TrajGenAgent is a hierarchical LLM-agent framework that generates human mobility trajectories via in-context activity chain synthesis followed by deterministic visit grounding, evaluated with anomaly-detection detectors for behavioral and semantic plausibility.
arXiv preprint arXiv:2402.14744 , year=
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ARMove is a transferable framework for human mobility prediction that combines agentic LLM reasoning, feature management, and large-small model synergy to outperform baselines on several metrics while improving interpretability and robustness.
A survey synthesizing LLM and MM-LLM uses in transportation operations, mobility services, and decision support while noting challenges like data heterogeneity and real-time needs.
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TrajGenAgent: A Hierarchical LLM Agent for Human Mobility Trajectory Generation
TrajGenAgent is a hierarchical LLM-agent framework that generates human mobility trajectories via in-context activity chain synthesis followed by deterministic visit grounding, evaluated with anomaly-detection detectors for behavioral and semantic plausibility.
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ARMove: Learning to Predict Human Mobility through Agentic Reasoning
ARMove is a transferable framework for human mobility prediction that combines agentic LLM reasoning, feature management, and large-small model synergy to outperform baselines on several metrics while improving interpretability and robustness.
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Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support
A survey synthesizing LLM and MM-LLM uses in transportation operations, mobility services, and decision support while noting challenges like data heterogeneity and real-time needs.