4 papers · 1 filter
Exploring the Effects of Alignment on Numerical Bias in Large Language Models
Ayako Sato, Hwichan Kim, Zhousi Chen +2
"LLM-as-a-judge," which utilizes large language models (LLMs) as evaluators, has proven effective in many evaluation tasks. However, evaluator LLMs exhibit numerical bias, a phenom…
Assessing the Capabilities of LLMs in Humor:A Multi-dimensional Analysis of Oogiri Generation and Evaluation
Ritsu Sakabe, Hwichan Kim, Tosho Hirasawa +1
Computational humor is a frontier for creating advanced and engaging natural language processing (NLP) applications, such as sophisticated dialogue systems. While previous studies…
Pruning Multilingual Large Language Models for Multilingual Inference
Hwichan Kim, Jun Suzuki, Tosho Hirasawa +1
Multilingual large language models (MLLMs), trained on multilingual balanced data, demonstrate better zero-shot learning performance in non-English languages compared to large lang…
Learning How to Translate North Korean through South Korean
Hwichan Kim, Sangwhan Moon, Naoaki Okazaki +1
South and North Korea both use the Korean language. However, Korean NLP research has focused on South Korean only, and existing NLP systems of the Korean language, such as neural m…