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Multi-Round Transfer Learning for Low-Resource NMT Using Multiple High-Resource Languages
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Discussion on Bilingual Cognition in International Exchange Activities
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Joint Training for Pivot-Based Neural Machine Translation
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BBN’s low-resource machine translation for the LoReHLT 2016 evaluation
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Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks
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Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network
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Deep Residual Learning for Image Recognition
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Learning Transferable Architectures for Scalable Image Recognition
inferredcites →https://doi.org/10.1109/tnn.2010.2091281openalex-snapshot
Domain Adaptation via Transfer Component Analysis
inferredcites →https://doi.org/10.1145/3099556openalex-snapshot
Translating Low-Resource Languages by Vocabulary Adaptation from Close Counterparts
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Punctuation as Implicit Annotations for Chinese Word Segmentation
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Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
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Distant domain transfer learning
inferredcites →https://doi.org/10.1609/aaai.v32i1.11976openalex-snapshot
Zero-Resource Neural Machine Translation with Multi-Agent Communication Game
inferredcites →https://doi.org/10.18653/v1/d16-1026openalex-snapshot
Zero-Resource Translation with Multi-Lingual Neural Machine Translation
inferredcites →https://doi.org/10.18653/v1/d16-1163openalex-snapshot
Transfer Learning for Low-Resource Neural Machine Translation
inferredcites →https://doi.org/10.18653/v1/n16-1101openalex-snapshot
Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism
inferredcites →https://doi.org/10.18653/v1/p16-1185openalex-snapshot
Semi-Supervised Learning for Neural Machine Translation
inferredcites →https://doi.org/10.18653/v1/p17-1176openalex-snapshot
A Teacher-Student Framework for Zero-Resource Neural Machine Translation
inferredcites →https://doi.org/10.18653/v1/p17-2090openalex-snapshot
Data Augmentation for Low-Resource Neural Machine Translation
inferredcites →https://doi.org/10.24963/ijcai.2017/594openalex-snapshot
Maximum Expected Likelihood Estimation for Zero-resource Neural Machine Translation
inferredcites →https://doi.org/10.3115/1073445.1073462openalex-snapshot
Statistical phrase-based translation
inferredcites →https://doi.org/10.3115/1219840.1219873openalex-snapshot
A hierarchical phrase-based model for statistical machine translation
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Improving statistical MT through morphological analysis
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Learning-based named entity recognition for morphologically-rich, resource-scarce languages
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
inferredcites →https://doi.org/10.3115/v1/p15-1002openalex-snapshot
Addressing the Rare Word Problem in Neural Machine Translation
inferredcites →https://doi.org/10.3115/v1/p15-1166openalex-snapshot
Multi-Task Learning for Multiple Language Translation
inferredcites →https://doi.org/10.48550/arxiv.1409.3215openalex-snapshot
Sequence to Sequence Learning with Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1502.02791openalex-snapshot
Learning Transferable Features with Deep Adaptation Networks
inferredcites →https://doi.org/10.48550/arxiv.1609.08144openalex-snapshot
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
inferredcites →https://doi.org/10.48550/arxiv.1610.01108openalex-snapshot
Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions
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An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation
inferredcites →https://doi.org/10.48550/arxiv.1706.06415openalex-snapshot
THUMT: An Open Source Toolkit for Neural Machine Translation
inferredcites →https://doi.org/10.48550/arxiv.1708.09803openalex-snapshot
Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation
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The mathematics of statistical machine translation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Data augmentation for low‐resource languages NMT guided by constrained sampling
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Enhancing Low-Resource Minority Language Translation with LLMs and Retrieval-Augmented Generation for Cultural Nuances
inferred← citeshttps://doi.org/10.1007/s40747-025-01780-5openalex-snapshot
Research on morphological knowledge-guided low-resource agglutinative languages-Chinese translation
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Advances in machine transliteration methods, limitations, challenges, applications and future directions
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The 2020s political economy of machine translation
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Computational Approaches to Neural Machine Translation in Low-Resource Languages: A Bibliometric Review (2017–July 2025)
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Co-Evolution of Multilingual Word Vectors and Language Models
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A Survey of Multilingual Neural Machine Translation
inferred← citeshttps://doi.org/10.1145/3464427openalex-snapshot
Improving Data Augmentation for Low-Resource NMT Guided by POS-Tagging and Paraphrase Embedding
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Low-resource Neural Machine Translation: Methods and Trends
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Neural Machine Translation for Low-resource Languages: A Survey
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Filtering and Extended Vocabulary based Translation for Low-resource Language Pair of Sanskrit-Hindi
inferred← citeshttps://doi.org/10.1145/3639930openalex-snapshot
Multi-granularity Knowledge Sharing in Low-resource Neural Machine Translation
inferred← citeshttps://doi.org/10.1145/3665244openalex-snapshot
Neural Machine Translation for Low-Resource Languages from a Chinese-centric Perspective: A Survey
inferred← citeshttps://doi.org/10.1145/3837853openalex-snapshot
Enhancing Myanmar Sign Language Translation Through Transfer Learning, Self-training, and Error Correction
inferred← citeshttps://doi.org/10.18653/v1/2021.findings-acl.241openalex-snapshot
Two Parents, One Child: Dual Transfer for Low-Resource Neural Machine Translation
inferred← citeshttps://doi.org/10.18653/v1/2021.findings-emnlp.114openalex-snapshot
Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help?
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Temporal Domain Adaptation for Historical Irish
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Bridging Dialects: Enhancing Neural Machine Dialect Translation for Gujarati Language Through Model Adaptation
inferred← citeshttps://doi.org/10.26599/tst.2020.9010029openalex-snapshot
Enriching the transfer learning with pre-trained lexicon embedding for low-resource neural machine translation
inferred← citeshttps://doi.org/10.32657/10356/157475openalex-snapshot
Neural machine translation with limited resources
inferred← citeshttps://doi.org/10.3390/app112210860openalex-snapshot
Machine Translation in Low-Resource Languages by an Adversarial Neural Network
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Exploring the Effects of Data Volume and Transfer-Language Choice on Transfer Learning with Application to Polish
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Bridging the AI Language Divide: A Systematic Review of NMT and LLMs in Low-Resource Translation
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A Comprehensive Survey of Multilingual Neural Machine Translation
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