In this setting, we consider inference phase attacks when a small fraction of agents is compromised. The compromised agent either does not send embedded features to the FC or sends arbitrary embedded features.

Scientists and engineers have been working on approximating the governing PDEs of these physical systems for centuries. The emergence of the computer-aided simulation facilitates a cost-friendly way to study these challenging problems.

This novel framework is then extended to a hierarchical structure, where uncorrelated tokens at different stages are gradually removed, resulting in a considerable shrinkage of computational cost. We include extensive experiments on both image and video tasks, where our method could deliver up to 1.4

Using a compressor-based distance metric derived from Kolmogorov complexity, together with few labeled data, NPC-L V classifies without further training.