Author

Yi-Jie Zhu

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Preprint Sep 2026

Computationally Efficient Pathology Segmentation using Knowledge Distillation from Foundation Models

Distillation consistently improves student performance over supervised training alone, producing state-of-the-art or near state-of-the-art results with substantially fewer parameters and up to ten-fold higher inference throughput than foundation-model-based segmentation networks.

Jia-Qi Lv, Yi-Jie Zhu, Saki Okada et al. · 0 citations