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There is abundant evidence of the fact that the way words change their meaning can be classified in different types of change, …

Modern language models are capable of contextualizing words based on their surrounding context. However, this capability is often …

While minimising false negatives in hate speech classification remains an important goal in order to reduce discrimination and increase …

This study addresses the critical issue of Natural Language Processing in low-resource languages such as Hindi, which, despite having …

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 …