1 citations · 1 across the 4 of their papers we have counts for
5 papers
KBS: A Korean Benchmark Suite for Foundation Model Evaluation
Yeonkyoung So, Jongmin Kim, Sungmok Jung +13
We present a Korean Benchmark Suite (KBS) comprising Ko-ARC, Ko-GSM8K, Ko-EQ-Bench, Ko-WinoGrande, Ko-LAMBADA, and Ko-IFEval, covering six capabilities across 9,396 items. The suit…
Polar: A Benchmark for Evaluating Political Bias in LLMs
Sangho Kim, Heejin Kim, Yoonhee Park +2
Political bias in large language models (LLMs) is increasingly significant, but difficult to measure reproducibly across political and linguistic contexts. We introduce Polar, a 4,…
Thunder-KoNUBench: A Corpus-Aligned Benchmark for Korean Negation Understanding
Sungmok Jung, Yeonkyoung So, Joonhak Lee +3
Although negation is known to challenge large language models (LLMs), benchmarks for evaluating negation understanding-especially in Korean-are scarce. We conduct a corpus-based an…
Ko-MuSR: A Multistep Soft Reasoning Benchmark for LLMs Capable of Understanding Korean
Chanwoo Park, Suyoung Park, JiA Kang +6
We present Ko-MuSR, the first benchmark to comprehensively evaluate multistep, soft reasoning in long Korean narratives while minimizing data contamination. Built following MuSR, K…
Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding
Yeonkyoung So, Gyuseong Lee, Sungmok Jung +4
Negation is a fundamental linguistic phenomenon that poses ongoing challenges for Large Language Models (LLMs), particularly in tasks requiring deep semantic understanding. Current…