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Spurious forgetting in LLMs is a reversible access loss, not permanent knowledge erasure, and can be mitigated by decoupling shared representational shifts from fact-specific updates.
Alignment tuning installs distinct bias directions in LLMs, allowing for targeted debiasing that recovers unbiased answers while maintaining performance.
