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Finitely Verifiable Segmentation: Decidability for Every Tokenizer with a Finite-State Verifier

Nicklas Nidh\"ogg
Oct 2026
Natural Language Processing

Abstract

A segmentation policy assigns to each byte string at most one segmentation into tokens. Call it finitely verifiable when a finite automaton over marked strings, bytes paired with boundary bits, accepts exactly the policy's own segmentations. The automaton judges a proposed segmentation and need not compute one. The paper shows what that hypothesis buys. Four questions that practice settles by folklore become decidable, whether a window certifies a token boundary, whether the boundary gap is bounded, whether a mask keeps generation completable, and whether two policies are equivalent. The last three specialize limitedness, coaccessibility and the equivalence of single-valued transducers. The first refines the synchronizing cut of code theory, and two more ask whether a certified cut, or the cuts of an inventory, let each piece scan alone. The class sits strictly between the online-scannable policies and those with regular domains, and its inner frontier is Choffrut's and decidable in polynomial time. Markings are length-preserving, so the class is exactly the rational segmentation policies, a normal form rather than a restriction, and what the decisions need is a supplied verifier. The class is closed under the operations pipelines use: composition over a labeled stage, restriction, splitting, and byte-fallback union of literal policies. Each composite inherits the six decisions, and certificates transfer between stages under four laws. Under rational, unifilar, almost surely stopping finite-state sources, each mass of the weighted section is an exact rational, and so is each rate where expected length is positive. Maximal-munch lexing, canonical byte-pair encoding and two-mode WordPiece instantiate the interface, and the munch library implements all six decisions. Every theorem carries an executable check, and every reported statistic is a program's own output.

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