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Autor:
Huang, Qi, Mezzi, Emanuele, Mutlu, Osman, Kofinas, Miltiadis, Prasad, Vidya, Khan, Shadnan Azwad, Ranguelova, Elena, van Stein, Niki
We introduce a novel metric for measuring semantic continuity in Explainable AI methods and machine learning models. We posit that for models to be truly interpretable and trustworthy, similar inputs should yield similar explanations, reflecting a co
Externí odkaz:
http://arxiv.org/abs/2407.12950