4 papers
When Context Flips, Safety Breaks: Diagnosing Brittle Safety in Aligned Language Models
Dasol Choi, Alex Kwon
Safety benchmark scores provide incomplete evidence of deployment readiness: aligned language models often adhere to rigid rules even when a situational update flips which action i…
XL-SafetyBench: A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity
Dasol Choi, Eugenia Kim, Jaewon Noh +14
Current LLM safety benchmarks are predominantly English-centric and often rely on translation, failing to capture country-specific harms. Moreover, they rarely evaluate a model's a…
No Language Data Left Behind: A Comparative Study of CJK Language Datasets in the Hugging Face Ecosystem
Dasol Choi, Woomyoung Park, Youngsook Song
Recent advances in Natural Language Processing (NLP) have underscored the crucial role of high-quality datasets in building large language models (LLMs). However, while extensive r…
Better Safe Than Sorry? Overreaction Problem of Vision Language Models in Visual Emergency Recognition
Dasol Choi, Seunghyun Lee, Youngsook Song
Vision-Language Models (VLMs) have shown capabilities in interpreting visual content, but their reliability in safety-critical scenarios remains insufficiently explored. We introdu…