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TMU NMT System with Japanese BART for the Patent task of WAT 2021
In this paper, we introduce our TMU Neural Machine Translation (NMT) system submitted for the Patent task (Korean Japanese and English Japanese) of 8th Workshop on Asian Translation (Nakazawa et al., 2021).
Korean-to-Japanese Neural Machine Translation System using Hanja Information
In this paper, we describe our TMU neural machine translation (NMT) system submitted for the Patent task (Korean→Japanese) of the 7th Workshop on Asian Translation (WAT 2020, Nakazawa et al., 2020).
A Single Linear Layer Yields Task-Adapted Low-Rank Matrices
To confirm this hypothesis, we devise a method named Conditionally Parameterized LoRA (CondLoRA) that updates initial weight matrices with low-rank matrices derived from a single linear layer.
Learning How to Translate North Korean through South Korean
Training a model using North Korean data is the most straightforward approach to solving this problem, but there is insufficient data to train NMT models.
Zero-shot North Korean to English Neural Machine Translation by Character Tokenization and Phoneme Decomposition
The primary limitation of North Korean to English translation is the lack of a parallel corpus; therefore, high translation accuracy cannot be achieved.
