We present the first benchmark dataset for abusive language detection in Tigrinya, demonstrating how multi-task learning can address critical content moderation gaps in underserved languages.

We present an Intent Classification Dataset for Wolof language. We conduct experiments on various baselines, including text and voice state-of-the-art models.