Token Propagation

Token propagation is a technique used to improve the efficiency and performance of various models, primarily focusing on reducing computational complexity while preserving crucial information. Current research centers on applying this to Vision Transformers (ViTs), employing methods like graph-based propagation and controlled token reduction to optimize inference speed and accuracy in image processing tasks. This approach also finds application in other domains, such as autonomous driving, where propagating state information through a transformer network enhances model robustness and performance. The overall goal is to develop more efficient and effective models across diverse applications by strategically managing the flow of information within the network.