2 citations · 4 across the 14 of their papers we have counts for
3 papers · 1 filter
Are you sure? Measuring models bias in content moderation through uncertainty
Alessandra Urbinati, Mirko Lai, Simona Frenda +1
Automatic content moderation is crucial to ensuring safety in social media. Language Model-based classifiers are being increasingly adopted for this task, but it has been shown tha…
What Are They Filtering Out? An Experimental Benchmark of Filtering Strategies for Harm Reduction in Pretraining Datasets
Marco Antonio Stranisci, Christian Hardmeier
Data filtering strategies are a crucial component to develop safe Large Language Models (LLM), since they support the removal of harmful contents from pretraining datasets. There i…
That is Unacceptable: the Moral Foundations of Canceling
Soda Marem Lo, Oscar Araque, Rajesh Sharma +1
Canceling is a morally-driven phenomenon that hinders the development of safe social media platforms and contributes to ideological polarization. To address this issue we present t…