An estimated 100,000 people work today as commercial content moderators. These
moderators are often exposed to disturbing content, which can lead to lasting psychological …

We introduce Llama Guard, an LLM-based input-output safeguard model geared towards
Human-AI conversation use cases. Our model incorporates a safety risk taxonomy, a …

Background: With digital transformation and growing social media usage, kids spend
considerable time on the web, especially watching videos on YouTube. YouTube is a source …

Given the increasing promise of graph neural networks (GNNs) in real-world applications,
several methods have been developed for explaining their predictions. Existing methods for …

Recommender systems are the algorithms which select, filter, and personalize content
across many of the world's largest platforms and apps. As such, their positive and negative …

The automatic identification of harmful content online is of major concern for social media
platforms, policymakers, and society. Researchers have studied textual, visual, and audio …

Popular messaging applications now enable end-to-end-encryption (E2EE) by default, and
E2EE data storage is becoming common. These important advances for security and privacy …

Hateful and abusive speech presents a major challenge for all online social media
platforms. Recent advances in Natural Language Processing and Natural Language …

Content moderation systems are crucial in Online Social Networks (OSNs). Indeed, their role
is to keep platforms and their users safe from malicious activities. However, there is an …

Polarization is implicated in the erosion of democracy and the progression to violence,
which makes the polarization properties of large algorithmic content selection systems …