7 papers
AdaKernel: Learning Adaptive Kernel Parameters for Spatiotemporal Graph Neural Networks
Zhongyue Zhang, Guangyin Jin, Yuxuan Liang +2
Modeling spatial dependencies is central to spatiotemporal data analysis using Graph Neural Networks (GNNs). Traditional methods rely on distance-based kernels with predefined para…
Discrete Prototypical Memories for Federated Time Series Foundation Models
Liwei Deng, Qingxiang Liu, Xinhe Niu +5
Leveraging Large Language Models (LLMs) as federated learning (FL)-based time series foundation models offers a promising way to transfer the generalization capabilities of LLMs to…
Aeolus: A Multi-structural Flight Delay Dataset
Lin Xu, Xinyun Yuan, Yuxuan Liang +2
We introduce Aeolus, a large-scale Multi-modal Flight Delay Dataset designed to advance research on flight delay prediction and support the development of foundation models for tab…
Reinforcement Learning for Hybrid Charging Stations Planning and Operation Considering Fixed and Mobile Chargers
Yanchen Zhu, Honghui Zou, Chufan Liu +3
The success of vehicle electrification relies on efficient and adaptable charging infrastructure. Fixed-location charging stations often suffer from underutilization or congestion…
GeoSR: Cognitive-Agentic Framework for Probing Geospatial Knowledge Boundaries via Iterative Self-Refinement
Jinfan Tang, Kunming Wu, Ruifeng Gongxie +2
Recent studies have extended the application of large language models (LLMs) to geographic problems, revealing surprising geospatial competence even without explicit spatial superv…
AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks
Qiongyan Wang, Yutong Xia, Siru ZHong +6
Monitoring real-time air quality is essential for safeguarding public health and fostering social progress. However, the widespread deployment of air quality monitoring stations is…