arXiv — NLP / Computation & Language · · 3 min read

Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation

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Computer Science > Computation and Language

arXiv:2608.07763 (cs)
[Submitted on 7 Aug 2026]

Title:Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation

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Abstract:Vision-language models (VLMs) have achieved strong performance on tasks such as image captioning, visual question answering, and image-to-text generation. However, they are predominantly trained on English-centric data, which limits their ability to handle culturally grounded visual understanding and leads to failures in interpreting region-specific meanings, symbolic content, and context-dependent visual cues. Existing benchmarks for cultural competence are often template-driven and focused on surface-level recognition, making them insufficient for evaluating deeper linguistic and pragmatic understanding in culturally situated settings. We introduce PoVisLE, a monocultural vision-language benchmark for Polish designed to evaluate culturally grounded multimodal understanding under a grounded evaluation paradigm, where language is interpreted in interaction with visual context. The dataset contains 1,117 images and 2,366 manually annotated VQA pairs. Overall, our dataset provides a controlled and challenging resource for assessing culturally grounded vision-language understanding beyond surface-level recognition.
Comments: 28 pages. Preprint under review
Subjects: Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2608.07763 [cs.CL]
  (or arXiv:2608.07763v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2608.07763
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Wojciech Kusa [view email]
[v1] Fri, 7 Aug 2026 21:01:14 UTC (11,726 KB)
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