58 citations · 65 across the 9 of their papers we have counts for
4 papers · 1 filter
Leveraging Argument Structure to Predict Content Hatefulness
Nicolás Benjamín 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…
Argument Quality Assessment with Large Language Models: A Pairwise Bradley-Terry Approach
Nicolás Benjamín 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…
When Hate Meets Facts: LLMs-in-the-Loop for Check-worthiness Detection in Hate Speech
Nicolás Benjamín 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…
Toward Reasonable Parrots: Why Large Language Models Should Argue with Us by Design
Elena Musi, Nadin Kokciyan, Khalid Al-Khatib +10
In this position paper, we advocate for the development of conversational technology that is inherently designed to support and facilitate argumentative processes. We argue that, a…