6 papers
MELON: A Large-Scale Dataset for Multi-Event Text-to-Long-Video Retrieval
Chan Hur, SeungWoo Song, Jeong-hun Hong +3
Existing text-video retrieval datasets primarily consist of short-form clips containing a single dominant event. While suitable for measuring basic vision-language alignment, they…
Hidden Threat in Synthetic Data: Covert Targeted Bias Injection through Benign Text
Minkyung Cho, Jihyo Kim, SeungWoo Song +4
Synthetic data is increasingly used to train large language models (LLMs), yet its security implications remain poorly understood. Prior work on subliminal learning suggests that m…
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…
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…
BOK-VQA: Bilingual outside Knowledge-Based Visual Question Answering via Graph Representation Pretraining
Minjun Kim, Seungwoo Song, Youhan Lee +2
The current research direction in generative models, such as the recently developed GPT4, aims to find relevant knowledge information for multimodal and multilingual inputs to prov…