activity
20242026
most citedMultimodal Clinical Trial Outcome Prediction with Large Language Models

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Why Are GUI Agents Correct but Late? Decode on the Decision-Time Critical Path, Tested with Pre-Compiled Policy Trees

Zihan Dong, Rui Qian, Qishi Zhan +3

Computer-use agents often fail on transient GUI events because they produce the correct action only after the relevant window has already closed. We identify the main cause as expe…

cs.CV2026

Self-Supervised Contrastive Learning for Cardiac MR Sequence Classification

Yuli Wang, Hyewon Jung, Dongshen Peng +10

Vision Transformer (ViT) models, utilizing self-attention mechanisms, have demonstrated robust generalization capabilities across various vision tasks, including image classificati…

cs.AI2026★ 1 cited

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

Dongshen Peng, Yi Wang, Austin Schoeffler +5

Large language models (LLMs) deployed in clinical decision support may acquiesce to patient requests for care that conflicts with evidence-based guidelines. We developed SycoEval-E…

stat.AP2025

Large-scale spatial variable gene atlas for spatial transcriptomics

Jiawen Chen, Jinwei Zhang, Dongshen Peng +4

Spatial variable genes (SVGs) reveal critical information about tissue architecture, cellular interactions, and disease microenvironments. As spatial transcriptomics (ST) technolog…

cs.LG2024★ 3 cited

Multimodal Clinical Trial Outcome Prediction with Large Language Models

Wenhao Zheng, Liaoyaqi Wang, Dongshen Peng +5

The clinical trial is a pivotal and costly process, often spanning multiple years and requiring substantial financial resources. Therefore, the development of clinical trial outcom…