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Explainable Natural Language Processing [electronic resource] / by Anders Søgaard.

By: Søgaard, Anders [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Human Language Technologies: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2021Edition: 1st ed. 2021.Description: XV, 107 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031021800.Subject(s): Artificial intelligence | Natural language processing (Computer science) | Computational linguistics | Artificial Intelligence | Natural Language Processing (NLP) | Computational LinguisticsAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Acknowledgments -- Introduction -- A Framework for Explainable NLP -- Local-Backward Explanations -- Global-Backward Explanations -- Local-Forward Explanations of Intermediate Representations -- Global-Forward Explanations of Intermediate Representations -- Local-Forward Explanations of Continuous Output -- Global-Forward Explanations of Continuous Output -- Local-Forward Explanations of Discrete Output -- Global-Forward Explanations of Discrete Output -- Evaluating Explanations -- Perspectives -- Resources -- Bibliography -- Author's Biography .
In: Springer Nature eBookSummary: This book presents a taxonomy framework and survey of methods relevant to explaining the decisions and analyzing the inner workings of Natural Language Processing (NLP) models. The book is intended to provide a snapshot of Explainable NLP, though the field continues to rapidly grow. The book is intended to be both readable by first-year M.Sc. students and interesting to an expert audience. The book opens by motivating a focus on providing a consistent taxonomy, pointing out inconsistencies and redundancies in previous taxonomies. It goes on to present (i) a taxonomy or framework for thinking about how approaches to explainable NLP relate to one another; (ii) brief surveys of each of the classes in the taxonomy, with a focus on methods that are relevant for NLP; and (iii) a discussion of the inherent limitations of some classes of methods, as well as how to best evaluate them. Finally, the book closes by providing a list of resources for further research on explainability.
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Acknowledgments -- Introduction -- A Framework for Explainable NLP -- Local-Backward Explanations -- Global-Backward Explanations -- Local-Forward Explanations of Intermediate Representations -- Global-Forward Explanations of Intermediate Representations -- Local-Forward Explanations of Continuous Output -- Global-Forward Explanations of Continuous Output -- Local-Forward Explanations of Discrete Output -- Global-Forward Explanations of Discrete Output -- Evaluating Explanations -- Perspectives -- Resources -- Bibliography -- Author's Biography .

This book presents a taxonomy framework and survey of methods relevant to explaining the decisions and analyzing the inner workings of Natural Language Processing (NLP) models. The book is intended to provide a snapshot of Explainable NLP, though the field continues to rapidly grow. The book is intended to be both readable by first-year M.Sc. students and interesting to an expert audience. The book opens by motivating a focus on providing a consistent taxonomy, pointing out inconsistencies and redundancies in previous taxonomies. It goes on to present (i) a taxonomy or framework for thinking about how approaches to explainable NLP relate to one another; (ii) brief surveys of each of the classes in the taxonomy, with a focus on methods that are relevant for NLP; and (iii) a discussion of the inherent limitations of some classes of methods, as well as how to best evaluate them. Finally, the book closes by providing a list of resources for further research on explainability.

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