Open Ko-LLM Leaderboard2: Bridging Foundational and Practical Evaluation for Korean LLMs

Fuente: arXiv
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Auteurs principaux: Kim, Hyeonwoo, Kim, Dahyun, Kim, Jihoo, Lee, Sukyung, Kim, Yungi, Park, Chanjun
Format: Preprint
Publié: 2024
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author Kim, Hyeonwoo
Kim, Dahyun
Kim, Jihoo
Lee, Sukyung
Kim, Yungi
Park, Chanjun
author_facet Kim, Hyeonwoo
Kim, Dahyun
Kim, Jihoo
Lee, Sukyung
Kim, Yungi
Park, Chanjun
contents The Open Ko-LLM Leaderboard has been instrumental in benchmarking Korean Large Language Models (LLMs), yet it has certain limitations. Notably, the disconnect between quantitative improvements on the overly academic leaderboard benchmarks and the qualitative impact of the models should be addressed. Furthermore, the benchmark suite is largely composed of translated versions of their English counterparts, which may not fully capture the intricacies of the Korean language. To address these issues, we propose Open Ko-LLM Leaderboard2, an improved version of the earlier Open Ko-LLM Leaderboard. The original benchmarks are entirely replaced with new tasks that are more closely aligned with real-world capabilities. Additionally, four new native Korean benchmarks are introduced to better reflect the distinct characteristics of the Korean language. Through these refinements, Open Ko-LLM Leaderboard2 seeks to provide a more meaningful evaluation for advancing Korean LLMs.
format Preprint
id arxiv_https___arxiv_org_abs_2410_12445
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Open Ko-LLM Leaderboard2: Bridging Foundational and Practical Evaluation for Korean LLMs
Kim, Hyeonwoo
Kim, Dahyun
Kim, Jihoo
Lee, Sukyung
Kim, Yungi
Park, Chanjun
Computation and Language
Artificial Intelligence
The Open Ko-LLM Leaderboard has been instrumental in benchmarking Korean Large Language Models (LLMs), yet it has certain limitations. Notably, the disconnect between quantitative improvements on the overly academic leaderboard benchmarks and the qualitative impact of the models should be addressed. Furthermore, the benchmark suite is largely composed of translated versions of their English counterparts, which may not fully capture the intricacies of the Korean language. To address these issues, we propose Open Ko-LLM Leaderboard2, an improved version of the earlier Open Ko-LLM Leaderboard. The original benchmarks are entirely replaced with new tasks that are more closely aligned with real-world capabilities. Additionally, four new native Korean benchmarks are introduced to better reflect the distinct characteristics of the Korean language. Through these refinements, Open Ko-LLM Leaderboard2 seeks to provide a more meaningful evaluation for advancing Korean LLMs.
title Open Ko-LLM Leaderboard2: Bridging Foundational and Practical Evaluation for Korean LLMs
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2410.12445