mlsanityData to 7 Oct 2026

Constructing a BPE Tokenization DFA

arXiv 2405.07671 ↗First posted 13 May 2024cs.FL cs.CL cs.LGcited by 5

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Abstract (arXiv)

Many natural language processing systems operate over tokenizations of text to address the open-vocabulary problem. In this paper, we give and analyze an algorithm for the efficient construction of deterministic finite automata (DFA) designed to operate directly on tokenizations produced by the popular byte pair encoding (BPE) technique. This makes it possible to apply many existing techniques and algorithms to the tokenized case, such as pattern matching, equivalence checking of tokenization dictionaries, and composing tokenized languages in various ways. The construction preserves some key properties of the automaton, and we use this to establish asymptotic bounds on the state complexity of the automata that result. Finally, we demonstrate how to construct an input-deterministic (subsequential) string-to-string transducer which precisely describes the relationship between strings and their correct tokenizations.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 3 of its 14 references that are in the map. First posted on arXiv 13 May 2024.

Builds on

3 of 14 references.

References · 3

  1. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,898
  2. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,973
  3. 2024Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detectioncited by 27

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 2.

5 papers.