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# Who cites «Leveraging Rule-Based Machine Translation Knowledge for Under-Resourced Neural Machine Translation Models»

7 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/torregrosa-2019-leveraging-rule-based-machine-translation/)

1. [Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation](https://arxiv.org/abs/2607.26286) *— 2026 · arXiv:2607.26286*
2. [PahGen: Generating Ancient Pahlavi Text via Grammar-guided Zero-shot Translation](https://aclanthology.org/2025.loresmt-1.16/) *— 2025 · Proceedings of the Eighth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2025)*
3. [A New Benchmark for Kalaallisut-Danish Neural Machine Translation](https://aclanthology.org/2024.americasnlp-1.7/) *— 2024 · Proceedings of the 4th Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP 2024)*
4. [A multi-source approach for Breton–French hybrid machine translation](https://aclanthology.org/2020.eamt-1.8/) *— 2020 · Proceedings of the 22nd Annual Conference of the European Association for Machine Translation*
5. [Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios](https://arxiv.org/abs/2009.13398) *— 2020 · arXiv:2009.13398*
6. li-2023-sign-language-recognition-translation-multi
7. puranik-2021-attentive-fine-tuning-transformers-translation
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