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cs.HC2024
OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning
Jiaqi Ma, Vivian Lai, Yiming Zhang +5
Recently, there has been a surge of explainable AI (XAI) methods driven by the need for understanding machine learning model behaviors in high-stakes scenarios. However, properly e…
cs.HC2023
Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts
Tessa Han, Yasha Ektefaie, Maha Farhat +2
Post hoc explanations have emerged as a way to improve user trust in machine learning models by providing insight into model decision-making. However, explanations tend to be evalu…