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The explosive prompt is introduced, a conditional payload that stays dormant until an attacker-chosen trigger is met, in effect a training-free, inference-time backdoor planted in a single piece of retrieved content.
When interacting with large language models (LLMs), users have limited visibility and control over how their personal information is retained, particularly after incorporation into model training. Although some deployed LLMs provide options to opt-out of training, these mechanisms do not offer guarantees about the dele...
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