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Explaining Classes through Stable Word Attributions
Input saliency methods have recently become a popular tool for explaining predictions of deep learning models in NLP.
Explaining Classes through Word Attribution
In this work, we propose a method for explaining classes using deep learning models and the Integrated Gradients feature attribution technique by aggregating explanations of individual examples in text classification to general descriptions of the classes.
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