4 papers · 1 filter
Beyond Dataset Creation: Critical View of Annotation Variation and Bias Probing of a Dataset for Online Radical Content Detection
Arij Riabi, Virginie Mouilleron, Menel Mahamdi +2
The proliferation of radical content on online platforms poses significant risks, including inciting violence and spreading extremist ideologies. Despite ongoing research, existing…
Common Ground, Diverse Roots: The Difficulty of Classifying Common Examples in Spanish Varieties
Javier A. Lopetegui, Arij Riabi, Djamé Seddah
Variations in languages across geographic regions or cultures are crucial to address to avoid biases in NLP systems designed for culturally sensitive tasks, such as hate speech det…
CamemBERT 2.0: A Smarter French Language Model Aged to Perfection
Wissam Antoun, Francis Kulumba, Rian Touchent +3
French language models, such as CamemBERT, have been widely adopted across industries for natural language processing (NLP) tasks, with models like CamemBERT seeing over 4 million…
Cloaked Classifiers: Pseudonymization Strategies on Sensitive Classification Tasks
Arij Riabi, Menel Mahamdi, Virginie Mouilleron +1
Protecting privacy is essential when sharing data, particularly in the case of an online radicalization dataset that may contain personal information. In this paper, we explore the…