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cs.CV2026
LogitDynamics: Reliable ViT Error Detection from Layerwise Logit Trajectories
Ido Beigelman, Moti Freiman
Reliable confidence estimation is critical when deploying vision models. We study error prediction: determining whether an image classifier's output is correct using only signals f…
cs.CV2025
PSA-MIL: A Probabilistic Spatial Attention-Based Multiple Instance Learning for Whole Slide Image Classification
Sharon Peled, Yosef E. Maruvka, Moti Freiman
Whole Slide Images (WSIs) are high-resolution digital scans widely used in medical diagnostics. WSI classification is typically approached using Multiple Instance Learning (MIL), w…
cs.CV2024★ 2 cited
CIMIL-CRC: a clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H\&E stained images
Hadar Hezi, Matan Gelber, Alexander Balabanov +2
Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) b…