Probing Linguistic Knowledge in Italian Neural Language Models across Language Varieties

In this paper, we present an in-depth investigation of the linguistic knowledge encoded by the transformer models currently available for the Italian language. In particular, we investigate how the complexity of two different architectures of probing models affects the performance of the Transformer...

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Bibliographic Details
Main Authors: Alessio Miaschi, Gabriele Sarti, Dominique Brunato, Felice Dell’Orletta, Giulia Venturi
Format: Article
Language:English
Published: Accademia University Press 2022-07-01
Series:IJCoL
Online Access:http://journals.openedition.org/ijcol/965
Description
Summary:In this paper, we present an in-depth investigation of the linguistic knowledge encoded by the transformer models currently available for the Italian language. In particular, we investigate how the complexity of two different architectures of probing models affects the performance of the Transformers in encoding a wide spectrum of linguistic features. Moreover, we explore how this implicit knowledge varies according to different textual genres and language varieties.
ISSN:2499-4553