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Evaluating Multimodal Generative AI with Korean Educational Standards

KoNET evaluates Multimodal Generative AI Systems using Korean national educational tests across various levels, focusing on language-specific performance.

Year
2025
Venue
arXiv 2025
Authors
2
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arxiv.org/abs/2502.15422ARXIV-DEFAULT
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Abstract

This paper presents the Korean National Educational Test Benchmark (KoNET), a new benchmark designed to evaluate Multimodal Generative AI Systems using Korean national educational tests. KoNET comprises four exams: the Korean Elementary General Educational Development Test (KoEGED), Middle (KoMGED), High (KoHGED), and College Scholastic Ability Test (KoCSAT). These exams are renowned for their rigorous standards and diverse questions, facilitating a comprehensive analysis of AI performance across different educational levels. By focusing on Korean, KoNET provides insights into model performance in less-explored languages. We assess a range of models - open-source, open-access, and closed APIs - by examining difficulties, subject diversity, and human error rates. The code and dataset builder will be made fully open-sourced at https://github.com/naver-ai/KoNET.

Authors

2