VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models
Authors: name: Jeongho Ju, name: Daeyoung Kim, name: SunYoung Park, name: Youngjune Kim

In this paper, we introduce an open-source Korean-English vision-language
model (VLM), VARCO-VISION. We incorporate a step-by-step training strategy that
allows a model learn both linguistic and visual information while preserving
the backbone model's knowledge. Our model demonstrates outstanding performance
in diverse settings requiring bilingual image-text understanding and generation
abilities compared to models of similar size. VARCO-VISION is also capable of
grounding, referring, and OCR, expanding its usage and potential applications
for real-world scenarios. In addition to the model, we release five Korean
evaluation datasets, including four closed-set and one openset benchmarks. We
anticipate that our milestone will broaden the opportunities for AI researchers
aiming to train VLMs. VARCO-VISION is available at
https://huggingface.co/NCSOFT/VARCO-VISION-14B.