5 papers
Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation
Vladimir Arkhipkin, Vladimir Korviakov, Nikolai Gerasimenko +22
This report introduces Kandinsky 5.0, a family of state-of-the-art foundation models for high-resolution image and 10-second video synthesis. The framework comprises three core lin…
Decentralized Optimization with Coupled Constraints
Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev +3
We consider the decentralized minimization of a separable objective , where the variables are coupled through an affine constraint $\sum_{i=1}^n\left(\math…
Curvature-Aligned Probing for Local Loss-Landscape Stabilization
Nikita Kiselev, Andrey Grabovoy
Local loss-landscape stabilization under sample growth is typically measured either pointwise or through isotropic averaging in the full parameter space. Despite practical value, b…
Closing the Curvature Gap: Full Transformer Hessians
Egor Petrov, Nikita Kiselev, Vladislav Meshkov +1
The optimization landscape of Transformer models remains poorly understood despite their widespread adoption. While recent studies have derived curvature properties for isolated se…
Unraveling the Hessian: A Key to Smooth Convergence in Loss Function Landscapes
Nikita Kiselev, Andrey Grabovoy
The loss landscape of neural networks is a critical aspect of their training, and understanding its properties is essential for improving their performance. In this paper, we inves…