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name: deberta_enhanced_mask_decoder description: Apply DeBERTa enhanced mask decoder scoring that injects absolute position evidence only at candidate decoding time.

DeBERTa Enhanced Mask Decoder

Use this skill when a reduced recovery or unit test needs to preserve DeBERTa's decoder-time absolute-position rule. The skill separates relative-context scoring from absolute-position scoring so an experiment can prove that absolute position was not mixed into encoder inputs.

Inputs

• Candidate records with label, text, and absolute_position.
• Relative-context scores from an encoder, attention helper, or deterministic proxy.
• Optional absolute-position target and weight.

Outputs

• Candidate logits with separate relative_score and emd_score fields.
• Predicted label.
• EMD ablation result with the absolute-position contribution disabled.

Workflow

1. Build candidate records from a masked-token or multiple-choice protocol.
2. Keep relative-context scores separate from absolute-position features.
3. Call scripts/enhanced_mask_decoder.py to add the EMD term at candidate scoring time.
4. Save both full and no-EMD scores in recovery logs when using this skill as mechanism evidence.

Validation

Run the skill-tree validator with --run-tests. The tests check that relative-only candidates can tie, EMD breaks an absolute-position-sensitive tie, and disabling EMD changes the chosen score path.

Limitations

This is a standard-library proxy for the EMD contract. It does not implement the full Transformer decoder stack or masked language model head.