6 papers
NOLLI: A Difficulty-Calibrated Puzzle Benchmark for Diagnosing the English-Korean Performance Gap
Dasol Choi, Joonyong Park, Daegon Yu +3
We introduce NOLLI, a procedurally generated English-Korean puzzle benchmark designed to diagnose where Korean performance gaps arise. It comprises 15 puzzle types (25 tasks; 7,500…
MATHENA: Mamba-based Architectural Tooth Hierarchical Estimator and Holistic Evaluation Network for Anatomy
Kyeonghun Kim, Jaehyung Park, Youngung Han +17
Dental diagnosis from Orthopantomograms (OPGs) requires coordination of tooth detection, caries segmentation (CarSeg), anomaly detection (AD), and dental developmental staging (DDS…
MAESIL: Masked Autoencoder for Enhanced Self-supervised Medical Image Learning
Kyeonghun Kim, Hyeonseok Jung, Youngung Han +14
Training deep learning models for three-dimensional (3D) medical imaging, such as Computed Tomography (CT), is fundamentally challenged by the scarcity of labeled data. While pre-t…
Redefining Evaluation Standards: A Unified Framework for Evaluating the Korean Capabilities of Language Models
Hanwool Lee, Dasol Choi, Sooyong Kim +6
Recent advancements in Korean large language models (LLMs) have driven numerous benchmarks and evaluation methods, yet inconsistent protocols cause up to 10 p.p performance gaps ac…
Empowering Multimodal Respiratory Sound Classification with Counterfactual Adversarial Debiasing for Out-of-Distribution Robustness
Heejoon Koo, Miika Toikkanen, Yoon Tae Kim +2
Multimodal respiratory sound classification offers promise for early pulmonary disease detection by integrating bioacoustic signals with patient metadata. Nevertheless, current app…
MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
Soo Yong Kim, Suin Cho, Vincent-Daniel Yun +1
Bridging clinical diagnostic reasoning with AI remains a central challenge in medical imaging. We introduce MedCLM, an automated pipeline that converts detection datasets into larg…