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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| Publicado en: | URI:https://journals.openedition.org/ijcol, |
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| Autores principales: | , , |
| Formato: | Article ou chapitre numérique |
| Lenguaje: | Anglais |
| Publicado: |
IJCoL
2020
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| Acceso en línea: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |