17 citations · 48 across the 11 of their papers we have counts for
20 papers · 1 filter
Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains
Areg Mikael Sarvazyan, José Ángel González, Marc Franco-Salvador +3
This paper presents the overview of the AuTexTification shared task as part of the IberLEF 2023 Workshop in Iberian Languages Evaluation Forum, within the framework of the SEPLN 20…
Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection
Angel Felipe Magnossão de Paula, Paolo Rosso, Damiano Spina
This paper proposes a novelty approach to mitigate the negative transfer problem. In the field of machine learning, the common strategy is to apply the Single-Task Learning approac…
Transformers and Ensemble methods: A solution for Hate Speech Detection in Arabic languages
Angel Felipe Magnossão de Paula, Imene Bensalem, Paolo Rosso +1
This paper describes our participation in the shared task of hate speech detection, which is one of the subtasks of the CERIST NLP Challenge 2022. Our experiments evaluate the perf…
Fake News and Hate Speech: Language in Common
Berta Chulvi, Alejandro Toselli, Paolo Rosso
In this paper we raise the research question of whether fake news and hate speech spreaders share common patterns in language. We compute a novel index, the ingroup vs outgroup ind…
Unsupervised Ranking and Aggregation of Label Descriptions for Zero-Shot Classifiers
Angelo Basile, Marc Franco-Salvador, Paolo Rosso
Zero-shot text classifiers based on label descriptions embed an input text and a set of labels into the same space: measures such as cosine similarity can then be used to select th…
Detecting early signs of depression in the conversational domain: The role of transfer learning in low-resource scenarios
Petr Lorenc, Ana-Sabina Uban, Paolo Rosso +1
The high prevalence of depression in society has given rise to the need for new digital tools to assist in its early detection. To this end, existing research has mainly focused on…