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.
Learning transferable visual models from natural language supervision
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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.