🔗 Who cites «Finding the Optimal Vocabulary Size for Neural Machine Translation»

54 papers of our library cite it (of the 140,884 whose bibliographies we read) · 4 with a page here, the most cited first · ← the paper

1. 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
2. Getting the most out of your tokenizer for pre-training and domain adaptationGautier Dagan, Gabriel Synnaeve, Baptiste Roziere2024 · 44 citations
3. Optimizing the Size of Subword Vocabularies in Dialect ClassificationVani Kanjirangat, Tanja Samardžić, Ljiljana Dolamic, et al.2023 · 11 citations
4. Bringing Mapudungun into the Modern MT Ecosystem: Morphology-Aware Tokenization for NLLB-200 Fine-TuningIsaac Thompson, Brandon Rogers, Eric Ringger2026

50 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/gowda-2020-finding-optimal-vocabulary-size-neural/cited-by/