--- title: "Who cites Language Model Tokenizers Introduce Unfairness…" description: "149 papers of the Elamur Research library cite «Language Model Tokenizers Introduce Unfairness Between Languages», found in their bibliographies; the…" canonical: "https://research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Language Model Tokenizers Introduce Unfairness…](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/) / cited by # Who cites «Language Model Tokenizers Introduce Unfairness Between Languages» 149 papers of our library cite it (of the 140,884 whose bibliographies we read) · 13 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/) 1. [**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/) 2. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/) 3. [**Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/) 4. [**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/) 5. [**Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-adapting-llms-hebrew-unveiling-dictalm/) 6. [**How well can LLMs Grade Essays in Arabic?**Rayed Ghazawi, Edwin Simpson*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/ghazawi-2025-well-llms-grade-essays-arabic/) 7. [**HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing**Arnon Turetzky, Or Tal, Yael Segal-Feldman, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/turetzky-2024-hebdb-weakly-supervised-dataset-hebrew/) 8. [**Do Diacritics Matter? Evaluating the Impact of Arabic Diacritics on Tokenization and LLM Benchmarks**Go Inoue, Bashar Alhafni, Nizar Habash, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2026-do-diacritics-matter-evaluating-impact/) 9. [**Morphemes Without Borders: Evaluating Root-Pattern Morphology in Arabic Tokenizers and LLMs**Yara Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alakeel-2026-morphemes-borders-evaluating-root-pattern/) 10. [**Morphemes without Borders: Evaluating Root–Pattern Morphology in Arabic Tokenizers and LLMs**Yara Yousif Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alakeel-2026-morphemes-without-borders-evaluating-root/) 11. [**Bringing Mapudungun into the Modern MT Ecosystem: Morphology-Aware Tokenization for NLLB-200 Fine-Tuning**Isaac Thompson, Brandon Rogers, Eric Ringger*2026*](https://md.research.elamur.ai/free/en/papers/thompson-2026-bringing-mapudungun-into-modern-mt/) 12. [**Expanding the Lexicon of Ge'ez Based African Languages: A Comparative Study of Amharic and Tigrinya**Hailay Kidu Teklehaymanot, Debela Desalegn Yadeta, Wolfgang Nejdl*2026*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2026-expanding-lexicon-ge-ez-based/) 13. [**LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2026*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2026-lgse-lexically-grounded-subword-embedding/) 136 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/) — Language Model Tokenizers Introduce Unfairness Between Languages