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cs.AI2026
How Far Are Large Multimodal Models from Human-Level Spatial Action? A Benchmark for Goal-Oriented Embodied Navigation in Urban Airspace
Baining Zhao, Ziyou Wang, Jianjie Fang +8
Large multimodal models (LMMs) show strong visual-linguistic reasoning but their capacity for spatial decision-making and action remains unclear. In this work, we investigate wheth…
cs.AI2025
AutoSearch: Unlocking the Reasoning Potential of Large Models for Web-based Source Search
Zhengqiu Zhu, Yatai Ji, Jiaheng Huang +3
Web-based management systems have been widely used in risk control and industrial safety. However, effectively integrating source search capabilities into these systems, to enable…
cs.AI2025
CityEQA: A Hierarchical LLM Agent on Embodied Question Answering Benchmark in City Space
Yong Zhao, Kai Xu, Zhengqiu Zhu +7
Embodied Question Answering (EQA) has primarily focused on indoor environments, leaving the complexities of urban settings-spanning environment, action, and perception-largely unex…