In the paper, at training time, it appears that you treat embeddings as a vectors of real numbers which is used to calculate cosine similarity and also as vectors of complex numbers which is used to calculate the angle between the two vectors to measure similarity. At inference time, what similarity metric should I use measure semantic similarity?
In the paper, at training time, it appears that you treat embeddings as a vectors of real numbers which is used to calculate cosine similarity and also as vectors of complex numbers which is used to calculate the angle between the two vectors to measure similarity. At inference time, what similarity metric should I use measure semantic similarity?