588 citations · 788 across the 7 of their papers we have counts for
7 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…
CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis
Shifu Yan, Caihua Shan, Wenyi Yang +5
In large-scale online services, crucial metrics, a.k.a., key performance indicators (KPIs), are monitored periodically to check their running statuses. Generally, KPIs are aggregat…
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…
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Defu Cao, Yujing Wang, Juanyong Duan +8
Multivariate time-series forecasting plays a crucial role in many real-world applications. It is a challenging problem as one needs to consider both intra-series temporal correlati…
Multivariate Time-series Anomaly Detection via Graph Attention Network
Hang Zhao, Yujing Wang, Juanyong Duan +7
Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications. Recent approaches have achieved significant progress…
Automated Model Selection for Time-Series Anomaly Detection
Yuanxiang Ying, Juanyong Duan, Chunlei Wang +3
Time-series anomaly detection is a popular topic in both academia and industrial fields. Many companies need to monitor thousands of temporal signals for their applications and ser…
Time-Series Anomaly Detection Service at Microsoft
Hansheng Ren, Bixiong Xu, Yujing Wang +7
Large companies need to monitor various metrics (for example, Page Views and Revenue) of their applications and services in real time. At Microsoft, we develop a time-series anomal…