Language Model, Transformers, Deep Learning, Artificial Intelligence, Machine Learning.
element-wise multiplication. Finally, the resulting values are multiplied with the query element-wise. Thus, it avoids the computationally heavy softmax(Q*K.t) of a Transformer. "AFT can be interpreted as performing implicit attention with as many heads as feature dimensions, where the attention