Authors: Weijia Zhang, Jindong Han, Zhao Xu, Hang Ni, Hao Liu, Hui Xiong

Published on: January 30, 2024

Impact Score: 8.3

Arxiv code: Arxiv:2402.01749

Summary

• What is new: The paper introduces the concept of Urban Foundation Models (UFMs) and proposes a novel framework for their development.
• Why this is important: Lack of clear definitions, systematic reviews, and scalable solutions in integrating machine learning into urban development.
• What the research proposes: A data-centric taxonomy for classifying UFM-related works and a new framework to guide the development of UFMs.
• Results: The paper lays the groundwork for the systematic advancement of UFMs, with potential applications highlighted across various urban contexts.

Technical Details

Technological frameworks used: Data-centric taxonomy, proposed UFM development framework

Models used: Foundation models like ChatGPT

Data used: Urban data modalities and types

Potential Impact

Smart city solutions providers, urban planning agencies, and technology companies focusing on AI and machine learning in urban contexts.

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