ReTokSync resolves tokenization ambiguity in generative linguistic steganography via targeted self-synchronizing resets, achieving over 99.7% extraction accuracy and 100% recovery with an auxiliary channel while matching baseline security and quality.
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cs.CR 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A black-box text steganography method using a dynamic codebook generated by multimodal LLMs and reject-sampling feedback achieves higher embedding capacity and text quality than prior white-box and fixed-codebook black-box approaches.
citing papers explorer
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ReTokSync: Self-Synchronizing Tokenization Disambiguation for Generative Linguistic Steganography
ReTokSync resolves tokenization ambiguity in generative linguistic steganography via targeted self-synchronizing resets, achieving over 99.7% extraction accuracy and 100% recovery with an auxiliary channel while matching baseline security and quality.
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Text Steganography with Dynamic Codebook and Multimodal Large Language Model
A black-box text steganography method using a dynamic codebook generated by multimodal LLMs and reject-sampling feedback achieves higher embedding capacity and text quality than prior white-box and fixed-codebook black-box approaches.