Language models typically tokenize text into subwords, using a deterministic, hand-
engineered heuristic of combining characters into longer surface-level strings such as' ing'or …

The development of neural machine translation has achieved a good translation effect on
large-scale general corpora, but there are still many problems in the translation of low …

Tokenization is widely used in large language models because it significantly improves
performance. However, tokenization imposes several disadvantages, such as performance …

Subword tokenization is a common method for vocabulary building in Neural Machine
Translation (NMT) models. However, increasingly complex tasks have revealed its …

In natural language processing, much current research focuses on training larger and larger
models on more and more data. In this thesis, we argue that how data is represented can …

Abstract The rise of Artificial Intelligence technology has raised concerns about the potential
compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes …

NLP models have grown as a powerful technology and impact our social life like never
before, along with rising concerns in practical applications including privacy invasion and …