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Extensions and reliability

# Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Coding

Jiaming Shen, Heng Ji, Jiawei Han

First arXiv submission: October 1, 2020 · EMNLP 2020

Published version: November 2020. The publication and preprint records below retain their own dates and identifiers.

Introduces self-adjusting arithmetic coding, choosing the candidate-set size at each generation step to control divergence from the language model. It supplies an imperceptibility analysis and evaluates capacity, divergence, and human judgments across multiple datasets.

[Read paper ↗](https://aclanthology.org/2020.emnlp-main.22/) · [PDF ↗](https://aclanthology.org/2020.emnlp-main.22.pdf) · [Code ↗](https://github.com/mickeysjm/StegaText)

## Relationship to Neural Linguistic Steganography

The introduction explicitly states that SAAC builds on Ziegler, Deng, and Rush's 2019 arithmetic-coding method, replacing a fixed truncation size with an adaptive one.

## Scope and limitations

Its distributional guarantee is relative to the underlying language model; choosing the truncation threshold still trades embedding behavior and computation against divergence.

## Cite this paper

### Published version

Jiaming Shen, Heng Ji, Jiawei Han. [Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Coding](https://aclanthology.org/2020.emnlp-main.22/). Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020

[Published version BibTeX](https://steganography.live/reading-list/papers/saac/publication.bib) · [Published version CSL-JSON](https://steganography.live/reading-list/papers/saac/publication.csl.json)
Show BibTeX`@inproceedings{saac-publication,
  title = {{Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Coding}},
  author = {Shen, Jiaming and Ji, Heng and Han, Jiawei},
  year = {2020},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  doi = {10.18653/v1/2020.emnlp-main.22},
  pages = {303--313},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2020.emnlp-main.22/}
}
`

### arXiv preprint

Jiaming Shen, Heng Ji, Jiawei Han. [Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Coding](https://arxiv.org/abs/2010.00677v1). arXiv:2010.00677. First submission: October 1, 2020.

This citation records the first arXiv version and its original title. The version-specific link distinguishes it from later revisions; cite the version supporting your claim.

[arXiv preprint BibTeX](https://steganography.live/reading-list/papers/saac/preprint.bib) · [arXiv preprint CSL-JSON](https://steganography.live/reading-list/papers/saac/preprint.csl.json)
Show BibTeX`@misc{saac-preprint,
  title = {{Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Coding}},
  author = {Shen, Jiaming and Ji, Heng and Han, Jiawei},
  year = {2020},
  publisher = {arXiv},
  eprint = {2010.00677v1},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2010.00677v1}
}
`

## Primary sources

- [Published bibliographic metadata and DOI.](https://aclanthology.org/2020.emnlp-main.22/)

- [First arXiv submission October 1, 2020.](https://arxiv.org/abs/2010.00677)

- [Introduction explicitly identifies extension of 2019 method; sections 2–3 define relative imperceptibility/adaptive K; page 1 links code.](https://aclanthology.org/2020.emnlp-main.22.pdf)

- [Official code repository linked by the paper.](https://github.com/mickeysjm/StegaText)

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