Understanding Attention Mechanisms - Part 3: From Cosine Similarity to Dot Product

This article explores the mathematical calculations behind attention mechanisms, specifically the transition from cosine similarity to dot product for comparing encoder and decoder outputs.

Details

The article discusses the mathematical details of comparing encoder and decoder outputs in attention mechanisms. It starts by presenting sample output values from the LSTM cells in the encoder and decoder. The cosine similarity equation is then introduced to calculate the similarity between these outputs. To further simplify the calculation, the article explains that the dot product can be used instead, as it only requires the numerator and ignores the denominator scaling. This simplification works well when dealing with a fixed number of cells. The article concludes by mentioning that the dot product approach will be explored in more detail in the next article.