Output Vector Editing for Memorization Mitigation in Large Language Models
Output vector editing modifies what specific neurons contribute to a model's output stream instead of just turning neurons on or off. This technique suppresses memorized sequences by introducing a vocabulary distractor into these neuron outputs, achieving up to 87.9% suppression on OLMo-7B. It offers precise, weight-level intervention without requiring retraining.