<p>So, In this paper : <a href="https://arxiv.org/pdf/2004.07464.pdf" rel="nofollow noreferrer">https://arxiv.org/pdf/2004.07464.pdf</a>
They have combined image embedding and text embedding by concatenating them.</p>
<pre><code>X = TE + IE 
</code></pre>
<p>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 <a href="https://arxiv.org/abs/1708.03629" rel="nofollow noreferrer">https://arxiv.org/abs/1708.03629</a> (Implemented here : <a href="https://github.com/vyraun/Half-Size" rel="nofollow noreferrer">https://github.com/vyraun/Half-Size</a>)</p>
How combine word embedded vectors to one vector?
<p>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.</p>