arxiv preprint – Simplifying Transformer Blocks

In this episode we discuss Simplifying Transformer Blocks
by Bobby He, Thomas Hofmann. The paper studies the possibility of simplifying standard transformer blocks without reducing training speed by experimenting with the removal of certain components such as skip connections and normalization layers. Using signal propagation theory along with empirical research, the authors justify modifications that allow for these simplifications. Their findings indicate that the streamlined transformer models match the performance and training speed of traditional transformers while offering increased training throughput and reduced parameter count.