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This paper investigates whether repetition loops in long factual enumeration tasks by Gemma 4 models can be fixed by editing a single neuron. It finds that targeted weight edits on a small set of MLP neurons can significantly reduce loop failures, though not completely eliminate doom looping in larger models.