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Ask a Language Model for Lottery Numbers: Concentration in Repeated Six-of-49 Outputs

arXiv 2610.00052 ↗First posted 4 Sep 2026cs.IR cs.AI cs.CLcited by 0

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Abstract (arXiv)

We evaluate six language-model configurations on requests for six distinct random integers from 1-49. Across 1,200 attempted calls using four English prompt variants, 1,184 responses yielded valid tickets. Effective diversity of number frequencies ranged from 9.9 to 18.0, compared with simulated fifth-percentile thresholds of 46.6-46.7 under independent uniform six-of-49 sampling at the corresponding sample sizes. Systems produced 8-93 distinct unordered tickets, and their modal tickets accounted for 22.5-68.0% of valid responses. Two archived Polish Lotto samples provided a physical-lottery comparison, with effective diversities of 41.1 and 41.4 at smaller sample sizes. These results demonstrate substantial concentration under the tested deployment settings. They do not identify its mechanism or establish performance under other prompts, temperatures, or tool configurations.

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References · 4

  1. 2024Non-Determinism of "Deterministic" LLM Settingscited by 84
  2. 2024Heads, Tails, and AI Fails: LLMs, Randomness, and Human Judgmentscited by 23
  3. 2026Where Does the Noise Come From? A Variance-Components Decomposition of Non-Determinism in LLM Brand Answerscited by 3
  4. 2026The Dice Roll Method: A Standardized Protocol for Repeated-Query Auditing of Large Language Model Brand Recommendationscited by 2

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