7 citations · 8 across the 3 of their papers we have counts for
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cs.CV2026
Robustifying pathology foundation models via fine-tuning
Alexandre Filiot, Oskar Thaeter, Benoit Schmauch +1
Pathology foundation models (FMs) produce powerful tile-level representations which remain sensitive to scanner and staining variability, undermining deployment across laboratories…
cs.CV2024★ 1 cited
CARMIL: Context-Aware Regularization on Multiple Instance Learning models for Whole Slide Images
Thiziri Nait Saada, Valentina Di Proietto, Benoit Schmauch +2
Multiple Instance Learning (MIL) models have proven effective for cancer prognosis from Whole Slide Images. However, the original MIL formulation incorrectly assumes the patches of…