mlsanityData to 14 Oct 2026

Token Complexity of Certifying Stochastic-Oracle Reliability

arXiv 2606.24074 ↗First posted 23 Jun 2026cs.CC cs.AI cs.FLcited by 2

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Abstract (arXiv)

Wang~citeWang2026 introduced the Stochastic-Oracle Turing Machine (SOTM) framework and defined token complexity as the minimum expected cost of interacting with a stochastic oracle needed to attain a specified solution quality for a task. This paper develops an analogous notion for certifying the reliability of a stochastic oracle on a given domain. Certification token complexity is the minimum expected token cost required, with controlled error probability, to distinguish oracles that meet a target reliability level from those that fall below a lower reliability threshold. We construct an SPRT-based certification SOTM that queries the oracle, computes binary correctness scores, and stops when the accumulated log-likelihood evidence crosses a decision threshold. The SOTM halts almost surely, satisfies the desired two-sided error guarantee over the reliability regions to be certified, and yields an explicit upper bound on certification token complexity in terms of the reliability thresholds, the error bound, and the expected per-turn token cost. We then establish a matching information-theoretic lower bound: even with adaptive queries, every error-bounded certification SOTM must incur the same leading-order expected token cost as the SPRT-based construction as the prescribed error bound tends to zero. Together, these bounds characterize the leading-order certification token complexity in the small-error regime.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 10 references that are in the map. First posted on arXiv 23 Jun 2026.

Builds on

3 of 10 references.

References · 3

  1. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
  2. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
  3. 2026Token Complexity Theory for AI-Augmented Computingcited by 3

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Citing papers per year: 2026: 2.

2 papers.