공대생 도전 일지

Towards standardizing Korean Grammatical Error Correction:Datasets and Annotation

https://arxiv.org/abs/2210.14389 Towards standardizing Korean Grammatical Error Correction: Datasets and AnnotationResearch on Korean grammatical error correction (GEC) is limited, compared to other major languages such as English. We attribute this problematic circumstance to the lack of a carefully designed evaluation benchmark for Korean GEC. In this work, we collecarxiv.org acl 2023에 붙은 논문입니..

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

https://arxiv.org/abs/2306.05685 Judging LLM-as-a-Judge with MT-Bench and Chatbot ArenaEvaluating large language model (LLM) based chat assistants is challenging due to their broad capabilities and the inadequacy of existing benchmarks in measuring human preferences. To address this, we explore using strong LLMs as judges to evaluate these marxiv.org LLM을 평가자로 사용하면 개방형, 멀티턴 대화에서 인간 선호도를 비교적 정확하게..