Do VLMs Read or Rewrite? On Transcription Faithfulness in Vision-Language Models
Vision Language Models (VLMs) are increasingly used in place of traditional OCR pipelines for document understanding. In this paper, we show they do not always act as faithful transcribers: when text is imperfect, they often tend to rewrite it into a more plausible form - a behavior that clean-text OCR benchmarks cannot detect. We introduce FaithC4, a multilingual perturbation benchmark of 1,455 single-page documents (English, Chinese, Korean) with three perturbation families: scramble, random substitution, and visually similar substitution. We use the benchmark to evaluate 15 systems spanning general-purpose VLMs, OCR-specialized VLMs, and traditional OCR pipelines. These three categorie...
| Authors | Gwang Gook Lee, Kenan Emir Ak, Jay Mohta et al. |
|---|---|
| Primary category | cs.AI |
| Published | 29 May 2026 |
| Last updated at source | 2 September 2026 |
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