4 accepted papers
Misinformation is a global issue that shapes public discourse, influencing opinions and decision-making across various domains. While automated fact-checking (AFC) has become essential in combating misinformation, most work in multilingual settings has focused on claim verification rather than gener…
In this work we present a system for multilingual olfactory information extraction covering six European languages, introducing new models to extract olfactory information from large amounts of text in a structured and scalable way. For the task we rely on a supervised multi-task approach to detect…
Exploring and understanding language data is a fundamental stage in all areas dealing with human language. It allows NLP practitioners to uncover quality concerns and harmful biases in data before training, and helps linguists and social scientists to gain insight into language use and human behavio…
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media. While several approaches have been proposed to tackle the problem from an algorithmic perspective, so to reduce th…