activity
20192026
most citedM4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation

10 citations · 18 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

GLINT: Sparsely Gated Vision-Language Alignment for Fine-Grained Radiology Representations

Jonggwon Park, Seongeun Lee, Junhyun Park +6

Vision-language models (VLMs) for radiology have emerged as a scalable paradigm by leveraging image-report pairs naturally produced in clinical workflows. However, this pairing rev…

cs.CV2025

RadZero: Similarity-Based Cross-Attention for Explainable Vision-Language Alignment in Chest X-ray with Zero-Shot Multi-Task Capability

Jonggwon Park, Byungmu Yoon, Soobum Kim +1

Recent advancements in multimodal models have significantly improved vision-language (VL) alignment in radiology. However, existing approaches struggle to effectively utilize compl…

cs.CV2025★ 1 cited

RA-RRG: Multimodal Retrieval-Augmented Radiology Report Generation with Key Phrase Extraction

Jonggwon Park, Byungmu Yoon, Soobum Kim +1

Automated radiology report generation (RRG) holds potential to reduce the workload of radiologists, and recent advances in multimodal large language models (MLLMs) have enabled mul…

cs.CV2024★ 10 cited

M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation

Jonggwon Park, Soobum Kim, Byungmu Yoon +2

The rapid evolution of artificial intelligence, especially in large language models (LLMs), has significantly impacted various domains, including healthcare. In chest X-ray (CXR) a…

cs.SD2019★ 7 cited

A Bi-directional Transformer for Musical Chord Recognition

Jonggwon Park, Kyoyun Choi, Sungwook Jeon +2

Chord recognition is an important task since chords are highly abstract and descriptive features of music. For effective chord recognition, it is essential to utilize relevant cont…