Low Resource Neural Machine Translation

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

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

24 shown of 24 papers with code (69 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.

• Revisiting Low-Resource Neural Machine Translation: A Case Study
  28 May 2019 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of…
• A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala
  3 Dec 2024 1 repository listed
  This paper presents a multi-way parallel English-Tamil-Sinhala corpus annotated with Named Entities (NEs), where Sinhala and Tamil are low-resource languages.
• From Priest to Doctor: Domain Adaptaion for Low-Resource Neural Machine Translation
  1 Dec 2024 1 repository listed
  Many of the world's languages have insufficient data to train high-performing general neural machine translation (NMT) models, let alone domain-specific models, and often the only available parallel data are small…
• Low-resource neural machine translation with morphological modeling
  3 Apr 2024 1 repository listed
  An attention augmentation scheme to the transformer model is proposed in a generic form to allow integration of pre-trained language models and also facilitate modeling of word order relationships between the source and…
• Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair Variables
  24 Jul 2023 1 repository listed
  Despite the tremendous success of Neural Machine Translation (NMT), its performance on low-resource language pairs still remains subpar, partly due to the limited ability to handle previously unseen inputs, i.
• ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation
  8 Dec 2022 1 repository listed
  In this paper, we propose a novel transfer learning method for NMT, namely ConsistTL, which can continuously transfer knowledge from the parent model during the training of the child model.
• Low-resource Neural Machine Translation with Cross-modal Alignment
  13 Oct 2022 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  How to achieve neural machine translation with limited parallel data?
• Low-Resource Neural Machine Translation: A Case Study of Cantonese
  1 Oct 2022 1 repository listed
  The development of Natural Language Processing (NLP) applications for Cantonese, a language with over 85 million speakers, is lagging compared to other languages with a similar number of speakers.
• On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation
  7 Sep 2022 1 repository listed Syntology ran 1 of 13 samples · 12 unverified
  Pre-Training (PT) of text representations has been successfully applied to low-resource Neural Machine Translation (NMT).
• On the Interaction of Regularization Factors in Low-resource Neural Machine Translation
  1 Jun 2022 1 repository listed
  We explore the roles and interactions of the hyper-parameters governing regularization, and propose a range of values applicable to low-resource neural machine translation.
• Linguistically-driven Multi-task Pre-training for Low-resource Neural Machine Translation
  20 Jan 2022 1 repository listed
  In the present study, we propose novel sequence-to-sequence pre-training objectives for low-resource machine translation (NMT): Japanese-specific sequence to sequence (JASS) for language pairs involving Japanese as the…
• Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
  8 Sep 2021 1 repository listed
  Many DA approaches aim at expanding the support of the empirical data distribution by generating new sentence pairs that contain infrequent words, thus making it closer to the true data distribution of parallel…
• Cultural and Geographical Influences on Image Translatability of Words across Languages
  1 Jun 2021 1 repository listed
  We find that images of words are not always invariant across languages, and that language pairs with shared culture, meaning having either a common language family, ethnicity or religion, have improved image…
• Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation
  3 Mar 2021 1 repository listed
  Meta-learning has been sufficiently validated to be beneficial for low-resource neural machine translation (NMT).
• Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task
  12 Aug 2020 1 repository listed
  Chinese word segmentation has entered the deep learning era which greatly reduces the hassle of feature engineering.
• Language Model Prior for Low-Resource Neural Machine Translation
  30 Apr 2020 1 repository listed Syntology ran 0 of 6 samples · 6 unverified
  A common solution is to exploit the knowledge of language models (LM) trained on abundant monolingual data.
• Low Resource Neural Machine Translation: A Benchmark for Five African Languages
  31 Mar 2020 1 repository listed
  Recent advents in Neural Machine Translation (NMT) have shown improvements in low-resource language (LRL) translation tasks.
• Improving Back-Translation with Uncertainty-based Confidence Estimation
  31 Aug 2019 1 repository listed
  While back-translation is simple and effective in exploiting abundant monolingual corpora to improve low-resource neural machine translation (NMT), the synthetic bilingual corpora generated by NMT models trained on…
• Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation
  6 Jul 2019 1 repository listed
  This paper proposes a novel multilingual multistage fine-tuning approach for low-resource neural machine translation (NMT), taking a challenging Japanese--Russian pair for benchmarking.
• Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies
  14 May 2019 1 repository listed
  Transfer learning or multilingual model is essential for low-resource neural machine translation (NMT), but the applicability is limited to cognate languages by sharing their vocabularies.
• Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation
  2 Nov 2018 1 repository listed
  We aim to better exploit the limited amounts of parallel text available in low-resource settings by introducing a differentiable reconstruction loss for neural machine translation (NMT).
• Improving Low-Resource Neural Machine Translation with Filtered Pseudo-Parallel Corpus
  1 Nov 2017 1 repository listed
  Large-scale parallel corpora are indispensable to train highly accurate machine translators.
• Data Augmentation for Low-Resource Neural Machine Translation
  1 May 2017 1 repository listed
  The quality of a Neural Machine Translation system depends substantially on the availability of sizable parallel corpora.
• Transfer Learning for Low-Resource Neural Machine Translation
  8 Apr 2016 1 repository listed
  Ensembling and unknown word replacement add another 2 Bleu which brings the NMT performance on low-resource machine translation close to a strong syntax based machine translation (SBMT) system, exceeding its performance…

Syntology lines on 4 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.