AI RESEARCH
ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Framework
arXiv CS.LG
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ArXi:2603.07946v1 Announce Type: new Human mobility generation aims to synthesize plausible trajectory data, which is widely used in urban system research. While Large Language Model-based methods excel at generating routine trajectories, they struggle to capture deviated mobility during large-scale societal events.