DEFT splits networks into frozen Core and trainable Slack to block forgetting
TheGradient · x · 2026-07-24
The mechanism in plain terms
The thread explains DEFT’s partitioning scheme: neurons with larger Hilbert-norm values are assigned to the frozen “Core,” while the rest become the trainable “Slack.” A merge step removes redundancy in the Core, and then an architectural mask blocks any path from Slack back into Core.
The claimed benefit
This creates a one-way valve for learning: new task updates can use the plastic side, but they cannot propagate backward to corrupt the stable foundation. The author presents it as a stronger guarantee against catastrophic forgetting than ordinary fine-tuning or soft regularization.
Related event: DEFT Introduces Core-Slack Architecture to Prevent Catastrophic Forgetting(3 posts)→
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