Metamorphic Testing with the Rashomon Set: Explanation Faithfulness in Machine Learning 事件

Metamorphic Testing with the Rashomon Set: Explanation Faithfulness in Machine Learning arXiv:2606.06056v1 Announce Type: cross Abstract: Multiple machine learning models can achieve near-equivalent predictive performance on the same task, yet provide divergent feature-based explanations. This is called the Rashomon effect of (explainable) machine learning, and it raises the question of which explanations, if any, are trustworthy. We propose a framework based on metamorphic testing that assesse