重构韩语大模型评估体系，更贴近真实应用与语言特点。
Open Ko-LLM Leaderboard2: Bridging Foundational and Practical Evaluation for Korean LLMs
- 用全新真实场景任务替代旧有学术化评测
- 新增4个本土韩语评测，捕捉语言独特性
- 适合关注韩语模型实用性能的研究者与开发者
Open Ko-LLM Leaderboard 在评估韩语大模型方面发挥了重要作用，但仍存在局限：其量化提升与模型实际应用效果之间存在脱节，且评测集主要为英文基准的翻译版本，未能充分反映韩语特性。为此，我们提出 Open Ko-LLM Leaderboard2，全面替换原有评测任务，引入更贴近真实应用场景的新任务，并新增4个原生韩语评测，以更好体现韩语的独特性。该更新旨在推动韩语大模型评价体系向更实用、更精准的方向发展。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。