5 papers
KoAGE: Do Large Language Models Know, Learn, and Coin Korean Neologisms?
SungHo Kim, Eojin Jeon, SangKeun Lee
Korean neologisms arise through diverse mechanisms, a demanding test of language models beyond lexical memorization. To enable systematic evaluation, we introduce NeoTrace, an auto…
KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters
SungHo Kim, Juhyeong Park, Yeachan Kim +1
The Korean writing system, \textit{Hangeul}, has a unique character representation rigidly following the invention principles recorded in \textit{Hunminjeongeum}.\footnote{\textit{…
SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models
SungHo Kim, Juhyeong Park, Eda Atalay +1
Korean is a morphologically rich language with a featural writing system in which each character is systematically composed of subcharacter units known as Jamo. These subcharacters…
Incorporating Domain Knowledge into Materials Tokenization
Yerim Oh, Jun-Hyung Park, Junho Kim +2
While language models are increasingly utilized in materials science, typical models rely on frequency-centric tokenization methods originally developed for natural language proces…
Polishing Every Facet of the GEM: Testing Linguistic Competence of LLMs and Humans in Korean
SungHo Kim, Nayeon Kim, Taehee Jeon +1
We introduce the , designed to assess the linguistic competence of LLMs and humans in K…