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arXiv · 2606.14122

Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models

Sangwhan Moon·Daisuke Oba·Youmi Ma·Tatsuya Hiraoka·Naoaki Okazaki
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Abstract

Byte-level tokenization enables language models to handle any Unicode input, but models can generate invalid UTF-8 sequences when encountering rare or unseen characters. We investigate the relationship between training scale and UTF-8 generation reliability with a 355M parameter model trained on 80B tokens from a balanced multilingual corpus of English, Japanese, Korean, and Chinese. We introduce multiple evaluation protocols that isolate UTF-8 structural validity from language modeling. UTF-8 validity convergence lags perplexity by a roughly a factor of two: perplexity stabilizes after 2.1B tokens, but UTF-8 validity requires 4.2B tokens. In context-free generation, rare characters achieve higher structural validity than common characters, suggesting over-specialization of frequent character representations. Through experiments, we observed that reliable UTF-8 generation is a distinct capability requiring evaluation beyond perplexity.

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Sangwhan Moon, Daisuke Oba, Youmi Ma, Tatsuya Hiraoka, Naoaki Okazaki. 2026-06-12. Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models. https://arxiv.org/abs/2606.14122

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