Explainable Natural Language Processing
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Explainable Natural Language Processing. / Søgaard, Anders.
Morgan & Claypool, 2021. 123 p. (Synthesis Lectures on Human Language Technologies; No. 3, Vol. 14).Research output: Book/Report › Book › Research › peer-review
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TY - BOOK
T1 - Explainable Natural Language Processing
AU - Søgaard, Anders
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
U2 - 10.2200/S01118ED1V01Y202107HLT051)
DO - 10.2200/S01118ED1V01Y202107HLT051)
M3 - Book
T3 - Synthesis Lectures on Human Language Technologies
BT - Explainable Natural Language Processing
PB - Morgan & Claypool
ER -
ID: 299760182