activity
20202026
most citedRevisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation

26 citations · 39 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CV2026

Localization-Guided Foreground Augmentation in Autonomous Driving

Jiawei Yong, Deyuan Qu, Qi Chen +2

Autonomous driving systems often degrade under adverse visibility conditions-such as rain, nighttime, or snow-where online scene geometry (e.g., lane dividers, road boundaries, and…

cs.LG2026

TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer

Jiawei Wang, Chuang Yang, Jiawei Yong +6

Mobility trajectories are essential for understanding urban dynamics and enhancing urban planning, yet access to such data is frequently hindered by privacy concerns. This research…

cs.LG2025

Towards Resilient Transportation: A Conditional Transformer for Accident-Informed Traffic Forecasting

Hongjun Wang, Jiawei Yong, Jiawei Wang +2

Traffic prediction remains a key challenge in spatio-temporal data mining, despite progress in deep learning. Accurate forecasting is hindered by the complex influence of external…

cs.LG2025

How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learning

Haotian Gao, Zheng Dong, Jiawei Yong +3

Spatio-temporal forecasting is essential for real-world applications such as traffic management and urban computing. Although recent methods have shown improved accuracy, they ofte…

cs.LG2024

Graph Community Augmentation with GMM-based Modeling in Latent Space

Shintaro Fukushima, Kenji Yamanishi

This study addresses the issue of graph generation with generative models. In particular, we are concerned with graph community augmentation problem, which refers to the problem of…

cs.IR2024

Multimodal Point-of-Interest Recommendation

Yuta Kanzawa, Toyotaro Suzumura, Hiroki Kanezashi +2

Large Language Models are applied to recommendation tasks such as items to buy and news articles to read. Point of Interest is quite a new area to sequential recommendation based o…