collaborators

5 papers

cs.CV2026

AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration

Haotian Li, Yida Wang, Leyuan Wang +7

In recent years, multimodal large language models (MLLMs) have shown strong potential for embodied intelligence, yet their ability to maintain geometrically consistent spatial unde…

cs.RO2026

Intelligent Automation for Embodied Benchmark Construction: Pipelines, Embodiments, Simulators, and Trends

Jinshan Lai, Jianwei Hu, Baoyang Jiang +7

Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control. This expansion has made bench…

cs.AI2026

Embodied-BenchClaw: An Autonomous Multi-Agent System for Embodied Spatial Intelligence Benchmark Construction

Baoyang Jiang, Fengchun Zhang, Leyuan Wang +7

Benchmarks are essential for evaluating embodied spatial intelligence, yet their construction is labor-intensive, hard to reuse, and difficult to maintain. Existing embodied benchm…

cs.SE2026

Exploring and Complementing End Users' Requirements in IoT enabled System

Haotian Li, Xiaohong Chen, Zhi Jin +4

End users create IoT automation rules via trigger action programming, but their expressions are often fragmented, capturing device operations rather than high level intents. This g…

cs.HC2026

Figures as Interfaces: Toward LLM-Native Artifacts for Scientific Discovery

Yifang Wang, Rui Sheng, Erzhuo Shao +4

Large language models (LLMs) are transforming scientific workflows, not only through their generative capabilities but also through their emerging ability to use tools, reason abou…