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Formalizing BPE Tokenization

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arxiv 2309.08715 v1 pith:X2WS3YD5 submitted 2023-09-15 cs.FL

classification cs.FL
keywords tokenizationotherparticularamountbeyondbyteconsiderconstant
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we formalize practical byte pair encoding tokenization as it is used in large language models and other NLP systems, in particular we formally define and investigate the semantics of the SentencePiece and HuggingFace tokenizers, in particular how they relate to each other, depending on how the tokenization rules are constructed. Beyond this we consider how tokenization can be performed in an incremental fashion, as well as doing it left-to-right using an amount of memory constant in the length of the string, enabling e.g. using a finite state string-to-string transducer.

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents

    cs.CR 2025-10 reject novelty 6.0 of 10

    The paper claims prompt compression is a new attack surface, but the abstract's COMA attack never appears in the body and the body's SoftCom requires white-box access.

  2. A Survey of LLM $\times$ DATA

    cs.DB 2025-05 conditional novelty 5.0 of 10

    A comprehensive survey of the bidirectional links between LLMs and data management, organized as DATA4LLM and LLM4DATA with a new 'IaaS' data-quality framework.

  3. Tokenization Standards for Linguistic Integrity: Turkish as a Benchmark

    cs.CL 2025-02 conditional novelty 4.0 of 10

    In a four-tokenizer comparison on Turkish MMLU questions, the fraction of tokens that are valid Turkish words correlates with accuracy more strongly than the fraction of morphologically pure tokens.

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