tabtoyou/KRETA
KRETA Benchmark π€ KRETA | π Paper | π Leaderboard | π» Github KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts (EMNLP 2025 Main Conference) Taebaek Hwang*, Minseo Kim*, Gisang Lee, Seonuk Kim, Hyunjun Eun Abstract Understanding and reasoning over text within visual contexts poses a significant challenge for Vision-Language Models (VLMs), given the complexity and diversity of real-world scenarios. Toβ¦ See the full description on the dataset page: https://huggingface.co/datasets/tabtoyou/KRETA.
| Author / organization | tabtoyou |
|---|---|
| Downloads | 498 (as reported by Hugging Face) |
| Likes | 14 |
| Created | 3 February 2025 |
| Last updated at source | 8 September 2025 |
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498 now (+2 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
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- 17 Oct 2026 Description: KRETA Benchmark π€ KRETA | π Paper | π Leaderboard | π» Github KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts (EMNLP 2025 Main Conference) Taebaek Hwang*, Minseo Kim*, Gisang Lee, S β KRETA Benchmark π€ KRETA | π Paper | π Leaderboard | π» Github KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts (EMNLP 2025 Main Conference) Taebaek Hwang*, Minseo Kim*, Gisang Lee, S
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