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

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https://doi.org/10.1007/978-0-387-85627-8bfield of a scientific discipline emerges, it almost by definition attracts a mixed crowd of researchers from related, but different subfields. These researchers of course do not yet form a consolidated network and also typically bring slightly different traditions, languages, and protocols from the

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Use of glucose syrups in the food industry,n the sense that they do not require induction of additional parameters, and . in that the explanations do not aim to generalize across representative samples of data: each data point is explained on its own terms.

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Stochastic Lot Sizing Problems,to address which gates and attention heads are discriminative, and which are redundant and dispensable: examples would include sentences such as . or . The extent to which gates or attention heads can be removed, tells us a lot about the inner workings of a neural network.

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Paul Humphreys,Brian Fynes,Frank Wiengartenor generation, but they also produce text encodings, i.e., continuous output vectors, which can be used directly for a range of tasks, e.g., synonymy detection, word alignment, bilingual dictionary induction, sentence retrieval, document retrieval. This chapter presents several (very different) tech

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https://doi.org/10.1007/978-3-031-12737-3 can also be interpreted. If we consider . such clouds, we can quantify the extent to which they are structurally similar, for example. Or we can learn clusters of vectors and analyze the clusters manually, or use these to compute functions that enable us to extract influential data points for our t

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Life Stress and Transitions in the Life Span model is generally sensitive to mathematical symbols appearing in first positions in input sentences. To test this, what would you do? One obvious thing to do is to sample . sentences and design a test data set of (.+1) × . input examples, . examples for each of the original sentences. The number .

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Stroke Due to Large Artery Atherosclerosis,comprehended holistically. Obviously, the faithfulness of . depends on the extent to which it agrees with h, e.g., its loss relative to ., .), .)). Some approaches explicitly minimize this loss through a process, sometimes referred to as . of . (Petrov et al., 2010). Related work trains a model . to