AI RESEARCH
Zero-Shot 3D Question Answering via Hierarchical View-to-Token Transportation
arXiv CS.LG
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ArXi:2606.03100v1 Announce Type: cross Recently, zero-shot 3D scene understanding via 2D Vision-Language Models (VLMs) has gained increasing research interest due to their promising spatial reasoning capabilities. Typically, multiple 2D views are sampled from a 3D point cloud and fed into pre-trained VLMs to answer a given question. This paradigm highlights the critical role of input context quality and raises the challenge of retaining as many task-relevant 3D details as possible under a limited input budget.