Author

D. Rueckert

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Preprint Aug 2026

Big, Bright, or Invisible: A Frozen-Feature Benchmark of 3D CT Foundation Models

Through controlled within-organ comparisons, it is empirically demonstrate that widespread or high-contrast abnormalities, such as devices and effusions, are reliably recovered and small, low-contrast focal lesions remain a persistent challenge across all evaluated encoders.

Maulik Chevli, Johannes Brandt, R. Braren et al. · 0 citations

#machine learning Preprint Sep 2026

Memorisation bias in medical AI

It is shown that predictions on a patient's unseen future data can change significantly if a model observed that same patient's anonymised historical data during training, a phenomenon known as memorisation bias, which exists across diverse data modalities and model architectures, and over prolonged time spans.

Moritz A. Knolle, M. Menten, Laurin Lux et al. · 0 citations

#natural language process... Preprint Aug 2026

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching

Continuous depth batching (CDB) is introduced, which schedules at the granularity of individual loop iterations, and handles boundary stages and loop steps in separate priority queues, makes exit decisions one step ahead, and overlaps all scheduling work with GPU computation.

Kristian Schwethelm, D. Rueckert, G. Kaissis · 0 citations