arXiv Computer Vision August 28, 2026 By Bojun Zhang, Junhong Liang, Feifei Zhai, Fengxian Ji, Yu Zhou

ReViCo: Unveiling the Limitations of VLMs in Visual Text Understanding via Error Correction

Read the original on arXiv Computer Vision →

ReViCo (Real Visual Correction) is a new benchmark that tests Vision Language Models (VLMs) on the task of correcting text errors in real‑world images, requiring deep understanding of visual text and its context. The study evaluates VLMs using both prompt‑based and targeted training approaches, revealing a significant performance gap between current models and humans. The results show that most VLMs struggle to accurately perceive visual text, leading to frequent correction mistakes, thereby underscoring the need for more robust, text‑aware VLMs.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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