4 citations · 6 across the 5 of their papers we have counts for
5 papers
Let's Scale Step by Step: Compute-Efficient Hyperparameter Transfer for Large-Scale Mixture-of-Experts
Nayeon Kim, Hojin Lee, Yunju Bak +2
Mixture-of-Experts (MoE) architectures significantly expand model capacity without a proportional increase in computational cost. However, optimizing their hyperparameters---partic…
Handling Korean Out-of-Vocabulary Words with Phoneme Representation Learning
Nayeon Kim, Eojin Jeon, Jun-Hyung Park +1
In this study, we introduce KOPL, a novel framework for handling Korean OOV words with Phoneme representation Learning. Our work is based on the linguistic property of Korean as a…
Polishing Every Facet of the GEM: Testing Linguistic Competence of LLMs and Humans in Korean
SungHo Kim, Nayeon Kim, Taehee Jeon +1
We introduce the , designed to assess the linguistic competence of LLMs and humans in K…
Kanana: Compute-efficient Bilingual Language Models
Kanana LLM Team, Yunju Bak, Hojin Lee +26
We introduce Kanana, a series of bilingual language models that demonstrate exceeding performance in Korean and competitive performance in English. The computational cost of Kanana…
Exploring the Impact of Corpus Diversity on Financial Pretrained Language Models
Jaeyoung Choe, Keonwoong Noh, Nayeon Kim +2
Over the past few years, various domain-specific pretrained language models (PLMs) have been proposed and have outperformed general-domain PLMs in specialized areas such as biomedi…