5 papers
PACE-RAG: Patient-Aware Contextual and Evidence-Constrained RAG for Clinical Drug Recommendation
Chaeyoung Huh, Hyunmin Hwang, Jung Hwan Shin +3
Drug recommendation requires a deep understanding of individual patient context, especially for complex conditions like Parkinson's disease. While LLMs possess broad medical knowle…
Adaptive Guidance for Retrieval-Augmented Masked Diffusion Models
Jaemin Kim, Jong Chul Ye
Retrieval-Augmented Generation (RAG) improves factual grounding by incorporating external knowledge into language model generation. However, when retrieved context is noisy, unreli…
UNICORN: Ultrasound Nakagami Imaging via Score Matching and Adaptation for Assessing Hepatic Steatosis
Kwanyoung Kim, Jaa-Yeon Lee, Youngjun Ko +2
Ultrasound imaging is an essential first-line tool for assessing hepatic steatosis. While conventional B-mode ultrasound imaging has limitations in providing detailed tissue charac…
PCPO: Proportionate Credit Policy Optimization for Aligning Image Generation Models
Jeongjae Lee, Jong Chul Ye
While reinforcement learning has advanced the alignment of text-to-image (T2I) models, state-of-the-art policy gradient methods are still hampered by training instability and high…
CellPainTR: Generalizable Representation Learning for Cross-Dataset Cell Painting Analysis
Cedric Caruzzo, Jong Chul Ye
Large-scale biological discovery requires integrating massive, heterogeneous datasets like those from the JUMP Cell Painting consortium, but technical batch effects and a lack of g…