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Dongliang Xu

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#artificial intelligence Preprint Sep 2026

AquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents

World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequences of candidate actions before interacting with the physical environment. However, underwater robots are usually subject to passive dynamics, such as inertia, buoyancy,...

Cun-Hao Zhu, Yi-Feng Wang, Dong-Liang Xu et al. · 0 citations
Jul 2026

No Training, Better Flights: Test-Time Scaled VLMs for UAV Navigation

A simple and effective approach to apply test-time scaling to VLN for UAV navigation through an iterative refinement process that requires no extra model training, guiding the model to re-evaluate its initial navigation plan for better accuracy and safety.

Feinan Cheng, Dongliang Xu, Wenli Nong et al. · 0 citations

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