Author

Juergen Gall

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Preprint Sep 2026

Where Compute Matters: Heterogeneous Attention for Efficient Video Diffusion

Efficient video generation requires reducing the quadratic cost of self-attention over long spatio-temporal token sequences. Existing efficient-attention methods typically apply the same computation pattern to every token, even though denoising difficulty varies substantially across video regions and evolves throughout...

Olga Zatsarynna, Denis Korzhenkov, Juergen Gall et al. · 0 citations

Preprint Sep 2026

Generative Uncertainty as a Self-supervised Signal for Semantic Similarity Learning

A novel self-supervised approach that leverages generative uncertainty from text-to-video (T2V) diffusion models to learn semantic similarity without human annotations to identify stable semantic features within existing pretrained representations, such as VideoMAE and V-JEPA.

Enrico Pallotta, Sina Raoufi, Lars Doorenbos et al. · 0 citations

Preprint Aug 2026

Rethinking Expressivity and Efficiency in Test-Time Training

Under the standard approximation of taking gradients at the chunk-start weights, a closed-form state transition is derived that exactly reproduces the chunk-end fast-weight and momentum states of the per-token recurrence of Test-Time Training.

Zeyun Zhong, Joya Chen, Manuel Martín et al. · 2 citations