6 citations · 9 across the 7 of their papers we have counts for
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cs.AI2025
CityLens: Evaluating Large Vision-Language Models for Urban Socioeconomic Sensing
Tianhui Liu, Hetian Pang, Xin Zhang +5
Understanding urban socioeconomic conditions through visual data is a challenging yet essential task for sustainable urban development and policy planning. In this work, we introdu…
cs.AI2024★ 6 cited
CityGPT: Empowering Urban Spatial Cognition of Large Language Models
Jie Feng, Tianhui Liu, Yuwei Du +3
Large language models(LLMs), with their powerful language generation and reasoning capabilities, have already achieved notable success in many domains, e.g., math and code generati…
cs.AI2024★ 3 cited
CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
Jie Feng, Jun Zhang, Tianhui Liu +6
As large language models (LLMs) continue to advance and gain widespread use, establishing systematic and reliable evaluation methodologies for LLMs and vision-language models (VLMs…