Tianjian Ouyang — accepted AI-conference papers

2026

CityLens: Evaluating Large Vision-Language Models for Urban Socioeconomic Sensing

Tianhui Liu, Hetian Pang, Xin Zhang, Tianjian Ouyang, Zhiyuan Zhang, Jie Feng +2

ICLR 2026poster

Understanding urban socioeconomic conditions through visual data is a challenging yet essential task for sustainable urban development and policy planning. In this work, we introduce CityLens, a comprehensive benchmark designed to evaluate the capabilities of Large Vision-Language Models (LVLMs) in…

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2026

UrbanMLLM: Joint Learning of Cross-view Imagery for Urban Understanding

Xin Zhang, Tianjian Ouyang, Yu Shang, Qingmin Liao, Yong Li

ICML 2026poster

Comprehensive urban understanding requires integrating macroscopic spatial structure with fine-grained street-level semantics. However, existing urban Multimodal Large Language Models (MLLMs) primarily rely on satellite imagery, limiting their ability to capture detailed urban appearance and cross-v…

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