3 papers
cs.CY2026
Fine-tuning LLMs for Tourist Trajectory Prediction using Field Experiment Data
Tatsuya Amano, Hirozumi Yamaguchi
Evaluating mobility interventions at tourist destinations requires predicting visitor behavior under varying conditions. Traditional methods struggle because tourist decisions depe…
cs.MA2026
Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation
Chiharu Shima, Haruki Yonekura, Fukuharu Tanaka +2
We propose a framework for predicting the effects of mobility introduction measures using a human-flow digital twin. This digital twin incorporates a multi-agent simulator that can…
cs.LG2025
MobText-SISA: Efficient Machine Unlearning for Mobility Logs with Spatio-Temporal and Natural-Language Data
Haruki Yonekura, Ren Ozeki, Tatsuya Amano +2
Modern mobility platforms have stored vast streams of GPS trajectories, temporal metadata, free-form textual notes, and other unstructured data. Privacy statutes such as the GDPR r…