3 papers
cs.CR2026
When Youth Enter the Algorithmic Wild: Discovering and Understanding Potentially Harmful Teen Videos on Douyin and Kwai
Shaoxuan Zhou, Yafei Sun, Jing Zhang +1
Short-video platforms like Douyin and Kwai have become central to adolescent digital life, but they also risk exposing teens to algorithmically amplified harmful content. Despite i…
cs.CR2026
Seeing the Unseen: Rethinking Illicit Promotion Detection with In-Context Learning
Sangyi Wu, Junpu Guo, Xianghang Mi
Illicit online promotion is a persistent threat that evolves to evade detection. Existing moderation systems remain tethered to platform-specific supervision and static taxonomies,…
cs.CL2025
Beyond One-Size-Fits-All: Personalized Harmful Content Detection with In-Context Learning
Rufan Zhang, Lin Zhang, Xianghang Mi
The proliferation of harmful online content--e.g., toxicity, spam, and negative sentiment--demands robust and adaptable moderation systems. However, prevailing moderation systems a…