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Keyword: machine translation ×Clear all

6 claims from 3 papers

1. Computer Science › Natural Language Processing Techniques

   Attention Is All You Need

   Vaswani, Shazeer, Parmar et al. · 2025

   The paper proposes the Transformer, a network built only on attention mechanisms, and reports better translation quality and shorter training times than leading recurrent or convolutional models.

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   1. UncheckedThe Transformer model scored 28.4 BLEU on WMT 2014 English-to-German translation, over 2 BLEU above earlier best results, including ensembles.“Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU.”
   2. UncheckedOn WMT 2014 English-to-French translation, the Transformer reports a single-model BLEU of 41.8 after 3.5 days on eight GPUs, at a fraction of rivals' training cost.“On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature.”
   3. UncheckedThe paper reports that the Transformer, a model built only on attention, also worked well on English constituency parsing, with large and with limited training data.“We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.”

2. Computer Science › Topic Modeling

   BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

   Lewis, Liu, Goyal et al. · Annual Meeting of the Association for Computational Linguistics (ACL) · 2020

   The paper presents BART, a denoising sequence-to-sequence pretraining model, tests different text-corruption methods, and reports results on generation, comprehension and translation tasks.

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   1. UncheckedBART matches RoBERTa on GLUE and SQuAD with similar training resources, and sets new best results on several generation tasks, by up to 6 ROUGE.“It matches the performance of RoBERTa with comparable training resources on GLUE and SQuAD, achieves new state-of-the-art results on a range of abstractive dialogue, question answering, and summarization tasks, with gains of up to 6 ROUGE.”
   2. UncheckedBART is reported to beat a back-translation machine translation system by 1.1 BLEU points while pretraining only on the target language.“BART also provides a 1.1 BLEU increase over a back-translation system for machine translation, with only target language pretraining.”

3. Computer Science › Topic Modeling

   A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets

   Laskar, Bari, Rahman, Bhuiyan, Joty and Huang · arXiv (Cornell University) · 2023

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   1. Unchecked“We also report a new emergent ability to follow multi-query instructions that we mostly found in ChatGPT and other instruction-tuned models.”