P(Yes): 15$\times$ Improvements via Test-Time Scaling of Decision Models

Key points

• Decision models answer typed questions, such as multiple-choice or yes/no questions, with a probability for each option.1
• The search is done either by editing one answer at a time or by joint optimization, which changes several answers at once.1
• Search raises accuracy for every model and test set we tried, and the gains are largest for exact correctness on logic puzzles, where every answer in a task must be right.1
• On 128 such puzzles, it takes Qwen3.8-27B from 2 to 30 exactly correct puzzles ($15\times$) and its per-blank accuracy from 27.8% to 48.5%.1

Sources (1)

• [1]P(Yes): 15$\times$ Improvements via Test-Time Scaling of Decision Models
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 18, 07:01 PM

  We add test-time search to frozen decision models, with no training: we show the model a complete proposed answer, read off its probability of saying "Yes" to the proposal's correctness, and search for answers that it rates higher.

  Decision models answer typed questions, such as multiple-choice or yes/no questions, with a probability for each option.

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