Papers with Visual text compression

1 papers
Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale (2026.findings-acl)

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Challenge: Visual text compression is emerging paradigm for rendering text as images for processing by vision-language models.
Approach: They propose a benchmark to assess VLM robustness under dense visual inputs.
Outcome: Evaluating 13 general-purpose VLMs and 3 OCR-specialized models reveals performance drops sharply under increased density or reduced resolution; cross-task transfer between OCR, NIAH, and VQA is limited; and VQ is comparatively robust because low-level details are lost before high-level semantics.

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