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arXiv:2401.10360cs.CR

Excuse me, sir? Your language model is leaking (information)

Or Zamir

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

We introduce a cryptographic method to hide an arbitrary secret payload in the response of a Large Language Model (LLM). A secret key is required to extract the payload from the model's response, and without the key it is provably impossible to distinguish between the responses of the original LLM and the LLM that hides a payload. In particular, the quality of generated text is not affected by the payload. Our approach extends a recent result of Christ, Gunn and Zamir (2023) who introduced an undetectable watermarking scheme for LLMs.

arXiv comments
Journal reference
Transactions on Machine Learning Research, 2835-8856, 2024
DOI
Subjects
cs.CRCryptography and Security cs.LGMachine Learning

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Jan 2024 to Jan 2024. Found in 1 HN submission from Jan 2024 to Jan 2024. Open submission discussions.

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