How combine word embedded vectors to one vector?

Question

I know the meaning and methods of word embedding(skip-gram, CBOW) completely. And I know, that Google has a word2vector API that by getting the word can produce the vector. but my problem is this: we have a clause that includes the subject, object, verb... that each word is previously embedded by the Google API, now "How we can combine these vectors together to create a vector that is equal to the clause?" Example: Clause: V= "dog bites man" after word embedding by the Google, we have V1, V2, V3 that each of them maps to the dog, bites, man. and we know that: V = V1+ V2 +V3 How can we provide V? I will appreciate if you explain it by taking an example of real vectors.

Answer 1

So, In this paper : https://arxiv.org/pdf/2004.07464.pdf They have combined image embedding and text embedding by concatenating them.

X = TE + IE 

Here X is fusion embedding with TE and IE as text and image embedding respectively. If your TE and IE have dimension of suppose 2048 each, your X will be of length 2*2024. Then maybe you can use this if possible or if you want to reduce the dimension you can use t-SNE/PCA or https://arxiv.org/abs/1708.03629 (Implemented here : https://github.com/vyraun/Half-Size)