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cs.CV2026
Beyond Attention Heatmaps: How to Get Better Explanations for Multiple Instance Learning Models in Histopathology
Mina Jamshidi Idaji, Julius Hense, Tom Neuhäuser +12
Multiple instance learning (MIL) has enabled substantial progress in computational histopathology, where a large amount of patches from gigapixel whole slide images are aggregated…
cs.CV2026
Attentive multilayer fusion for vision transformers
Laure Ciernik, Marco Morik, Lukas Thede +4
With the rise of large-scale foundation models, efficiently adapting them to downstream tasks remains a central challenge. Linear probing, which freezes the backbone and trains a l…
cs.CV2024
Objective drives the consistency of representational similarity across datasets
Laure Ciernik, Lorenz Linhardt, Marco Morik +3
The Platonic Representation Hypothesis claims that recent foundation models are converging to a shared representation space as a function of their downstream task performance, irre…