SpatialBlock: Teaching LVLMs Spatial Reasoning with Synthetic Block-Stacking
KAIST AI
KAIST researchers build SpatialBlock-15k, a 15k-problem synthetic dataset of block-stacking tasks covering 3D-to-2D projection, viewpoint transformation, and structural composition. VLMs fine-tuned on it significantly outperform baselines and generalize to real-world spatial tasks, avoiding costly dense geometric annotation of real scenes.
Why it matters
Cheap structured synthetic data closes a real spatial-reasoning gap that real-image annotation has failed to fix
Importance: 2/5
Notable synthetic-data paper for spatial reasoning