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20232026
most citedA Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis

4 citations · 9 across the 12 of their papers we have counts for

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cs.CV2026

Graph-Supervised Hierarchical Clinical Alignment for Radiology Report Generation with Large Language Models

Yingshu Li, Yunyi Liu, Zhanyu Wang +4

Radiology report generation (RRG) has recently benefited from large language models, which substantially improve report fluency. However, clinically faithful generation remains cha…

cs.CV2026

DRRG: A Discrete Diffusion Framework for Radiology Report Generation

Shaoyang Zhoua, Yingshu Li, Yunyi Liu +4

Purpose: Automatic radiology report generation (RRG) has been widely explored to improve reporting accuracy and reduce radiologists' workload. Most existing methods rely on autoreg…

cs.CV2026

Seeing What Matters: Lesion-Aware High-Resolution Patch Discovery and Fusion for Chest X-ray Report Generation

Yingshu Li, Yunyi Liu, Zhenghao Chen +5

Despite rapid advances in chest X-ray (CXR) foundation models, most radiology report generation (RRG) systems still rely on heavily downsampled inputs (e.g., 256x256) due to the fi…

cs.CV2025

A Review of Longitudinal Radiology Report Generation: Dataset Composition, Methods, and Performance Evaluation

Shaoyang Zhou, Yingshu Li, Yunyi Liu +3

Chest Xray imaging is a widely used diagnostic tool in modern medicine, and its high utilization creates substantial workloads for radiologists. To alleviate this burden, vision la…

cs.CV2025

S-RRG-Bench: Structured Radiology Report Generation with Fine-Grained Evaluation Framework

Yingshu Li, Yunyi Liu, Zhanyu Wang +4

Radiology report generation (RRG) for diagnostic images, such as chest X-rays, plays a pivotal role in both clinical practice and AI. Traditional free-text reports suffer from redu…

cs.CV2024

Attention-driven GUI Grounding: Leveraging Pretrained Multimodal Large Language Models without Fine-Tuning

Hai-Ming Xu, Qi Chen, Lei Wang +1

Recent advancements in Multimodal Large Language Models (MLLMs) have generated significant interest in their ability to autonomously interact with and interpret Graphical User Inte…

cs.CV2024

KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models

Yingshu Li, Zhanyu Wang, Yunyi Liu +3

Harnessing the robust capabilities of Large Language Models (LLMs) for narrative generation, logical reasoning, and common-sense knowledge integration, this study delves into utili…

cs.CV2023★ 4 cited

A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis

Yingshu Li, Yunyi Liu, Zhanyu Wang +7

This work conducts an evaluation of GPT-4V's multimodal capability for medical image analysis, with a focus on three representative tasks of radiology report generation, medical vi…

cs.CV2023★ 1 cited

R2GenGPT: Radiology Report Generation with Frozen LLMs

Zhanyu Wang, Lingqiao Liu, Lei Wang +1

Large Language Models (LLMs) have consistently showcased remarkable generalization capabilities when applied to various language tasks. Nonetheless, harnessing the full potential o…