2 citations · 3 across the 6 of their papers we have counts for
6 papers
Semantic Hardness Is Not Visual Hardness: Sign-Aware Hard Negative Mining for Sign Language Retrieval
Junmyeong Lee, Chan Hur, ChangSu Choi +5
Sign Language Retrieval (SLRet) enables efficient access to sign language content but remains fragile in fine-grained scenarios where visually similar signs must be distinguished.…
ELO: Efficient Layer-Specific Optimization for Continual Pretraining of Multilingual LLMs
HanGyeol Yoo, ChangSu Choi, Minjun Kim +6
We propose an efficient layer-specific optimization (ELO) method designed to enhance continual pretraining (CP) for specific languages in multilingual large language models (MLLMs)…
KORMo: Korean Open Reasoning Model for Everyone
Minjun Kim, Hyeonseok Lim, Hangyeol Yoo +10
This work presents the first large-scale investigation into constructing a fully open bilingual large language model (LLM) for a non-English language, specifically Korean, trained…
MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation
ChangSu Choi, Hoyun Song, Dongyeon Kim +6
Distilling the tool-use capabilities of large language models (LLMs) into small language models (SLMs) is essential for their practical application. The predominant approach, super…
X-LLaVA: Optimizing Bilingual Large Vision-Language Alignment
Dongjae Shin, Hyeonseok Lim, Inho Won +6
The impressive development of large language models (LLMs) is expanding into the realm of large multimodal models (LMMs), which incorporate multiple types of data beyond text. Howe…
Optimizing Language Augmentation for Multilingual Large Language Models: A Case Study on Korean
ChangSu Choi, Yongbin Jeong, Seoyoon Park +11
Large language models (LLMs) use pretraining to predict the subsequent word; however, their expansion requires significant computing resources. Numerous big tech companies and rese…