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This paper introduces a decoupled evaluation paradigm to separate memory recall from actual utilization in LLM personalization, finding that agents often recall user preferences but fail to act on them in behavioral scenarios. Large-scale experiments across 16 systems and five memory architectures reveal a significant Know-Act gap, especially for health-related preferences.