Large Language Models

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KoSimpleQA: A Korean Factuality Benchmark with an Analysis of Reasoning LLMs
Date pendingDonghyeon Ko, Kyubyung Chae, Yeguk Jin +6Korean Facts
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Date pendingErfan LoghmaniLarge Language Model Fine-Tuning Large Language Model Performance
Closed-Loop Bayesian Molecular Inverse Design with Semantic LLM Surrogates
Date pendingYaoyao Xu, Xinjian Zhao, Xiaozhuang Song +2Bayesian Optimization Large Language
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Date pendingKexin Chu, Dawei Xiang, Zixu Shen +3Mixture-Of-Expert Inference Mixed-Precision Quantization
AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training
Date pendingZhenyu Han, Ansheng You, Haibo Wang +16Asynchronous Execution LLM Post-Training Methods
UrduMMLU: A Massive Multitask Benchmark for Urdu Language Understanding
Date pendingAhmer Tabassum, Sarfraz Ahmad, Hasan Iqbal +3Multilingual Benchmark Mmlu-Pro
LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains
Date pendingRyogo Hishikawa, Ichiro Kataoka, Shinya YudaCollaborative Filtering Recommendation

Date pending · cs.CLJ/K move · Enter open · S save

KoSimpleQA: A Korean Factuality Benchmark with an Analysis of Reasoning LLMs

Donghyeon Ko, Kyubyung Chae, Yeguk Jin, Byungwook Lee+5

We present

\textbf{Korean SimpleQA (KoSimpleQA)}

, a benchmark for evaluating factuality in large language models (LLMs) with a focus on Korean cultural knowledge. KoSimpleQA is designed to be challenging yet easy to grade, consisting of 938 short, fact-seeking questions with unambiguous answers. We conduct a comprehensive evaluation across a diverse set of open-source LLMs of varying sizes that support Korean, and find that even the strongest model generates correct answer only 31.6% of the time, underscoring the challenging nature of KoSimpleQA. Notably, performance rankings on KoSimpleQA differ substantially from those on the English SimpleQA, highlighting the unique value of our dataset. Furthermore, we observe that reasoning helps mitigate the cross-lingual knowledge gap in LLMs, which refers to disparities in their ability to manifest knowledge across languages. KoSimpleQA can be found at https://github.com/naver-ai/KoSimpleQA.

Korean Facts Large Language Model Reasoning Large Language

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