Papers with non-English-speaking users
Annotation-Efficient Vision-Language Model Adaptation to the Polish Language Using the LLaVA Framework (2026.eacl-srw)
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Grzegorz Statkiewicz, Alicja Dobrzeniecka, Karolina Seweryn, Aleksandra Krasnodębska, Karolina Piosek, Katarzyna Bogusz, Sebastian Cygert, Wojciech Kusa
| Challenge: | Currently, most vision-language models are trained on English-centric data, limiting their usability for non-English-speaking users. |
| Approach: | They reproduce and adapt LLaVA-Next methodology to create Polish VLMs . they use a fully automated pipeline for translating and filtering existing multimodal datasets based on Polish data for OCR and culturally specific tasks. |
| Outcome: | The proposed model improves on a Polish-adapted model and shows higher quality captions in generative evaluations. |