2 citations · 3 across the 11 of their papers we have counts for
7 papers · 1 filter
Which Language Should a Skeleton Speak? Language Choices in Multilingual Reasoning
HyeonSeok Lim, SeungWoo Song, Inho Won +3
Skeleton-based reasoning prompting is a promising training-free approach for structuring LLM reasoning, but prior work largely assumes an English-centric setting. We propose the La…
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…
Solar Open 2 Technical Report
Sungrae Park, Sanghoon Kim, Gyoungjin Gim +50
We present Solar Open 2, a 250B-A15B Mixture-of-Experts language model built for long-horizon agentic tasks, scaled up from Solar Open 1 (Solar Open 100B). To hold entire agent tra…
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.…
MentalBench: A DSM-Grounded Benchmark for Evaluating Psychiatric Diagnostic Capability of Large Language Models
Hoyun Song, Migyeong Kang, Jisu Shin +7
Large language models (LLMs) have attracted growing interest as supportive tools for psychiatric assessment and clinical decision support. However, existing mental health benchmark…
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)…