Titlebook: Explainable Natural Language Processing; Anders Søgaard Book 2021 Springer Nature Switzerland AG 2021

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Behavioral Pharmacology of Caffeine away from the models themselves. The same holds for the metrics we use to evaluate explanations. The metrics are, in other words, orthogonal to the taxonomy presented here. In this chapter, we therefore introduce a classification of explanations (not methods), distinguishing, for example, explanati

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978-3-031-01052-1Springer Nature Switzerland AG 2021

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Explainable Natural Language Processing978-3-031-02180-0Series ISSN 1947-4040 Series E-ISSN 1947-4059

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B. A. Tashmukhamedov,A. I. Gagel’ganshesis classes from which h(•) will be induced. Once we have been reminded about these standard architectures, we are in a position to introduce a simple, yet incredibly useful, framework for thinking about interpretability methods.

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A Framework for Explainable NLP,hesis classes from which h(•) will be induced. Once we have been reminded about these standard architectures, we are in a position to introduce a simple, yet incredibly useful, framework for thinking about interpretability methods.

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Global-Backward Explanations,questioned whether this correlation holds in general (Freitas, 2013), and it is important to remember that weight pruning strategies are often motivated by other concerns, including making inference faster, and storage and memory requirements smaller (Kim and Hassan, 2020).

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