3 papers
cs.CV2026
MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models
Han Jang, Junhyeok Lee, Songsoo Kim +4
Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains underexplored. With the 21s…
cs.CL2026
Surrogate modeling for interpreting black-box LLMs in medical predictions
Changho Han, Songsoo Kim, Dong Won Kim +4
Large language models (LLMs), trained on vast datasets, encode extensive real-world knowledge within their parameters, yet their black-box nature obscures the mechanisms and extent…
cs.CL2025
A Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection
Songsoo Kim, Seungtae Lee, See Young Lee +3
Background: The positive predictive value (PPV) of large language model (LLM)-based proofreading for radiology reports is limited due to the low error prevalence. Purpose: To asses…