Fine-tuning an LLM to imitate a model never trained on unwanted data leaves the capability quickly relearnable.
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We begin by showing that this is true even for an idealized form of unlearning: training to imitate a model that was never trained on unwanted information.
Oracle-matching baseline: finetuning a model to imitate a model never trained on the forget data still leaves the capability recoverable.
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Created by extractor · Nov 11, 2026. Every judgment on this page is accompanied by a reasoning trace.