2 citations · 2 across the 5 of their papers we have counts for
6 papers
Stochastic Voronoi Ensembles for Anomaly Detection
Yang Cao, Sikun Yang, Xuyun Zhang +1
Anomaly detection aims to identify data instances that deviate significantly from majority of data, which has been widely used in fraud detection, network security, and industrial…
Towards Token-Level Text Anomaly Detection
Yang Cao, Bicheng Yu, Sikun Yang +2
Despite significant progress in text anomaly detection for web applications such as spam filtering and fake news detection, existing methods are fundamentally limited to document-l…
Kernel Representation and Similarity Measure for Incomplete Data
Yang Cao, Sikun Yang, Kai He +4
Measuring similarity between incomplete data is a fundamental challenge in web mining, recommendation systems, and user behavior analysis. Traditional approaches either discard inc…
Isolation-based Spherical Ensemble Representations for Tabular Anomaly Detection
Yang Cao, Sikun Yang, Hao Tian +5
Unsupervised tabular anomaly detection is a critical task with applications spanning offensive language detection, network security, and quality control. Despite extensive research…
Text Anomaly Detection with Simplified Isolation Kernel
Yang Cao, Sikun Yang, Yujiu Yang +2
Two-step approaches combining pre-trained large language model embeddings and anomaly detectors demonstrate strong performance in text anomaly detection by leveraging rich semantic…
TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection
Yang Cao, Sikun Yang, Chen Li +5
Text anomaly detection is crucial for identifying spam, misinformation, and offensive language in natural language processing tasks. Despite the growing adoption of embedding-based…