Natural language inference (NLI) datasets are great resources to train and benchmark models that infer entailment relations. However, these datasets are known to have issues such as lexical biases that affect the behaviour ...

This thesis explores the concept of detecting non-literal phrases using Large Language Models (LLM) such as GPT-4 and Gemini Pro, as well as Recurrent Neural Networks (RNN), LSTM and BiLSTM models in particular. Through ...

According to the World Health Organization, one in three women has been a victim of physical or sexual violence by their partner at some point in their lives. This indicates that Gender-Based Violence is a global public ...

Reporting bias (the human tendency to not mention obvious or redundant information) and social bias (societal attitudes toward specific demographic groups) have both been shown to propagate from human text data to language ...

This thesis explores the topic of using the GPT-4 large language model, to generate high-quality, diverse synthetic dialogue datasets for training Natural Language Understanding (NLU) models in task-oriented dialogue ...

The current thesis focuses on the application of neural machine translation (NMT) models translating from Ancient Greek to English. The rich morphology, syntax, and vocabulary of the Ancient Greek combined with its status ...

The scope of this thesis is on Lexical Semantic Change (LSC) and its automatic detection in the Polish language. Following Cassotti et al. (2023)’s findings, the following thesis leverages XL-Lexeme, a transformerbased ...