Byteification retrofits token-based LLMs to work at byte level, fixing letter-counting failures
PontiEdoardo · x · 2026-10-12
Most LLMs can't reliably reason about individual letters—think the classic "how many r's in strawberry"—because words are encoded as opaque tokens.
Writing in Nature, Minixhofer et al. introduce byteification, a technique that retrofits existing token-based LLMs to operate at the byte level, giving them direct access to character information. A News & Views piece by Peking University's Zhao Zhang and Yingfei Xiong notes the retrofitted models can now correctly count the 'i's in "artificial intelligence."
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