most citedMulti-Modal Foundation Models for Computational Pathology: A Survey

3 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2026

ColdDDI: Evaluating Knowledge Utilization in Cold-Start Drug-Drug Interaction Prediction

Jiheng Liang, Chen Zhao, Di Wu +4

Cold-start drug-drug interaction (DDI) prediction tests whether models can identify clinically significant interactions for drugs without training-time interaction history. Existin…

q-bio.GN2026★ 1 cited

Histopathology-centered Computational Evolution of Spatial Omics: Integration, Mapping, and Foundation Models

Ninghui Hao, Xinxing Yang, Boshen Yan +7

Spatial omics (SO) technologies enable spatially resolved molecular profiling, while hematoxylin and eosin (H&E) imaging remains the gold standard for morphological assessment in c…

cs.LG2025

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools

Minh-Hao Van, Prateek Verma, Chen Zhao +1

Foundation models (FMs) are catalyzing a transformative shift in materials science (MatSci) by enabling scalable, general-purpose, and multimodal AI systems for scientific discover…

cs.CV2025★ 3 cited

Multi-Modal Foundation Models for Computational Pathology: A Survey

Dong Li, Guihong Wan, Xintao Wu +7

Foundation models have emerged as a powerful paradigm in computational pathology (CPath), enabling scalable and generalizable analysis of histopathological images. While early deve…

cs.CV2025

A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks

Dong Li, Guihong Wan, Xintao Wu +6

Computational pathology foundation models (CPathFMs) have emerged as a powerful approach for analyzing histopathological data, leveraging self-supervised learning to extract robust…