AI RESEARCH
When Hate Meets Facts: LLMs-in-the-Loop for Check-worthiness Detection in Hate Speech
arXiv CS.CL
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ArXi:2603.25269v1 Announce Type: new Hateful content online is often expressed using fact-like, not necessarily correct information, especially in coordinated online harassment campaigns and extremist propaganda. Failing to jointly address hate speech (HS) and misinformation can deepen prejudice, reinforce harmful stereotypes, and expose bystanders to psychological distress, while polluting public debate. Moreover, these messages require effort from content moderators because they must assess both harmfulness and veracity, i.e., fact-check them.