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coherence_alpha_selection

coherence_alpha_selection

Select a coherence boosting alpha from cached validation likelihoods without model finetuning.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: coherence_alpha_selection description: Select a coherence boosting alpha from cached validation likelihoods without model finetuning.

Coherence Alpha Selection

Use this skill when validation examples contain full-context and premise-free candidate log likelihoods and labels. It implements the paper's one-pass validation-grid choice of alpha.

Inputs

  • Validation records with full_logprobs, short_logprobs, and label.
  • A numeric alpha grid.

Outputs

  • Best alpha, accuracy curve, and deterministic tie-breaking notes.

Workflow

  1. For each alpha, call the boosted scoring rule.
  2. Compute validation accuracy.
  3. Choose the highest accuracy; ties prefer the alpha with smaller absolute value, then smaller numeric value for reproducibility.
  4. Return the full curve for audit.

Validation

Run tests/test_alpha_selection.py.

Limitations

The skill assumes likelihoods have already been computed by a frozen LM or a declared proxy scorer.

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