collaborators

13 papers

cs.AI2026

Democratizing and accelerating AI-driven pathology research through agentic intelligence

Jiabo Ma, Cheng Jin, Yihui Wang +19

Computational pathology has advanced rapidly with the emergence of foundation models, yet widespread adoption remains limited by substantial technical complexity and programming re…

cs.LG2026

Spatial Transcriptomics-Guided Alignment Enhances Molecular Profiling in Pathology Foundation Model

Fengtao Zhou, Yingxue Xu, Zhengyu Zhang +20

Comprehensive molecular profiling is essential for modern precision oncology but remains hindered by prohibitive costs, specimen exhaustion, and protracted turnaround times. While…

cs.CV2026

A Breast Vision Pathology Foundation Model for Real-world Clinical Utility

Yingxue Xu, Zhengyu Zhang, Xiuming Zhang +32

Pathology foundation models have shown strong retrospective performance, but whether such systems can support clinically relevant use remains unclear. This challenge is particularl…

cs.CV2026

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

Yu Cai, Cheng Jin, Jiabo Ma +25

Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image analysis. Here, we present LitePath, a dep…

cs.LG2026

Investigating Data Pruning for Pretraining Biological Foundation Models at Scale

Yifan Wu, Jiyue Jiang, Xichen Ye +9

Biological foundation models (BioFMs), pretrained on large-scale biological sequences, have recently shown strong potential in providing meaningful representations for diverse down…

eess.IV2025

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model

Zhe Xu, Ziyi Liu, Junlin Hou +13

Multimodal large language models (MLLMs) have emerged as powerful tools for computational pathology, offering unprecedented opportunities to integrate pathological images with lang…