Author

Ming-Xi Fu

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Open access Oct 2026

Enhancing cervical squamous cell carcinoma diagnosis under distribution shift via domain-adaptive representation learning

Summary Automated whole-slide image (WSI) analysis for cervical squamous cell carcinoma (CSCC) is challenged by limited pathological specificity in general models and poor cross-center generalization. We propose CSCC-PAG (pre-training, adaptation, generalization), a framework integrating domain-specific pre-training wi...

Zi-Rui Huang, Yen-Chun Liu, Sai-Hui Jin et al. · iScience · 0 citations

Jul 2026

Pretraining Multiple Instance Learning Networks with Multi-Teacher Distillation from Pathology Slide Foundation Models

A distillation-based pretraining framework for MIL is proposed, which leverages two slide-level foundation models, TITAN and CARE, as teachers to transfer their representational knowledge into a diverse set of MIL architectures.

Ming-Xi Fu, Jiawen Li, Renao Yan et al. · arXiv.org · 0 citations

Jul 2026

ALICE: Learning a General-Purpose Pathology Foundation Model from Vision, Vision-Language, and Slide-Level Experts

This work presents ALICE, a unified foundation model trained through multi-stage agglomerative distillation that sequentially distills eight vision-only, vision-language, and slide-level teacher models into dedicated modules of a single backbone for broad computational pathology applications.

Jiawen Li, Tian Guan, Huijuan Shi et al. · arXiv.org · 0 citations