Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

Researchers at an unspecified institution argue that Vision-Language Models (VLMs) lack spatial reasoning due to a dimensional mismatch from training on 2D projections, proposing a method to factorize 4D properties to reinforce spatial understanding.

Despite the remarkable prowess of Vision-Language Models VLMs in general multimodal tasks, they remain fundamentally flat'' when reasoning about the physical world. We argue that this spatial bottleneck stems from a profound dimensional mismatch: while VLMs are trained to interpret 2D projection