CrispEdit edits LLMs via low-curvature projections using Bregman divergence and K-FAC approximations, achieving high edit success with under 1% average capability degradation.
New insights and perspectives on the natural gradient method.Journal of Machine Learning Research, 21(146):1–76, 2020.http://jmlr.org/papers/v21/17-678.html
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CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing
CrispEdit edits LLMs via low-curvature projections using Bregman divergence and K-FAC approximations, achieving high edit success with under 1% average capability degradation.