no code implementations • 27 Nov 2023 • Liesbeth Allein, Maria Mihaela Truşcǎ, Marie-Francine Moens
The social and implicit nature of human communication ramifies readers' understandings of written sentences.
no code implementations • 1 Sep 2023 • RuiQi Li, Liesbeth Allein, Damien Sileo, Marie-Francine Moens
The capabilities and use cases of automatic natural language processing (NLP) have grown significantly over the last few years.
1 code implementation • 24 Feb 2023 • Liesbeth Allein, Marlon Saelens, Ruben Cartuyvels, Marie-Francine Moens
Our findings show that the presence of temporal information and the manner in which timelines are constructed greatly influence how fact-checking models determine the relevance and supporting or refuting character of evidence documents.
no code implementations • 31 Aug 2021 • Liesbeth Allein, Marie-Francine Moens, Domenico Perrotta
The latent representations of news articles and user-generated content allow that during training the model is guided by the profile of users who prefer content similar to the news article that is evaluated, and this effect is reinforced if that content is shared among different users.
no code implementations • 10 Sep 2020 • Liesbeth Allein, Isabelle Augenstein, Marie-Francine Moens
Truth can vary over time.
no code implementations • 20 Aug 2020 • Liesbeth Allein, Marie-Francine Moens
Public, professional and academic interest in automated fact-checking has drastically increased over the past decade, with many aiming to automate one of the first steps in a fact-check procedure: the selection of so-called checkworthy claims.
no code implementations • 9 Jan 2020 • Liesbeth Allein, Artuur Leeuwenberg, Marie-Francine Moens
Drawing on previous research conducted on neural context-dependent dt-mistake correction models (Heyman et al. 2018), this study constructs the first neural network model for Dutch demonstrative and relative pronoun resolution that specifically focuses on the correction and part-of-speech prediction of these two pronouns.