MergeLock applies random invertible matrix transformations to Transformer attention weights, preserving the model's own output while forcing any merged model's accuracy down to near random.
Parameter-efficient multi-task model fusion with partial linearization
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Model Unmerging: Making Your Models Unmergeable for Secure Model Sharing
MergeLock applies random invertible matrix transformations to Transformer attention weights, preserving the model's own output while forcing any merged model's accuracy down to near random.