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Found 2 papers, 2 papers with code
Capturing Humans' Mental Models of AI: An Item Response Theory Approach
Improving our understanding of how humans perceive AI teammates is an important foundation for our general understanding of human-AI teams.
Variable-Based Calibration for Machine Learning Classifiers
In this paper we introduce the notion of variable-based calibration to characterize calibration properties of a model with respect to a variable of interest, generalizing traditional score-based metrics such as expected calibration error (ECE).
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