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This work trains small causal predictors on matched FineWeb-2 text and evaluates on FLORES-200 under UTF-8, UBE, and UBE's same-length big-endian variant, finding that UBE's mean error falls below UTF-8's final mean error after only 25% and 37.5% of training.
Byte-level byte-pair encoding (BBPE) tokenizers are attractive for multilingual large language models (LLMs) because they cover all Unicode text. In UTF-8-based BBPE, however, many scripts start from a higher fallback cost than English: when no learned merges can be applied, a multibyte character requires multiple byte...
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