106 datasets found

The LDC 2002 English-Chinese dataset is used for testing the proposed approach.

The WMT 2016 English-German dataset is used for testing the proposed approach.

The WMT 2014 English-French dataset is used for testing the proposed approach.

The proposed approach is tested on English-German, English-French and Chinese-to-English translation tasks.

The dataset contains 160K sentence pairs for German-English translation.

The dataset contains 20M sentence pairs for Chinese-English translation.

Bleu: a method for automatic evaluation of machine translation.

The IWSLT 2014 German-to-English dataset is a machine translation dataset, containing 153K sentence pairs.

The dataset used for multilingual neural machine translation.

The dataset used for ImageNet-2012 and multilingual neural machine translation.

The WMT En-De, WMT En-Fr, and WMT En-Ro translation tasks.

The Workshop of Machine Translation 2018 dataset is used to train the text machine translation models.

The dataset used in the paper is WMT 2014 English-German dataset, which is a machine translation dataset.

The dataset is used for machine translation, text summarization, and open-ended text generation tasks.

The dataset is used for machine translation, text summarization, and open-ended text generation tasks.

High-quality human translations from books, leveraging the induction bias that high-quality human translations are superior to machine-generated translations.

High-quality human translations from books, leveraging the induction bias that high-quality human translations are superior to machine-generated translations.

High-quality human translations from books, leveraging the induction bias that high-quality human translations are superior to machine-generated translations.

The M-MMLU dataset is a multilingual dataset for machine translation.

The CMMLU dataset is a multilingual dataset for machine translation.