PRISM is a new activation-conditioned model that recovers full sets of simultaneous instructions from LLM hidden states via judge-guided GRPO training and outperforms prior activation-to-language methods on security-relevant tasks.
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Rep2Text recovers roughly half the tokens from 16-token sequences using only the last-token representation while retaining semantic coherence across several LLMs.
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PRISM: Recovering Instruction Sets from Language Model Activations
PRISM is a new activation-conditioned model that recovers full sets of simultaneous instructions from LLM hidden states via judge-guided GRPO training and outperforms prior activation-to-language methods on security-relevant tasks.
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Rep2Text: Decoding Full Text from a Single LLM Token Representation
Rep2Text recovers roughly half the tokens from 16-token sequences using only the last-token representation while retaining semantic coherence across several LLMs.