Elamur Research⌕
☰
home / papers / Canine: Pre-training an Efficient… / cited by

Who cites «Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation»

156 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

  1. How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language ModelsPhillip Rust, Jonas Pfeiffer, Ivan Vulić, et al.2021 · 444 citations
  2. Challenges and Applications of Large Language ModelsJean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 300 citations
  3. XTREME-R: Towards More Challenging and Nuanced Multilingual EvaluationSebastian Ruder, Noah Constant, Jan Botha, et al.2021 · 277 citations
  4. Charformer: Fast Character Transformers via Gradient-based Subword TokenizationYi Tay, Vinh Q. Tran, Sebastian Ruder, et al.2021 · 179 citations
  5. Lifting the Curse of Multilinguality by Pre-training Modular TransformersJonas Pfeiffer, Naman Goyal, Xi Victoria Lin, et al.2022 · 172 citations
  6. Language Model Tokenizers Introduce Unfairness Between LanguagesAleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.2023 · 149 citations
  7. Fanar: An Arabic-Centric Multimodal Generative AI PlatformFanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
  8. Tokenizer Choice For LLM Training: Negligible or Crucial?Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.2024 · 102 citations
  9. Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLPSabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, et al.2021 · 89 citations
  10. Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language UnderstandingAbbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.2022 · 9 citations
  11. Explicit Morphological Knowledge Improves Pre-training of Language Models for HebrewEylon Gueta, Omer Goldman, Reut Tsarfaty2023 · 7 citations
  12. Expanding the Lexicon of Ge'ez Based African Languages: A Comparative Study of Amharic and TigrinyaHailay Kidu Teklehaymanot, Debela Desalegn Yadeta, Wolfgang Nejdl2026
  13. The Impact of Tokenization Algorithms on Hungarian Language Model PerformanceMátyás Osváth, Máté Norbert Molnár, Roland Gunics, et al.2026

143 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/clark-2022-canine-pre-training-efficient-tokenization/cited-by/