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coherence_boosted_scoring

coherence_boosted_scoring

Apply the coherence boosting log-linear scoring rule to full-context and premise-free answer likelihoods.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: coherence_boosted_scoring description: Apply the coherence boosting log-linear scoring rule to full-context and premise-free answer likelihoods.

Coherence Boosted Scoring

Use this skill when you already have candidate log likelihoods under a full context and a premise-free context and need the paper's inference-time correction.

Inputs

  • Equal-length lists of full-context and premise-free log likelihoods.
  • A real-valued alpha; negative values discount premise-free priors.

Outputs

  • Combined scores full_logprob + alpha * short_logprob.
  • Predicted candidate index and margin diagnostics.

Workflow

  1. Validate equal list lengths and finite numeric values.
  2. Compute boosted scores in the log domain.
  3. Return the argmax, preserving candidate order.
  4. Record whether alpha is negative, zero, or positive for mechanism evidence.

Validation

Run the deterministic tests in tests/test_boosted_scoring.py.

Limitations

This skill does not estimate likelihoods or select alpha. It only implements the paper's scoring equation.

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