6 papers
TrajGenAgent: A Hierarchical LLM Agent for Human Mobility Trajectory Generation
Siyu Li, Toan Tran, Lingyi Zhao +2
Human mobility data is important for transportation, urban planning, and epidemic control, but large-scale trajectory collection is often costly and privacy-constrained, motivating…
NARA: Anchor-Conditioned Relation-Aware Contextualization of Heterogeneous Geoentities
Jina Kim, Gengchen Mai, Lingyi Zhao +2
Geospatial foundation models have primarily focused on raster data such as satellite imagery, where self-supervised learning has been widely studied. Vector geospatial data instead…
BeSTAD: Behavior-Aware Spatio-Temporal Anomaly Detection for Human Mobility Data
Junyi Xie, Jina Kim, Yao-Yi Chiang +2
Traditional anomaly detection in human mobility has primarily focused on trajectory-level analysis, identifying statistical outliers or spatiotemporal inconsistencies across aggreg…
HiCoTraj:Zero-Shot Demographic Reasoning via Hierarchical Chain-of-Thought Prompting from Trajectory
Junyi Xie, Yuankun Jiao, Jina Kim +3
Inferring demographic attributes such as age, sex, or income level from human mobility patterns enables critical applications such as targeted public health interventions, equitabl…
Geo-Llama: Leveraging LLMs for Human Mobility Trajectory Generation with Spatiotemporal Constraints
Siyu Li, Toan Tran, Haowen Lin +5
Generating realistic human mobility data is essential for various application domains, including transportation, urban planning, and epidemic control, as real data is often inacces…
Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Framework
Minxuan Duan, Yinlong Qian, Lingyi Zhao +4
Existing methods for anomaly detection often fall short due to their inability to handle the complexity, heterogeneity, and high dimensionality inherent in real-world mobility data…