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Plus MMStar RealWorldQA Method, K\mathcal{F}=\{f_{j}\}_{j=1}^{K} includes both closed-source and open-weight MLLMs with heterogeneous architectures, capacities, and cost profiles: • Commercial MLLMs, including GPT-5 series [1], Gemini 2.5 series [25], and Claude models, which offer strong general-purpose multimodal reasoning at higher monetary cost. • Open-weight MLLMs, spanning
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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.