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It is found that merely warning the agents of potential imposter presence is not beneficial: it degrades decisions when no imposter is present, provokes reactions ranging from self-accusation to scapegoating, inflates token use, and reveals to the imposter how it was uncovered.
Two training-time mitigations, label augmentation and shortcut-targeted hard negatives, which reduce judged nonsense while preserving ranking performance are studied.
This paper studies the phenomenon whereby specific short input phrases induce a partial amnesia effect in state space models, by irreversibly overwriting information in their hidden states, referred to as a Hidden State Poisoning Attack (HiSPA).
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