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Developing Language-Specific Models Using a Neural Architecture Search
2021
Applied Sciences
This paper applies the neural architecture search (NAS) method to Korean and English grammaticality judgment tasks. Based on the previous research, which only discusses the application of NAS on a Korean dataset, we extend the method to English grammatical tasks and compare the resulting two architectures from Korean and English. Since complex syntactic operations exist beneath the word order that is computed, the two different resulting architectures out of the automated NAS language modeling
doi:10.3390/app112110324
fatcat:q5gdfjd2tfeaxncsqmq6gtlnh4