arXiv cs.AI· Xiaofei Yu, Kailai Sun, Yanyu Mao, Baoshen Guo, Heye Huang, Yongcai Wang, Baotong Mi, Alok Prakash, Shenhao Wang, Jinhua Zhao·· 2 小时前AI 评分32
AgenticCity-Bench：面向城市动态纵向多模态观测与智能体推理的基准
AgenticCity-Bench: Longitudinal Multimodal Observations of Urban Dynamics with Agentic Reasoning
AI 导读
研究者推出 AgenticCity-Bench，一个用于多层统一状态建模与智能体城市任务推理的纵向多模态基准。该基准覆盖六大洲 12 个国家的 16 个城市，时间跨度为 2000 至 2025 年，包含涵盖城市功能、活动和环境状态的 18 种模态，并支持城市跨模态翻译以及涉及预测、规划和资源分析的智能体任务。数据集已开放获取。
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