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AlignMerge - Alignment-Preserving Large Language Model Merging via Fisher-Guided Geometric Constraints
Merging large language models (LLMs) is a practical way to compose capabilities from multiple fine-tuned checkpoints without retraining. Yet standard schemes (linear weight soups, task vectors, and Fisher-weighted averaging) can preserve loss while quietly destroying alignment. We argue that merging
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