588 citations · 779 across the 10 of their papers we have counts for
10 papers
STAND-Guard: A Small Task-Adaptive Content Moderation Model
Minjia Wang, Pingping Lin, Siqi Cai +5
Content moderation, the process of reviewing and monitoring the safety of generated content, is important for development of welcoming online platforms and responsible large langua…
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…
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…
Protecting the Future: Neonatal Seizure Detection with Spatial-Temporal Modeling
Ziyue Li, Yuchen Fang, You Li +7
A timely detection of seizures for newborn infants with electroencephalogram (EEG) has been a common yet life-saving practice in the Neonatal Intensive Care Unit (NICU). However, i…
Label-Efficient Interactive Time-Series Anomaly Detection
Hong Guo, Yujing Wang, Jieyu Zhang +5
Time-series anomaly detection is an important task and has been widely applied in the industry. Since manual data annotation is expensive and inefficient, most applications adopt u…
TS2Vec: Towards Universal Representation of Time Series
Zhihan Yue, Yujing Wang, Juanyong Duan +4
This paper presents TS2Vec, a universal framework for learning representations of time series in an arbitrary semantic level. Unlike existing methods, TS2Vec performs contrastive l…