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Towards a Data-Centric Understanding of Spatial Reasoning in Multimodal Large Language Models

arXiv:2610.19108v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have been widely applied in embodied agents and robotics for vision tasks. However, MLLMs suffer from limitations in spatial reasoning and perception. Post-training techniques have shown promise for improving t…

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  1. 2026-10-15 04:00 · arXiv cs.CV
    Towards a Data-Centric Understanding of Spatial Reasoning in Multimodal Large Language Models

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