---
license: apache-2.0
task_categories:
- image-text-to-text
tags:
- vlm
- spatial-reasoning
---

# SpaceNum: Revisiting Spatial Numerical Understanding in VLMs

[Project Page](https://sterzhang.github.io/SpaceNum-Home/) | [Paper](https://huggingface.co/papers/2605.23898)

SpaceNum is a unified framework designed to evaluate how well Vision-Language Models (VLMs) ground numerical outputs in spatial perception. It covers two complementary settings:
1. **Numbers as dynamic transitions** during spatial exploration.
2. **Numbers as static layouts** in spatial reasoning.

The benchmark formulates two bidirectional tasks, **Num2Space** and **Space2Num**, to assess the mapping between vision-side spatial structures and language-side numerical representations. SpaceNum aims to determine if VLM numerical outputs are truly grounded in spatial perception or if models rely on shallow spatial cues.