mlsanityData to 14 Oct 2026

Addressing Segmentation Ambiguity in Neural Linguistic Steganography

arXiv 2211.06662 ↗First posted 12 Nov 2022cs.CLcited by 7

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Abstract (arXiv)

Previous studies on neural linguistic steganography, except Ueoka et al. (2021), overlook the fact that the sender must detokenize cover texts to avoid arousing the eavesdropper's suspicion. In this paper, we demonstrate that segmentation ambiguity indeed causes occasional decoding failures at the receiver's side. With the near-ubiquity of subwords, this problem now affects any language. We propose simple tricks to overcome this problem, which are even applicable to languages without explicit word boundaries.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 13 of its 34 references that are in the map. First posted on arXiv 12 Nov 2022.

Builds on

13 of 34 references.

References · 13

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  4. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
  5. 2019CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Datacited by 548
  6. 2019Neural Linguistic Steganographycited by 78
  7. 2017Generating Steganographic Text with LSTMscited by 44
  8. 2021Provably Secure Generative Linguistic Steganographycited by 34
  9. 2019Towards Near-imperceptible Steganographic Textcited by 32
  10. 2021Frustratingly Easy Edit-based Linguistic Steganography with a Masked Language Modelcited by 30
  11. 2020Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Codingcited by 17
  12. 2022Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Codingcited by 7
1 more
  1. 2022Autoregressive Linguistic Steganography Based on BERT and Consistency Codingcited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 4.

7 papers.

  1. 2024Provably Secure Disambiguating Neural Linguistic Steganographycited by 5
  2. 2025Addressing Tokenization Inconsistency in Steganography and Watermarking Based on Large Language Modelscited by 4
  3. 2026Efficient Provably Secure Linguistic Steganography via Range Codingcited by 3
  4. 2026Anchored Sliding Window: Toward Robust and Imperceptible Linguistic Steganographycited by 2
  5. 2025A High-Capacity and Secure Disambiguation Algorithm for Neural Linguistic Steganographycited by 1
  6. 2026HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Frameworkcited by 1
  7. 2026A Comprehensive Survey on Linguistic Steganography: Methods, Countermeasures, Evaluation, and Challengescited by 0