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Hi, dear, author, really thanks for sharing the result of this paper, it is an exciting work. I click this github page many times everyday to see if the code is updated.... I am confusing about Adaptive Embedding Aggregation Fusion module, in formula 13, as my understanding, Q is fixed embedding, it is one dimensional, K is reshaped into two dimensional, then how can them multiply together?
The text was updated successfully, but these errors were encountered:
As described in our paper, the dimensions of K and V are (D, T×F), while Q can be interpreted as (1, D), resulting in a final output shape of (1, D). We utilized nn.MultiheadAttention for this operation. Code updates will be made available once our paper is received.
As described in our paper, the dimensions of K and V are (D, T×F), while Q can be interpreted as (1, D), resulting in a final output shape of (1, D). We utilized nn.MultiheadAttention for this operation. Code updates will be made available once our paper is received.
Hi, dear, author, really thanks for sharing the result of this paper, it is an exciting work. I click this github page many times everyday to see if the code is updated.... I am confusing about Adaptive Embedding Aggregation Fusion module, in formula 13, as my understanding, Q is fixed embedding, it is one dimensional, K is reshaped into two dimensional, then how can them multiply together?
The text was updated successfully, but these errors were encountered: