🔗 Who cites «Efficiently Adapting Pretrained Language Models To New Languages»

20 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Efficiently Adapting Pretrained Language Models To New Languages»

1. Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction CapabilitiesShaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.2024 · 15 citations
2. How Can We Effectively Expand the Vocabulary of LLMs with 0.01GB of Target Language Text?Computational LinguisticsAtsuki Yamaguchi, Aline Villavicencio, Nikolaos Aletras2026 · 11 citations
3. Teaching Old Tokenizers New Words: Efficient Tokenizer Adaptation for Pretrained ModelsFindings of the Association for Computational LinguisticsTaido Purason, Pavel Chizhov, Ivan P. Yamshchikov, et al.2026 · 4 citations
4. Kuwain 1.5B: An Arabic SLM via Language InjectionarXiv:2504.15120Khalil Hennara, Sara Chrouf, Mohamed Motaism Hamed, et al.2025 · 4 citations
5. MERLIN: Multi-Stage Curriculum Alignment for Multilingual Encoder-LLM Integration in Cross-Lingual ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Kosei Uemura, David Guzmán, Quang Phuoc Nguyen, et al.2026 · 1 citation
6. Building Patient Journeys in Hebrew: A Language Model for Clinical Timeline ExtractionKai Golan Hashiloni, Brenda Kasabe Nokai, Michal Shevach, et al.2025

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

This page in Markdown → https://md.research.elamur.ai/free/en/papers/csaki-2023-efficiently-adapting-pretrained-language-models/cited-by/