---
title: "Who cites Neural Machine Translation with Byte-Level…"
description: "88 papers of the Elamur Research library cite «Neural Machine Translation with Byte-Level Subwords», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/wang-2019-neural-machine-translation-byte-level/cited-by/"
---
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# Who cites «Neural Machine Translation with Byte-Level Subwords»

88 papers of our library cite it (of the 140,884 whose bibliographies we read) · 10 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/wang-2019-neural-machine-translation-byte-level/)

1. [**Qwen3 Technical Report**An Yang, Anfeng Li, Baosong Yang, et al.*2025 · 3,276 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen3-technical-report/)
2. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
3. [**Surface Form Competition: Why the Highest Probability Answer Isn't Always Right**Ari Holtzman, Peter West, Vered Shwartz, et al.*2021 · 271 citations*](https://md.research.elamur.ai/free/en/papers/holtzman-2021-surface-form-competition-why-highest/)
4. [**Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq**Changhan Wang, Yun Tang, Xutai Ma, et al.*2020 · 259 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-fairseq-s2t-fast-speech-text/)
5. [**mGPT: Few-Shot Learners Go Multilingual**Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.*2022 · 203 citations*](https://md.research.elamur.ai/free/en/papers/shliazhko-2022-mgpt-few-shot-learners-go/)
6. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
7. [**Tokenizer Choice For LLM Training: Negligible or Crucial?**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 102 citations*](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/)
8. [**Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP**Sabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, et al.*2021 · 89 citations*](https://md.research.elamur.ai/free/en/papers/mielke-2021-between-words-characters-brief-history/)
9. [**MoVoC: Morphology-Aware Subword Construction for Ge'ez Script Languages**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2025-movoc-morphology-aware-subword-construction/)
10. [**MoVoC: Morphology-Aware Subword Construction for Geez Script Languages**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2025-movoc-morphology-aware-subword-construction-geez/)

78 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/wang-2019-neural-machine-translation-byte-level/) — Neural Machine Translation with Byte-Level Subwords