Llama-Mob: Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility Prediction

Understand

Human mobility prediction plays a critical role in applications such as disaster response, urban planning, and epidemic forecasting.

• Traditional methods often rely on designing crafted, domain-specific models, and typically focus on short-term predictions, which struggle to generalize across diverse urban environments.
• In this study, we introduce Llama3-8B-Mob, a large language model fine-tuned with instruction tuning, for long-term citywide mobility prediction--in a Q&A manner.
• We validate our approach using large-scale human mobility data from four metropolitan areas in Japan, focusing on predicting individual trajectories over the next 15 days.