Component-Weighted Centroid Search for Exact Incremental BPE
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Abstract (arXiv)
Exact incremental BPE maintains the canonical tokenization state after every appended byte. The recent algorithm of Jiang and Gong (2026) does this in O(log2 t) worst-case time, where t is the maximum canonical token length. Its centroid search visits O(log t) components and can pay another O(log t) for ordered point location at each one. Within Jiang and Gong's normalized/proper merge-stage model, we change only that local search. Each interval is weighted by the size of the recursive component it selects, so a move from size m to size m' costs O(1+log(m/m')). These charges telescope, giving O(log t) time per append and O(nlog t) over an n-byte stream, with the same BPE semantics and asymptotic space. We also construct a normalized proper BPE family over a fixed alphabet where count-balanced search uses Theta(log2 t) probes on a reachable update, while the weighted search uses Theta(log t). A Rust implementation matches the predicted probe counts on every tested instance. On ordinary vocabularies the queried degrees are small, however, and the improvement is a worst-case guarantee rather than an average-speed result.
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References · 4
- 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,898
- 2024Tokenization as Finite-State Transductioncited by 5
- 2026TokTier: Exact Stateful CPU+GPU Tokenization for Agentic LLM Servingcited by 2
- 2026Incremental BPE Tokenizationcited by 1
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