---
title: "Who cites Efficient and Effective Vocabulary — 26 citing papers"
description: "26 papers of the Elamur Research library cite «Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models»…"
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---
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# Who cites «Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models»

26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models»](https://md.research.elamur.ai/free/en/papers/kim-2024-efficient-effective-vocabulary-expansion-towards/)

1. [**HyperCLOVA X Technical Report arXiv:2404.01954**Kang Min Yoo, Jaegeun Han, Sookyo In, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/yoo-2024-hyperclova-x-technical-report/)
2. [**LLM-as-a-Judge & Reward Model: What They Can and Cannot Do arXiv:2409.11239**Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/son-2024-llm-judge-reward-model-they/)
3. [**Sailor: Open Language Models for South-East Asia arXiv:2404.03608**Longxu Dou, Qian Liu, Guangtao Zeng, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/dou-2024-sailor-open-language-models-south/)
4. **[Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2024-developing-pragmatic-benchmark-assessing-korean/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yeeun Kim, Youngrok Choi, Eunkyung Choi, et al.*2024 · 24 citations*
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. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
7. **[ACSE: An Ancient Character Semantic-Aware Embedding for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-acse-ancient-character-semantic-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhihan Zhou, Daqian Shi, Lida Shi, et al.*2026*
8. **[ELO: Efficient Layer-Specific Optimization for Continual Pretraining of Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/yoo-2026-elo-efficient-layer-specific-optimization/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hangyeol Yoo, ChangSu Choi, Minjun Kim, et al.*2026*
9. [**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/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/kim-2024-efficient-effective-vocabulary-expansion-towards/) — Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models