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MTet: Multi-domain Translation for English-Vietnamese

2022-03-02 · Blog 2022 3 · Chinh Ngo, Hieu Tran, Long Phan, Trieu H. Trinh, Hieu Nguyen, Minh Nguyen, Minh-Thang Luong

We are excited to introduce a new larger and better quality Machine Translation dataset, MTet, which stands for Multi-domain Translation for English and VieTnamese. In our new release, we extend our previous dataset (v1.0) by adding more high-quality English-Vietnamese sentence pairs on various domains. In addition, we also show our new larger Transformer models can achieve state-of-the-art results on multiple test sets.

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Code (1)

vietai/mTet tf

Tasks

Machine TranslationSentenceTranslation

Methods 이 논문이 사용한 방법론

Attention 설명 없음
Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…
BPE Byte Pair Encoding, or BPE, is a subword segmentation algorithm that encodes rare and unknown words as sequences of subword units. The intuition is that various word…
Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
Position-Wise Feed-Forward Layer 설명 없음
Residual Connection 설명 없음
Absolute Position Encodings Absolute Position Encodings are a type of position embeddings for [Transformer-based models] where positional encodings are…

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