Recent advances in Vision-Language Models (VLMs) have led to rapid progress in video understanding across a wide range of benchmark tasks. However, existing evaluations largely focus on short-term reasoning, failing to assess a critical capability: maintaining cumulative temporal consistency over extended time horizons...
Leon D. Mayer, Lucas Luttner, P. Godau et al.· 0 citations
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise more transferable and data-efficient solutions, but existing approaches are limited in scale, evaluated narrowly, and often assume that a s...
C. U. Harsy, Tassilo Wald, Karol Gotkowski et al.· 0 citations
The authors' analysis identifies temporal modeling as the architectural factor most consistently associated with generalization to the unseen center, although the effect is not uniform across metrics in the controlled baseline comparison, and both parameter-efficient baselines remain more costly than a constant predict...
Max Kirchner, Hanna Hoffmann, Alexander C. Jenke et al.· Medical Image Analysis· 1 citation
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