Estimate Memory Aware Synapses parameter importance from unlabeled inputs using output-sensitivity gradients.
Scanned 9/9/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill mas_unlabeled_importance --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: mas_unlabeled_importance
description: Estimate Memory Aware Synapses parameter importance from unlabeled inputs using output-sensitivity gradients.
---
# MAS Unlabeled Importance
Use when MAS recovery needs label-free importance. Inputs are weights and unlabeled samples; outputs are nonnegative importance values and sample-count metadata. Compute squared-output-norm gradients, average absolute values, and reject empty streams. Validate with `python tests/test_importance.py`.
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