41 citations · 44 across the 7 of their papers we have counts for
7 papers
SemPOI-RL: Aligning LLM Semantic Reasoning for Interpretable Out-of-Town POI Sequential Generation
Yunqi Liu, Yang Zhang, Ruixing Zhang +4
Large language models (LLMs) exhibit strong semantic reasoning and open-ended generation abilities, but aligning these abilities with structured sequential generation remains chall…
Intent Speaks Louder: Controllable User Simulation Beyond Response Imitation
Bo Wang, Ruixing Zhang, Yunqi Liu +4
User simulators are widely used as scalable environments for training and evaluating interactive assistants. Generating the next user turn is inherently one-to-many: the same profi…
Think over Trajectories: Leveraging Video Generation to Reconstruct GPS Trajectories from Cellular Signaling
Ruixing Zhang, Hanzhang Jiang, Leilei Sun +3
Mobile devices continuously interact with cellular base stations, generating massive volumes of signaling records that provide broad coverage for understanding human mobility. Howe…
JiuTian Chuanliu: A Large Spatiotemporal Model for General-purpose Dynamic Urban Sensing
Liangzhe Han, Leilei Sun, Tongyu Zhu +3
As a window for urban sensing, human mobility contains rich spatiotemporal information that reflects both residents' behavior preferences and the functions of urban areas. The anal…
Regions are Who Walk Them: a Large Pre-trained Spatiotemporal Model Based on Human Mobility for Ubiquitous Urban Sensing
Ruixing Zhang, Liangzhe Han, Leilei Sun +3
User profiling and region analysis are two tasks of significant commercial value. However, in practical applications, modeling different features typically involves four main steps…
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
Liangzhe Han, Xiaojian Ma, Leilei Sun +4
Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society. Among them, the pairwise Origin-Destination (OD) demand…
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
Ruixing Zhang, Liangzhe Han, Boyi Liu +2
Recent years have witnessed a rapid growth of applying deep spatiotemporal methods in traffic forecasting. However, the prediction of origin-destination (OD) demands is still a cha…