in NLP academic paper, would it be okay to refer the "token embeddings" as "tokens"? I am writing a paper in Natural Language Processing (NLP), and I just have a quick question about terminology.

In language models like Transformers, "token" refers to individual word in a text sequence, whereas there is a special term "token embedding" to refer to the embedding that results after token gets passed through the initial embedding layer.

Would it be problematic if I just refer a "token embedding" as a "token"? 

(e.g. "interaction between hidden embeddings and token embeddings" ---> "interaction between hidden embeddings and tokens")

I am trying to accommodate the different terminologies, but my sentences are getting really wordy...

Thank you,
At least to me, it would sound strange, as I would understand tokens as the discrete textual units they are, not their assigned vectors.

I would suggest that you don't try to force nonstandard simplifications. Just say what you want, in a technically accurate way, preferably using short sentences to avoid making it difficult for the reader to follow your discourse.