LangMAP adapts UnigramLM for multilingual use to deliver language-specific tokenization from a shared vocabulary, boosting boundary alignment metrics across natural and programming languages with mixed downstream fine-tuning gains.
and Blevins, Terra and Goldfine, Nora and Steinert-Threlkeld, Shane
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cs.CL 2years
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UNVERDICTED 2representative citing papers
TokAlign++ learns token alignments between LLM vocabularies from monolingual representations to enable faster adaptation, better text compression, and effective token-level distillation across 15 languages with minimal steps.
citing papers explorer
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LangMAP: A Language-Adaptive Approach to Tokenization
LangMAP adapts UnigramLM for multilingual use to deliver language-specific tokenization from a shared vocabulary, boosting boundary alignment metrics across natural and programming languages with mixed downstream fine-tuning gains.
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TokAlign++: Advancing Vocabulary Adaptation via Better Token Alignment
TokAlign++ learns token alignments between LLM vocabularies from monolingual representations to enable faster adaptation, better text compression, and effective token-level distillation across 15 languages with minimal steps.