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A Deafening Silence: Catastrophic Forgetting Lives in the Output Embeddings of Tokens the Data Never Speaks

arXiv cs.CL ↗ · 2026-10-08 Cached

该论文定位了LLM持续预训练/微调中灾难性遗忘的根源——语料库中罕见词元的输出嵌入,并提出仅提升输出投影层Adam ε值的单行优化器改动,在160M至12B参数规模上消除了39.4%至67.9%的遗忘且不损害目标学习。

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