive: Instrument Uncertainty in LLM Annotation
Thomas Reiter, Christoph Kern, Fedor Miasnikov +4
Large language models (LLMs) can give reliable labels under one setup yet change those labels when researchers make other reasonable design choices. We tested seven LLMs, 12 task d…
From Ground Truth to Measurement: A Statistical Framework for Human Labeling
Robert Chew, Stephanie Eckman, Christoph Kern +1
Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human labeling introduces systematic…
Dialect and Gender Bias in YouTube's Spanish Captioning System
Iris Dania Jimenez, Christoph Kern
Spanish is the official language of twenty-one countries and is spoken by over 441 million people. Naturally, there are many variations in how Spanish is spoken across these countr…