3 papers
cs.IR2026
LLM-Enhanced Topical Trend Detection at Snapchat
Hangqi Zhao, Jay Li, Abhiruchi Bhattacharya +6
Automatic detection of topical trends at scale is both challenging and essential for maintaining a dynamic content ecosystem on social media platforms. In this work, we present a l…
cs.CL2025
ToxiCraft: A Novel Framework for Synthetic Generation of Harmful Information
Zheng Hui, Zhaoxiao Guo, Hang Zhao +2
In different NLP tasks, detecting harmful content is crucial for online environments, especially with the growing influence of social media. However, previous research has two main…
cs.CL2025
ToxiLab: How Well Do Open-Source LLMs Generate Synthetic Toxicity Data?
Zheng Hui, Zhaoxiao Guo, Hang Zhao +5
Effective toxic content detection relies heavily on high-quality and diverse data, which serve as the foundation for robust content moderation models. Synthetic data has become a c…