KoViDoRe: A Benchmark for Korean Visual Document Retrieval
Recent advances in multimodal retrieval have improved the ability to retrieve information from visually rich documents such as PDFs and reports. However, existing benchmarks remain largely centered on English and provide limited coverage of Korean visual documents with complex structures. Furthermore, most existing Korean resources primarily evaluate single-page retrieval, failing to capture realistic scenarios that require evidence aggregation across multiple pages. To address these gaps, we introduce KoViDoRe, a benchmark for Korean visual document retrieval. The dataset is constructed from publicly available Korean documents with diverse layouts, including tables, figures, and multi-co...
| Authors | Yongbin Choi, Yongwoo Song, Mujeen Sung |
|---|---|
| Primary category | cs.IR |
| Published | 21 August 2026 |
| Last updated at source | 15 October 2026 |
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