Omega-S: A Data-Free Regularization Penalty for LLM Fine-Tuning
Alberto Acedo · hf · 2026-08-12
The author introduces Omega-S, a functional resilience index for low-rank fine-tuning of LLMs.
It is a lightweight, data-free regularization penalty that helps retain the original capabilities of the model by penalizing the variance in weight-matrix node degrees, effectively mitigating catastrophic forgetting during fine-tuning.
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