Browse State-of-the-Art › NMT
NMT
523 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 523 papers with code (1,773 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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17 Aug 2015 44 repositories listed Syntology ran 2 of 8 samples · 6 unverified · 2 pointer-only (licence)Our ensemble model using different attention architectures has established a new state-of-the-art result in the WMT'15 English to German translation task with 25.
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26 Sep 2016 28 repositories listed Syntology ran 23 of 46 samples · 23 unverified · 12 pointer-only (licence)To improve parallelism and therefore decrease training time, our attention mechanism connects the bottom layer of the decoder to the top layer of the encoder.
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31 Aug 2015 26 repositories listed Syntology ran 21 of 30 samples · 9 unverified · 21 pointer-only (licence)Neural machine translation (NMT) models typically operate with a fixed vocabulary, but translation is an open-vocabulary problem.
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15 Dec 2017 16 repositories listedWritten in Python and built on MXNet, the toolkit offers scalable training and inference for the three most prominent encoder-decoder architectures: attentional recurrent neural networks, self-attentional transformers,…
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20 Apr 2018 14 repositories listedMachine translation systems achieve near human-level performance on some languages, yet their effectiveness strongly relies on the availability of large amounts of parallel sentences, which hinders their applicability…
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11 Mar 2017 12 repositories listed Syntology ran 1 of 9 samples · 8 unverifiedNeural Machine Translation (NMT) has shown remarkable progress over the past few years with production systems now being deployed to end-users.
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28 May 2018 9 repositories listed Syntology ran 2 of 29 samples · 27 unverifiedOpenNMT is an open-source toolkit for neural machine translation (NMT).
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29 Jul 2019 8 repositories listed Syntology ran 3 of 17 samples · 14 unverified · 1 pointer-only (licence)We present Joey NMT, a minimalist neural machine translation toolkit based on PyTorch that is specifically designed for novices.
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3 Jul 2020 6 repositories listedWhile BERT is an effective method for learning monolingual sentence embeddings for semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019), BERT based cross-lingual sentence embeddings…
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31 Oct 2019 6 repositories listed Syntology ran 5 of 10 samples · 5 unverified · 3 pointer-only (licence)Instead, we evaluate MLMs out of the box via their pseudo-log-likelihood scores (PLLs), which are computed by masking tokens one by one.
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19 Sep 2018 6 repositories listedAlthough end-to-end neural text-to-speech (TTS) methods (such as Tacotron2) are proposed and achieve state-of-the-art performance, they still suffer from two problems: 1) low efficiency during training and inference; 2)…
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4 Aug 2018 6 repositories listed Syntology ran 0 of 3 samples · 3 unverifiedThe ability to generate natural language sequences from source code snippets has a variety of applications such as code summarization, documentation, and retrieval.
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20 Jun 2017 6 repositories listedThis paper introduces THUMT, an open-source toolkit for neural machine translation (NMT) developed by the Natural Language Processing Group at Tsinghua University.
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25 Jun 2016 6 repositories listed Syntology ran 0 of 2 samples · 2 unverifiedWe demonstrate that standard knowledge distillation applied to word-level prediction can be effective for NMT, and also introduce two novel sequence-level versions of knowledge distillation that further improve…
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30 Oct 2014 5 repositories listedOur experiments on the WMT14 English to French translation task show that this method provides a substantial improvement of up to 2.
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18 Aug 2020 4 repositories listed Syntology ran 6 of 9 samples · 3 unverifiedWe explore the application of very deep Transformer models for Neural Machine Translation (NMT).
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17 Jun 2017 4 repositories listedIn this paper, we present Neural Phrase-based Machine Translation (NPMT).
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10 Jan 2017 4 repositories listed Syntology ran 0 of 1 samples · 1 unverifiedWe describe an open-source toolkit for neural machine translation (NMT).
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17 Oct 2022 3 repositories listedMeanwhile we inject two types of perturbations into the retrieved pairs for robust training.
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7 Sep 2021 3 repositories listedWe present IndicBART, a multilingual, sequence-to-sequence pre-trained model focusing on 11 Indic languages and English.
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27 May 2021 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)On four benchmark machine translation datasets, we demonstrate that the proposed method is able to effectively filter out the noises in retrieval results and significantly outperforms the vanilla kNN-MT model.
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24 Apr 2020 3 repositories listed Syntology ran 2 of 13 samples · 11 unverifiedMassively multilingual models for neural machine translation (NMT) are theoretically attractive, but often underperform bilingual models and deliver poor zero-shot translations.
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18 Apr 2020 3 repositories listed Syntology ran 1 of 3 samples · 2 unverifiedWe find that alignments created from embeddings are superior for four and comparable for two language pairs compared to those produced by traditional statistical aligners, even with abundant parallel data; e.
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17 Feb 2020 3 repositories listedWhile BERT is more commonly used as fine-tuning instead of contextual embedding for downstream language understanding tasks, in NMT, our preliminary exploration of using BERT as contextual embedding is better than using…
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10 Nov 2019 3 repositories listedTo evaluate the quality of the mined bitexts, we train NMT systems for most of the language pairs and evaluate them on TED, WMT and WAT test sets.
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4 Sep 2018 3 repositories listedWhile modern machine translation has relied on large parallel corpora, a recent line of work has managed to train Neural Machine Translation (NMT) systems from monolingual corpora only (Artetxe et al., 2018c; Lample et…
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19 Aug 2018 3 repositories listedWe perform a validation experiment of NMT on English-Japanese machine translation, and find that it is possible to achieve comparable accuracy to direct subword training from raw sentences.
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23 Jun 2018 3 repositories listedEvaluating on adversarial examples has become a standard procedure to measure robustness of deep learning models.
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6 Nov 2017 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)Character-based neural machine translation (NMT) models alleviate out-of-vocabulary issues, learn morphology, and move us closer to completely end-to-end translation systems.
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15 Mar 2017 3 repositories listed Syntology ran 0 of 6 samples · 6 unverifiedDuring training, both the dynamic discriminator and the static BLEU objective are employed to evaluate the generated sentences and feedback the evaluations to guide the learning of the generator.
Syntology lines on 16 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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