AIBearisharXiv – CS AI · May 127/10
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The Cartesian Shortcut: Re-evaluate Vision Reasoning in Polar Coordinate Space
Researchers reveal that multimodal large language models achieve high visual reasoning benchmark scores by exploiting a 'Cartesian Shortcut'—leveraging grid-based layouts that convert to explicit text coordinates rather than performing genuine visual understanding. The Polaris-Bench study shows frontier models collapse from 70-83% accuracy to 31-39% when benchmarks are reformulated in polar coordinate space, exposing critical deficiencies in topology-invariant reasoning.