Zihao Jin — accepted AI-conference papers

2026

GEMA-Score: Granular Explainable Multi-Agent Scoring Framework for Radiology Report Evaluation

Zhenxuan Zhang, KinHei Lee, Peiyuan Jing, Weihang Deng, Huichi Zhou, Zihao Jin +5

AAAI 2026technical

Automatic medical report generation has the potential to support clinical diagnosis, reduce the workload of radiologists, and demonstrate potential for enhancing diagnostic consistency. However, current evaluation metrics often fail to reflect the clinical reliability of generated reports. Overlap-b

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2025

Cyclic Vision-Language Manipulator: Towards Reliable and Fine-Grained Image Interpretation for Automated Report Generation

Yingying Fang, Zihao Jin, Shaojie Guo, Jinda Liu, Zhiling Yue, Yijian Gao +4

IJCAI 2025

Despite significant advancements in automated report generation, the opaqueness of text interpretability continues to cast doubt on the reliability of the content produced. This paper introduces a novel approach to identify specific image features in X-ray images that influence the outputs of report

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