6 papers
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Hyunjae Kim, Dain Kim, Pan Xiao +25
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by…
Benchmarking Direct Preference Optimization for Medical Large Vision-Language Models
Dain Kim, Jiwoo Lee, Jaehoon Yun +4
Large Vision-Language Models (LVLMs) hold significant promise for medical applications, yet their deployment is often constrained by insufficient alignment and reliability. While D…
SCRIPTMIND: Crime Script Inference and Cognitive Evaluation for LLM-based Social Engineering Scam Detection System
Heedou Kim, Changsik Kim, Sanghwa Shin +1
Social engineering scams increasingly employ personalized, multi-turn deception, exposing the limits of traditional detection methods. While Large Language Models (LLMs) show promi…
Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards
Jaehoon Yun, Jiwoong Sohn, Jungwoo Park +9
Large language models have shown promise in clinical decision making, but current approaches struggle to localize and correct errors at specific steps of the reasoning process. Thi…
Learning from Negative Samples in Biomedical Generative Entity Linking
Chanhwi Kim, Hyunjae Kim, Sihyeon Park +3
Generative models have become widely used in biomedical entity linking (BioEL) due to their excellent performance and efficient memory usage. However, these models are usually trai…
Augmenting Biomedical Named Entity Recognition with General-domain Resources
Yu Yin, Hyunjae Kim, Xiao Xiao +6
Training a neural network-based biomedical named entity recognition (BioNER) model usually requires extensive and costly human annotations. While several studies have employed mult…