The outstanding performance recently reached by neural language models (NLMs) across many natural language processing (NLP) tasks has steered the debate towards understanding whether NLMs implicitly learn linguistic competence. Probes, i.e., …
In this paper, we propose a comprehensive linguistic study aimed at assessing the implicit behaviour of one of the most prominent Neural Language Model (NLM) based on Transformer architectures, BERT (Devlin et al., 2019), when dealing with a …
In this paper, we propose an extensive evaluation of the first text-to-text Italian Neural Language Model (NLM), IT5, on a classification scenario. In particular, we test the performance of IT5 on several tasks involving both the classification of …
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 …
In this paper, we propose an evaluation of a Transformer-based punctuation restoration model for the Italian language. Experimenting with a BERT-base model, we perform several fine-tuning with different training data and sizes and tested them in an …
In the last few years, the analysis of the inner workings of state-of-the-art Neural Language Models (NLMs) has become one of the most addressed line of research in Natural Language Processing (NLP). Several techniques have been devised to obtain …
In this paper we present a new evaluation resource for Italian aimed at assessing the role of textual connectives in the comprehension of the meaning of a sentence. The resource is arranged in two sections (acceptability assessment and cloze test), …
Probing tasks are frequently used to evaluate whether the representations of Neural Language Models (NLMs) encode linguistic information. However, it is still questioned if probing classification tasks really enable such investigation or they simply …
In this paper, we propose an evaluation of a Transformer-based punctuation restoration model for the Italian language. Experimenting with a BERT-base model, we perform several fine-tuning with different training data and sizes and tested them in an …
Several studies investigated the linguistic information implicitly encoded in Neural Language Models. Most of these works focused on quantifying the amount and type of information available within their internal representations and across their …