On the Readability of Kernel-based Deep Learning Models in Semantic Role Labeling Tasks over Multiple Languages

Sentence embeddings are effective input vectors for the neural learning of a number of inferences about content and meaning. Unfortunately, most of such decision processes are epistemologically opaque as for the limited interpretability of the acquired neural models based on the involved embeddings....

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Détails bibliographiques
Dans:URI:https://journals.openedition.org/ijcol,
Auteurs principaux: Rossini, Daniele, Croce, Danilo, Basili, Roberto
Format: Article ou chapitre numérique
Langue:Anglais
Publié: IJCoL 2020
Accès en ligne:Accès Université d'Orléans et IFPM
Accès Université d'Orléans et IFPM

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