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Author

Daniel Z. Kaplan

2 papers indexed here

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Preprint Sep 2026

TT-VidT: Decoupling the Temporal Axis for Efficient Motion-Centric Video Pretraining

Comparisons in video self-supervised learning often evaluate complete training recipes rather than isolating the method itself: architecture, objective, data exposure, schedule, scale, and decoder capacity can all vary at once. This makes it hard to identify which choices yield motion-prioritized representations, whose...

Shih-Ying Yeh, Daniel Z. Kaplan, Xue-Hai Wang et al. · 0 citations

Scaling Vision Transformers for Functional MRI with Flat Maps

A new model family (CortexMAE) trained using the masked autoencoder framework is introduced, and in this setting the CortexMAE family outperforms prior models by a large margin, and the first open evaluation suite (Brainmarks) for fMRI foundation models is released.

Connor Lane, Mihir Tripathy, L. Murali et al. · 5 citations · ⚡1

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