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 whether and how using different architectures of probing models affects the performance of Italian transformers in encoding a wide spectrum of linguistic features. Moreover, we explore how this implicit knowledge varies according to different textual genres.

Italian Transformers Under the Linguistic Lens

Miaschi;Alessio;Brunato;Dominique;Dell'Orletta;Felice;Venturi;Giulia
2020

Abstract

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 whether and how using different architectures of probing models affects the performance of Italian transformers in encoding a wide spectrum of linguistic features. Moreover, we explore how this implicit knowledge varies according to different textual genres.
2020
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
979-12-80136-28-2
nlp
neural language models
interpretability
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/421765
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