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Matching papers

MJev-Spatial: System One Spatial Intelligence via Native Attention Matching

353 upvotes · 15 OCT 2026 · Luozheng Qin, Yuhan Zhu, Changhai Zhou et al.

This paper introduces MJev-Spatial, a new AI model that can quickly understand and act in the physical world by using a unified classification framework to answer spatial intelligence tasks. Practitioners may care about this model because it can solve real-world problems faster and more efficiently than existing models.

vision-language modelsspatial intelligencemultimodal decision modelscontinual learningpretrainingbatching

SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem

134 upvotes · 7 SEP 2026 · Soohyun Ryu, Sohee Kim, Eunho Yang

This paper helps large Vision-Language Models (LVLMs) better understand and reason about 3D scenes from 2D images, a key aspect of spatial intelligence, by training them on a synthetic dataset of block-stacking problems. Practitioners might care because improving spatial intelligence can lead to better performance on various visual tasks.

vision-language modelsspatial intelligencesynthetic datasetsblock-stacking3D-to-2D projection