5 papers
EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain
Yi-Fan Lu, Xian-Ling Mao, Bo Wang +2
It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, finance, and biology. However, event e…
VETime: Vision Enhanced Zero-Shot Time Series Anomaly Detection
Yingyuan Yang, Tian Lan, Yifei Gao +5
Time-series anomaly detection (TSAD) requires identifying both immediate Point Anomalies and long-range Context Anomalies. However, existing foundation models face a fundamental tr…
SEOE: A Scalable and Reliable Semantic Evaluation Framework for Open Domain Event Detection
Yi-Fan Lu, Xian-Ling Mao, Tian Lan +3
Automatic evaluation for Open Domain Event Detection (ODED) is a highly challenging task, because ODED is characterized by a vast diversity of un-constrained output labels from var…
CICADA: Cross-Domain Interpretable Coding for Anomaly Detection and Adaptation in Multivariate Time Series
Tian Lan, Yifei Gao, Yimeng Lu +1
Unsupervised Time series anomaly detection plays a crucial role in applications across industries. However, existing methods face significant challenges due to data distributional…
Beyond Exact Match: Semantically Reassessing Event Extraction by Large Language Models
Yi-Fan Lu, Xian-Ling Mao, Tian Lan +3
Event extraction has gained extensive research attention due to its broad range of applications. However, the current mainstream evaluation method for event extraction relies on to…