4 citations · 14 across the 18 of their papers we have counts for
6 papers · 1 filter
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…