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

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

collaborators

5 papers

q-bio.GN20261 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.CV2025

Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models

Zhixia He, Chen Zhao, Minglai Shao +5

Out-of-distribution (OOD) detection is committed to delineating the classification boundaries between in-distribution (ID) and OOD images. Recent advances in vision-language models…

cs.CV2025

Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains

Yumeng Lin, Dong Li, Xintao Wu +4

Ensuring fairness and robustness in machine learning models remains a challenge, particularly under domain shifts. We present Face4FairShifts, a large-scale facial image benchmark…

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.CV20253 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…