collaborators

7 papers

cs.CL2025

ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks

Yinghao Zhu, Junyi Gao, Zixiang Wang +9

Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility in non-generative clinical prediction, often presumed inferior to specialized models, rem…

cs.CV2025

SuperGS: Consistent and Detailed 3D Super-Resolution Scene Reconstruction via Gaussian Splatting

Shiyun Xie, Zhiru Wang, Yinghao Zhu +3

Recently, 3D Gaussian Splatting (3DGS) has excelled in novel view synthesis (NVS) with its real-time rendering capabilities and superior quality. However, it encounters challenges…

cs.LG2025

ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

Zixiang Wang, Yinghao Zhu, Huiya Zhao +9

We introduce ColaCare, a framework that enhances Electronic Health Record (EHR) modeling through multi-agent collaboration driven by Large Language Models (LLMs). Our approach seam…

cs.CL2025

EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation

Yinghao Zhu, Changyu Ren, Zixiang Wang +7

The integration of multimodal Electronic Health Records (EHR) data has significantly advanced clinical predictive capabilities. Existing models, which utilize clinical notes and mu…

cs.LG2025

PRISM: Mitigating EHR Data Sparsity via Learning from Missing Feature Calibrated Prototype Patient Representations

Yinghao Zhu, Zixiang Wang, Long He +4

Electronic Health Records (EHRs) contain a wealth of patient data; however, the sparsity of EHRs data often presents significant challenges for predictive modeling. Conventional im…

cs.CV2025

AGFSync: Leveraging AI-Generated Feedback for Preference Optimization in Text-to-Image Generation

Jingkun An, Yinghao Zhu, Zongjian Li +6

Text-to-Image (T2I) diffusion models have achieved remarkable success in image generation. Despite their progress, challenges remain in both prompt-following ability, image quality…