PolyComp: A Polycube-based Benchmark for Compositional 3D Spatial Reasoning in Multimodal Models
We introduce PolyComp, a procedurally generated and verified benchmark that stresses visual recognition and compositional spatial reasoning. In each problem, a model must identify which of four options shows a pair of polycube components that can be combined to form a target solid. The benchmark contains 120 problems across four geometry families, and each problem has three different presentation formats using either a single image or multiple images. The random guessing baseline is 25%. Across the three presentations (360 presented problems per model), GPT-5.6 Sol with max effort attains 50.0% accuracy (95% problem-cluster CI 43.3-56.7%) at a mean cost of \$0.951 per presented problem, C...
| Authors | Siddharth Patel |
|---|---|
| Primary category | cs.CV |
| Published | 13 August 2026 |
| Last updated at source | 27 August 2026 |
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