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
Distilling Aggregate Mobility Statistics into a Language Model Policy for Post-Event Crowd Simulation
Tatsuya Amano, Hirozumi Yamaguchi
Pedestrian simulators need a behaviour rule for every agent, but privacy usually limits the data for setting one to aggregate statistics, namely zone-level device counts and origin…
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…