Om Tailor, Yucheng Pan, Solaleh Mohammadi, Xinyan Liu, Kaiqing Zhang · 2026 · arXiv
DOI: 10.48550/arXiv.2610.30516 · open-access PDF
在大型语言模型(LLM)语文学中,编码器在另一种普通的响应中隐藏一个私人信息,作为向解码器传输的文本,试图恢复它。 这种私人信息传输的成功通常通过端到端(E2E)恢复来衡量,这检查了解码器是否正确地重建了私人信息。 然而,E2E恢复不能区分编码失败与解码失败,也不能揭示该私人信息如何在编码器传输的文本中呈现。
Machine translation (Meta M2M100); the English original follows.
In large language model (LLM) steganography, an encoder hides a private message in an otherwise ordinary response, as text transmitted to a decoder, who attempts to recover it. The success of this private-message transmission is commonly measured through end-to-end (E2E) recovery, which checks whether the decoder correctly reconstructs the private message. However, E2E recovery cannot distinguish encoding failures from decoding failures or reveal how the private message is represented in the encoder's transmitted text. To address these limitations, we introduce a rolewise decomposition framewo
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