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Forget costly, inflexible legacy travel demand models: a new generative framework matches their accuracy while slashing development time and boosting scalability.
This work presents a foundation model framework for universal human mobility patterns that leverages cross-domain data fusion and large language models to address limitations in existing approaches, and demonstrates adaptability through domain transfer techniques that ensure transferability across diverse urban contexts.
