he-h/rhythm
[NeurIPS 2025] RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
RHYTHM helps urban planners, transportation analysts, and researchers understand and predict how people move within cities. It takes raw human movement data, like GPS trajectories, and uses it to forecast future mobility patterns across different urban environments. This tool is for anyone needing to model and predict human movement at scale, especially across multiple cities.
No commits in the last 6 months.
Use this if you need a scalable and efficient way to predict human mobility patterns across various cities, leveraging existing large language model capabilities without extensive computational resources.
Not ideal if your primary goal is to predict movement for individual users or specific niche scenarios rather than broader, city-level patterns.
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8
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3
Language
Python
License
MIT
Category
Last pushed
Oct 07, 2025
Commits (30d)
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