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This paper introduces a validation framework to evaluate whether LLM-based urban simulators reproduce empirical human mobility patterns. Using data from Paris and Shanghai, the authors find a substantial gap between plausible narratives and realistic mobility constraints, and provide open infrastructure for reproducible evaluation.
TrajGenAgent proposes a hierarchical LLM agent framework that decouples macro-level activity planning from micro-level spatiotemporal instantiation for realistic human mobility trajectory generation without fine-tuning. It also introduces an anomaly-detection-based evaluation for behavioral fidelity.