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A simple Galois Power-of-Two real time embedding scheme for performing Arabic morphology deep learning tasks
Egyptian Informatics Journal
This paper describes how a simple novel Galois Power-of-Two (GPOW2) real-time embedding scheme is used to improve the performance and accuracy of downstream NLP tasks. GPOW2 computes embeddings live on the fly (real time) in the context of target NLP tasks without the need for tabulated preembeddings. One excellent feature of the method is the ability to capture multilevel embeddings in the same pass. It simultaneously computes character, word and sentence embeddings on the fly. GPOW2 has beendoi:10.1016/j.eij.2020.03.002 fatcat:72tunevhcze7dm42fpeaa3zeby