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UMMs exhibit significant exposure bias in multi-turn interactions, revealing critical performance gaps that existing benchmarks overlook.
Forget LLMs – generating realistic 3D scenes might just hinge on learning how objects relate to each other locally.
Monocular SLAM gets a serious upgrade: M^3 slashes pose estimation error by 64% by fusing multi-view foundation models with dense matching.
