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How to use the embedding in natural language processing models to improve my PhD ?

I am working on a PhD in natural language processing, and I am interested in using word embeddings to improve the performance of my models. I have trained a word embedding model on a large corpus of text, but I am not sure how to use the embeddings to improve my models. Can you provide some guidance on how to use word embeddings in NLP tasks?

 

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