AI RESEARCH
From GPS Points to Travel Patterns: Flexible and Semantic Trajectory Generation with LLMs
arXiv CS.AI
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ArXi:2605.30014v1 Announce Type: new Urban trajectories play a crucial role in modeling urban dynamics and ing various smart city applications. However, privacy concerns restrict access to large-scale and high-quality trajectory datasets. Trajectory generation provides a promising alternative by synthesizing realistic data to mitigate privacy risks. However, existing methods fail to explicitly capture travel patterns and can only generate fixed-length trajectories under a single condition.