4 citations · 14 across the 18 of their papers we have counts for
18 papers
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…
Self-supervised restoration of singing voice degraded by pitch shifting using shallow diffusion
Yunyi Liu, Taketo Akama
Pitch shifting has been an essential feature in singing voice production. However, conventional signal processing approaches exhibit well known trade offs such as formant shifts an…
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…
Text2Move: Text-to-moving sound generation via trajectory prediction and temporal alignment
Yunyi Liu, Shaofan Yang, Kai Li +1
Human auditory perception is shaped by moving sound sources in 3D space, yet prior work in generative sound modelling has largely been restricted to mono signals or static spatial…
RadReason: Radiology Report Evaluation Metric with Reasons and Sub-Scores
Yingshu Li, Yunyi Liu, Lingqiao Liu +2
Evaluating automatically generated radiology reports remains a fundamental challenge due to the lack of clinically grounded, interpretable, and fine-grained metrics. Existing metho…
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…
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels
Erjian Guo, Zhen Zhao, Zicheng Wang +3
Medical Visual Question Answering (Med-VQA) systems benefit the interpretation of medical images containing critical clinical information. However, the challenge of noisy labels an…
Simi-SFX: A similarity-based conditioning method for controllable sound effect synthesis
Yunyi Liu, Craig Jin
Generating sound effects with controllable variations is a challenging task, traditionally addressed using sophisticated physical models that require in-depth knowledge of signal p…
ReFINE: A Reward-Based Framework for Interpretable and Nuanced Evaluation of Radiology Report Generation
Yunyi Liu, Yingshu Li, Zhanyu Wang +4
Automated radiology report generation (R2Gen) has advanced significantly, introducing challenges in accurate evaluation due to its complexity. Traditional metrics often fall short…
Deep Learning-Based Fatigue Cracks Detection in Bridge Girders using Feature Pyramid Networks
Jiawei Zhang, Jun Li, Reachsak Ly +2
For structural health monitoring, continuous and automatic crack detection has been a challenging problem. This study is conducted to propose a framework of automatic crack segment…
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…
ICGAN: An implicit conditioning method for interpretable feature control of neural audio synthesis
Yunyi Liu, Craig Jin
Neural audio synthesis methods can achieve high-fidelity and realistic sound generation by utilizing deep generative models. Such models typically rely on external labels which are…
MRScore: Evaluating Radiology Report Generation with LLM-based Reward System
Yunyi Liu, Zhanyu Wang, Yingshu Li +4
In recent years, automated radiology report generation has experienced significant growth. This paper introduces MRScore, an automatic evaluation metric tailored for radiology repo…
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…
DDSP-SFX: Acoustically-guided sound effects generation with differentiable digital signal processing
Yunyi Liu, Craig Jin, David Gunawan
Controlling the variations of sound effects using neural audio synthesis models has been a difficult task. Differentiable digital signal processing (DDSP) provides a lightweight so…
Q2ATransformer: Improving Medical VQA via an Answer Querying Decoder
Yunyi Liu, Zhanyu Wang, Dong Xu +1
Medical Visual Question Answering (VQA) systems play a supporting role to understand clinic-relevant information carried by medical images. The questions to a medical image include…