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This paper investigates the effectiveness of top-1 collapse rate as a stability monitor for short-horizon LoRA fine-tuning of discrete diffusion language models, finding it has zero precision, and proposes max gradient norm as a more reliable alternative with higher precision and F1 score on LLaDA-family models.