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Towards Near-imperceptible Steganographic Text
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We show that the imperceptibility of several existing linguistic steganographic systems (Fang et al., 2017; Yang et al., 2018) relies on implicit assumptions on statistical behaviors of fluent text. We formally analyze them and empirically evaluate these assumptions. Furthermore, based on these observations, we propose an encoding algorithm called patient-Huffman with improved near-imperceptible guarantees.
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Semantic Steganography: A Framework for Robust and High-Capacity Information Hiding using Large Language Models
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