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Text analysis has undergone substantial evolution since its inception, moving from manual qualitative assessments to sophisticated …

Contextualized embeddings are the preferred tool for modeling Lexical Semantic Change (LSC). Current evaluations typically focus on a …

In the universe of Natural Language Processing, Transformer-based language models like BERT and (Chat)GPT have emerged as lexical …

Recent studies suggested that language models are efficient tools for measuring lexical semantic change. In our paper, we present the …

We present the DURel tool that implements the annotation of semantic proximity between uses of words into an online, open source …

The study of semantic shifts, that is, of how words change meaning as a consequence of social practices, events and political …

The recent introduction of large-scale datasets for the WiC (Word in Context) task enables the creation of more reliable and meaningful …

This thesis is concerned with the process of providing an evaluation for Lexical Semantic Change Detection, including (i) the …

Semantic Shift Detection (SSD) is the task of identifying, interpreting, and assessing the possible change over time in the meanings of …

In this chapter we provide an overview of computational modeling for semantic change using large and semi-large textual corpora. We aim …