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cs.CL2025

Can Code-Switched Texts Activate a Knowledge Switch in LLMs? A Case Study on English-Korean Code-Switching

Seoyeon Kim, Huiseo Kim, Chanjun Park +2

Recent large language models (LLMs) demonstrate multilingual abilities, yet they are English-centric due to dominance of English in training corpora. The limited resource for low-r…

cs.CL2025

LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs

Sumin An, Junyoung Sung, Wonpyo Park +2

While large language models (LLMs) excel in generating coherent and contextually rich outputs, their capacity to efficiently handle long-form contexts is limited by fixed-length po…

cs.CL2025

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

Hyeonwoo Kim, Dahyun Kim, Jihoo Kim +3

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…

cs.CL2025

Understanding LLM Development Through Longitudinal Study: Insights from the Open Ko-LLM Leaderboard

Chanjun Park, Hyeonwoo Kim

This paper conducts a longitudinal study over eleven months to address the limitations of prior research on the Open Ko-LLM Leaderboard, which have relied on empirical studies with…

cs.CL2024

LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models

Yungi Kim, Hyunsoo Ha, Seonghoon Yang +3

Creating high-quality, large-scale datasets for large language models (LLMs) often relies on resource-intensive, GPU-accelerated models for quality filtering, making the process ti…

cs.CL2024

Representing the Under-Represented: Cultural and Core Capability Benchmarks for Developing Thai Large Language Models

Dahyun Kim, Sukyung Lee, Yungi Kim +2

The rapid advancement of large language models (LLMs) has highlighted the need for robust evaluation frameworks that assess their core capabilities, such as reasoning, knowledge, a…