arXiv Computer Vision October 9, 2026 By Kaichun Yang, Jian Chen

A Stevens's Power Law Check-up of GPT-5.5's Implicit Reading of Visual Encoding

Read the original on arXiv Computer Vision →

The paper adapts Stevens's power law to assess how AI models, specifically GPT‑5.5, implicitly interpret visualizations. In a pilot study, the model first estimates the magnitude of a reference visual representation and then compares subsequent images of the same representation, without access to legends or colormap names. The evaluation covers twelve visual variables, aiming to make algorithmic reading of visual encodings measurable, comparable to human perception, and more transparent.

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