5 citations · 9 across the 18 of their papers we have counts for
6 papers · 1 filter
LLM-as-an-Interviewer: Beyond Static Testing Through Dynamic LLM Evaluation
Eunsu Kim, Juyoung Suk, Seungone Kim +3
We introduce LLM-as-an-Interviewer, a novel paradigm for evaluating large language models (LLMs). This approach leverages multi-turn interactions where the LLM interviewer actively…
Uncovering Factor Level Preferences to Improve Human-Model Alignment
Juhyun Oh, Eunsu Kim, Jiseon Kim +4
Large language models (LLMs) often exhibit tendencies that diverge from human preferences, such as favoring certain writing styles or producing overly verbose outputs. While crucia…
BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
Junho Myung, Nayeon Lee, Yi Zhou +19
Large language models (LLMs) often lack culture-specific knowledge of daily life, especially across diverse regions and non-English languages. Existing benchmarks for evaluating LL…
CLIcK: A Benchmark Dataset of Cultural and Linguistic Intelligence in Korean
Eunsu Kim, Juyoung Suk, Philhoon Oh +3
Despite the rapid development of large language models (LLMs) for the Korean language, there remains an obvious lack of benchmark datasets that test the requisite Korean cultural a…
The Generative AI Paradox on Evaluation: What It Can Solve, It May Not Evaluate
Juhyun Oh, Eunsu Kim, Inha Cha +1
This paper explores the assumption that Large Language Models (LLMs) skilled in generation tasks are equally adept as evaluators. We assess the performance of three LLMs and one op…
Multi-FAct: Assessing Factuality of Multilingual LLMs using FActScore
Sheikh Shafayat, Eunsu Kim, Juhyun Oh +1
Evaluating the factuality of long-form large language model (LLM)-generated text is an important challenge. Recently there has been a surge of interest in factuality evaluation for…