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GeoAnchor: Collaborative Reasoning via Latent Decomposition for 3D Spatial Understanding

arXiv cs.CV2w4 min read

arXiv:2607.13454v1 Announce Type: new Abstract: Although multimodal large language models (MLLMs) have achieved remarkable progress, understanding 3D spatial relationships from 2D images remains a critical challenge. Existing methods primarily rely on symbolic text tokens, which inherently lack the fidelity to represent continuous geometric information. While recent methods use latent representations to enhance reasoning, relying on a single latent type cannot adapt to the diversity of spatial tasks, leading to misalignment in complex geometric scenarios. To address these limitations, we propo

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