3 papers
cs.CL2026
Argument Quality Assessment with Large Language Models: A Pairwise Bradley-Terry Approach
Nicolás BenjamÃn Ocampo, Agnes Paullate Nyiranziza, Davide Ceolin
Large Language Models (LLMs) have demonstrated remarkable capabilities in tasks related to reasoning and judgment. However, assessing the quality of arguments requires a rigorous e…
cs.CL2026
Leveraging Argument Structure to Predict Content Hatefulness
Nicolás BenjamÃn Ocampo, Davide Ceolin
Information disorder is a challenging phenomenon that affects society at large. This phenomenon entails the diffusion of misleading, misinforming, and hateful content online. In di…
cs.CL2026
When Hate Meets Facts: LLMs-in-the-Loop for Check-worthiness Detection in Hate Speech
Nicolás BenjamÃn Ocampo, Tommaso Caselli, Davide Ceolin
Hateful content online is often expressed using fact-like, not necessarily correct information, especially in coordinated online harassment campaigns and extremist propaganda. Fail…