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Author

Yongbin Choi

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Open access Aug 2026

KoViDoRe: A Benchmark for Korean Visual Document Retrieval

This work introduces KoViDoRe, a benchmark for Korean visual document retrieval, and curates a large-scale training dataset, Ko-VDR Train Public, to support the development of retrieval models tailored to Korean visual documents.

Yongbin Choi, Yongwoo Song, Mujeen Sung · 1 citation
Preprint Aug 2026

KoVRE: Training an Efficient Embedding Model for Korean Visual Document Retrieval

KoVRE: Korean Visual Document Retrieval Embedding is introduced, a single-vector retriever for Korean visual documents, alongside a comprehensive training recipe, demonstrating that targeted bilingual supervision and carefully designed training strategies can produce a highly effective Korean VDR model across diverse d...

Yongbin Choi, Gyuho Shim, Youngjoon Jang · 0 citations

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