4 citations · 8 across the 12 of their papers we have counts for
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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…
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…
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…
VTOS: Learning to Orchestrate Vision Tools by Co-Searching Solutions and Observers
Jinchao Ge, Lingqiao Liu, Shuwen Zhao +1
Vision foundation tools such as open-vocabulary detectors, segmentation models, and post-processing operators are powerful building blocks for computer vision, but their effectiven…