110 citations · 260 across the 12 of their papers we have counts for
13 papers
SqLinear: Balanced Square Partitioning Makes Linear Interaction Sufficient for Large-Scale Traffic Forecasting
Yongfeng Su, Hongwen Li, Zijian Zhang +5
Traffic prediction is a core task in intelligent transportation systems and urban-scale decision making. Despite the effectiveness of mainstream neural network-based methods, their…
Beyond Relational: Semantic-Aware Multi-Modal Analytics with LLM-Native Query Optimization
Junhao Zhu, Lu Chen, Xiangyu Ke +4
Multi-modal analytical processing has the potential to transform applications in e-commerce, healthcare, entertainment, and beyond. However, real-world adoption remains elusive due…
Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detection
Yuanyuan Yao, Yuhan Shi, Lu Chen +5
Multivariate time series (MTS) anomaly detection identifies abnormal patterns where each timestamp contains multiple variables. Existing MTS anomaly detection methods fall into thr…
FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning
Zhihao Zeng, Ziquan Fang, Wei Shao +2
Trajectory data, which capture the movement patterns of people and vehicles over time and space, are crucial for applications like traffic optimization and urban planning. However,…
Causal Spatio-Temporal Prediction: An Effective and Efficient Multi-Modal Approach
Yuting Huang, Ziquan Fang, Zhihao Zeng +2
Spatio-temporal prediction plays a crucial role in intelligent transportation, weather forecasting, and urban planning. While integrating multi-modal data has shown potential for e…
Effective and Efficient Cross-City Traffic Knowledge Transfer: A Privacy-Preserving Perspective
Zhihao Zeng, Ziquan Fang, Yuting Huang +2
Traffic prediction aims to forecast future traffic conditions using historical traffic data, serving a crucial role in urban computing and transportation management. While transfer…