Jinge Wu — accepted AI-conference papers

2026

Error Correction in Radiology Reports: A Knowledge Distillation-Based Multi-Stage Framework

Jinge Wu, Zhaolong Wu, Ruizhe Li, Tong Chen, Abul Hasan, Yunsoo Kim +3

AAAI 2026technical

The increasing complexity and workload of clinical radiology leads to inevitable oversights and mistakes in their use as diagnostic tools, causing delayed treatments and sometimes life-threatening harm to patients. While large language models (LLMs) have shown remarkable progress in many tasks, thei

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2025

Look & Mark: Leveraging Radiologist Eye Fixations and Bounding boxes in Multimodal Large Language Models for Chest X-ray Report Generation

Yunsoo Kim, Jinge Wu, Su Hwan Kim, Pardeep Vasudev, Jiashu Shen, Honghan Wu

ACL 2025finding

Recent advancements in multimodal Large Language Models (LLMs) have significantly enhanced the automation of medical image analysis, particularly in generating radiology reports from chest X-rays (CXR). However, these models still suffer from hallucinations and clinically significant errors, limitin…

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