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Not All Is Lost: Repairing Lossy User Preference States of Personalization Encoders
Personalization encoders compress evolving interaction histories into preference states used to rank items or condition text generation. A task head operating only on this state can miss useful evidence that remains in the frozen encoder's cached representations for individual timesteps. We study th
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