AINeutralarXiv – CS AI · 7h ago6/10
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Making Models Unmergeable via Scaling-Sensitive Loss Landscape
Researchers propose Trap², an architecture-agnostic defense framework that protects AI models from unauthorized merging by encoding protection into model weights during fine-tuning. The method degrades model performance when weights are re-scaled during merging operations while maintaining effectiveness in standalone use, addressing a governance gap where downstream users can bypass safety alignment and licensing restrictions.