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---
name: least_squares_mask_tuning
description: Tune surviving pruning mask coefficients with damped least squares for activation reconstruction.
---
# Least Squares Mask Tuning
Use this skill for the paper's final post-training pruning stage, after a binary structured mask has been selected and rearranged. It tunes only surviving mask entries to reconstruct original layer activations. Do not use it as model-weight retraining, and never revive pruned entries.
## Inputs
- Matrix `A` of per-unit activation contributions.
- Target vector `b` for reconstruction.
- Binary keep mask.
- Damping and acceptable coefficient range.
## Outputs
A real-valued mask, baseline/tuned reconstruction errors, and an accepted flag. Pruned entries remain zero.
## Workflow
Restrict `A` to kept columns, solve damped normal equations, insert the coefficients into the full mask, and reject coefficients outside the range. Report whether reconstruction error improved.
## Validation
Run the included deterministic synthetic tests.
