10 papers
RooseBERT: A New Deal For Political Language Modelling
Deborah Dore, Elena Cabrio, Serena Villata
The increasing amount of political debates and politics-related discussions calls for the definition of novel computational methods to automatically analyse such content with the f…
Compact Prompting in Instruction-tuned LLMs for Joint Argumentative Component Detection
Sofiane Elguendouze, Erwan Hain, Elena Cabrio +1
Argumentative component detection (ACD) is a core subtask of Argument(ation) Mining (AM) and one of its most challenging aspects, as it requires jointly delimiting argumentative sp…
PEACE 2.0: Grounded Explanations and Counter-Speech for Combating Hate Expressions
Greta Damo, Stéphane Petiot, Elena Cabrio +1
The increasing volume of hate speech on online platforms poses significant societal challenges. While the Natural Language Processing community has developed effective methods to a…
Merging Embedded Topics with Optimal Transport for Online Topic Modeling on Data Streams
Federica Granese, Benjamin Navet, Serena Villata +1
Topic modeling is a key component in unsupervised learning, employed to identify topics within a corpus of textual data. The rapid growth of social media generates an ever-growing…
Stick-Breaking Embedded Topic Model with Continuous Optimal Transport for Online Analysis of Document Streams
Federica Granese, Serena Villata, Charles Bouveyron
Online topic models are unsupervised algorithms to identify latent topics in data streams that continuously evolve over time. Although these methods naturally align with real-world…
Beating Harmful Stereotypes Through Facts: RAG-based Counter-speech Generation
Greta Damo, Elena Cabrio, Serena Villata
Counter-speech generation is at the core of many expert activities, such as fact-checking and hate speech, to counter harmful content. Yet, existing work treats counter-speech gene…