CityBehavEx: Scalable LLM-Assisted Urban Simulation Platform Validated Against Real-World Mobility

Jul 15, 2026

CityBehavEx is an interactive urban simulation platform that integrates large language models (LLMs) with traditional human mobility models to efficiently simulate city-scale populations. The system can run simulations of 100,000 agents over 75 days in under one hour on a single consumer GPU, and supports empirical validation by comparing generated mobility patterns to real-world spatial, temporal, and semantic distributions. CityBehavEx also provides tools for inspecting agent behavior, debugging, and validating routines against real-world data, addressing scalability and validation challenges in prior LLM-based simulators.

Why it matters: This work offers a scalable and empirically validated approach to LLM-driven urban simulation, potentially advancing applications in urban planning and policy analysis.

Full story at: arXiv Computation and Language ↗