Rui Yang

Artefact and risk area detection of the tanDEM-X 30m edited DEM using an integrated machine learning and dem-of-difference framework: a case study in the Alps

Peijun Dong, Xingang Zhang, Yunfei Zhang, Rui Yang, Zeyu Hao

Verify, Repair, Repeat, or Stop? Robust Stopping for Noisy Verify-Repair Loops in LLM Agents

Yitao Wu, Si Shen, Rui Yang, Hong Peng, Bin Hu

Verify-repair loops are a standard means for large language model (LLM) agents to correct faulty plans in code generation, mathematical reasoning, and tool use. When both the verifier and the repairer are noisy, repair can damage already-correct plans, and reported acceptance kee…Read more

SIMAX: A Scalable and Interpretable Framework for Multi-Fidelity and Annotated Clinician-Patient Dialogue Simulation

Zhuhan Bao, Rui Yang, Bohao Yang, Zhiyi Liu, Sicheng Shu, Ruio Heerschap, et al.

Background. The widespread deployment of ambient digital scribes is driving large-scale capture of clinician-patient dialogues. Human coding of clinical communication data remains costly, inconsistent, and difficult to scale, motivating AI-driven communication coding systems. How…Read more

A Weakly Supervised Deep Learning Model and Human–Machine Fusion for Accurate Grading of Renal Cell Carcinoma from Histopathology Slides

Qingyuan Zheng, Rui Yang, Huazhen Xu, Junjie Fan, Panpan Jiao, Xinmiao Ni, et al.

(1) Background: The Fuhrman grading (FG) system is widely used in the management of clear cell renal cell carcinoma (ccRCC). However, it is affected by observer variability and irreproducibility in clinical practice. We aimed to use a deep learning multi-class model called SSL-CL…Read more