Explaining short text classification with diverse synthetic exemplars and counter-exemplars
Journal: Machine Learning
Year: 2022

Abstract We present xspells , a model-agnostic local approach for explaining the decisions of black box models in classification of short texts. The explanations provided consist of a set of exemplar sentences and a set of counter-exemplar sentences. The former are examples classified by the black box with the same label as the text to explain. The latter are examples classified with a different label (a form of counter-factuals). Both are close in meaning to the text to explain, and both are me