Sorry Robot, Happy Human: Vision-Language Models Read Only One of Two Legible Typographic Layers
Vision-language models (VLMs), despite their success in optical character recognition (OCR) tasks, are vulnerable to typographic attacks and have a fragile structure for images with multiple text layers. In this study, the DecoyBench dataset was created using the Decoy Font method. The dataset consists of 300 images, each containing text with sharp contour lines superimposed on another text with soft shading. Six recent closed-source models from three different model families were evaluated using this dataset under two different prompting conditions (naive and guided) and at two different resolutions ($512\times512$ and $64\times64$). A validation study showed that human participants coul...
| Authors | Mert İncidelen, Yamen Kashkash, Asya Berker et al. |
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| Primary category | cs.CL |
| Published | 25 September 2026 |
| Last updated at source | 25 September 2026 |
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