arXiv cs.AI· Xiaofei Yu, Kailai Sun, Yanyu Mao, Baoshen Guo, Heye Huang, Yongcai Wang, Baotong Mi, Alok Prakash, Shenhao Wang, Jinhua Zhao·· 15 小时前AI 评分24
AgenticCity-Bench：面向智能体推理的城市动态纵向多模态基准
AgenticCity-Bench: Longitudinal Multimodal Observations of Urban Dynamics with Agentic Reasoning
AI 导读
AgenticCity-Bench 是一个纵向多模态基准，覆盖六大洲 12 个国家 16 座城市 2000 至 2025 年的数据，包含城市功能、活动与环境状态三类共 18 种模态。该基准以统一空间参考和日历索引组织异构数据源，支持城市跨模态转换以及预测、规划、资源分析等智能体城市任务。数据集已公开，用于研究从多模态城市与地球观测走向联合理解与智能体城市决策。
正文 · 原文
Abstract:City systems are shaped by interactions among infrastructure, human activity, and environmental conditions. Existing earth observation and urban benchmarks are limited in unified modeling and in capturing their joint dynamics. We introduce AgenticCity-Bench, a longitudinal multimodal benchmark for multi-layer unified state modeling and agentic city task reasoning. The benchmark covers 16 cities in 12 countries across six continents from 2000 to 2025, and includes 18 modalities spanning urban function, activity, and environmental state. It organizes heterogeneous data sources around a common spatial reference and calendar index while preserving spatial and temporal coverage, provenance and tile-level availability. On this foundation, AgenticCity-Bench supports urban cross-modal translation together with diverse agentic city tasks involving forecasting, planning and resource analysis. This study provides a unified benchmark for studying the transition from multimodal urban and earth observation to joint understanding and agentic city decision-making. The dataset is available at this https URL.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.35293 [cs.AI] |
| (or arXiv:2610.35293v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.35293 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Kailai Sun [view email]
[v1]
Mon, 26 Oct 2026 12:01:17 UTC (14,736 KB)
来源：arXiv cs.AI · arxiv.org