2 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection
Wenbin Li, Di Yao, Chang Gong +6
Trajectory anomaly detection, aiming to estimate the anomaly risk of trajectories given the Source-Destination (SD) pairs, has become a critical problem for many real-world applica…
Effective and Efficient Representation Learning for Flight Trajectories
Shuo Liu, Wenbin Li, Di Yao +1
Flight trajectory data plays a vital role in the traffic management community, especially for downstream tasks such as trajectory prediction, flight recognition, and anomaly detect…
PORCA: Root Cause Analysis with Partially Observed Data
Chang Gong, Di Yao, Jin Wang +6
Root Cause Analysis (RCA) aims at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from complex systems. It has been widely used…
STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis
Wenbin Li, Di Yao, Ruibo Zhao +7
The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-tem…
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Shuo Liu, Di Yao, Lanting Fang +5
Detecting anomaly edges for dynamic graphs aims to identify edges significantly deviating from the normal pattern and can be applied in various domains, such as cybersecurity, fina…