7 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CL2026
What Models Know, How Well They Know It: Knowledge-Weighted Fine-Tuning for Learning When to Say "I Don't Know"
Joosung Lee, Hwiyeol Jo, Donghyeon Ko +3
While large language models (LLMs) demonstrate strong capabilities across diverse user queries, they still suffer from hallucinations, often arising from knowledge misalignment bet…
cs.CL2025
KoSimpleQA: A Korean Factuality Benchmark with an Analysis of Reasoning LLMs
Donghyeon Ko, Yeguk Jin, Kyubyung Chae +6
We present , a benchmark for evaluating factuality in large language models (LLMs) with a focus on Korean cultural knowledge. KoSimpleQA is d…
cs.CL2024★ 7 cited
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…