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With advances in neural language models, the focus of linguistic steganography has shifted from edit-based approaches to generation-based ones.
The prisoners’ problem and the subliminal channel
Gustavus J Simmons. 1984 · 1984
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On the limits of steganography
Ross J Anderson and Fabien AP Petitcolas. 1998 · 1998
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A practical and effective approach to large-scale automated linguistic steganography
Mark Chapman, George I. Davida, and Marc Rennhard. 2001 · 2001
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Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2004
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Linguistic steganography: Survey, analysis, and robustness concerns for hiding information in text
Krista Bennett. 2004 · 2004
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A method of linguistic steganography based on collocationally-verified synonymy
Igor A. Bolshakov. 2005 · 2005
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Attacks on lexical natural language steganography systems
Cuneyt M. Taskiran, Umut Topkara, Mercan Topkara, and Edward J. Delp. 2006 · 2006
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z. Li, Madian Khabsa, Han Fang, and Hao Ma. 2020 · 2006
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Adversarial watermarking transformer: Towards tracing text provenance with data hiding
Sahar Abdelnabi and Mario Fritz. 2020 · 2009
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Steganography in digital media: principles, algorithms, and applications
Jessica Fridrich. 2009 · 2009
Cited alongside, same era.
Practical linguistic steganography using contextual synonym substitution and a novel vertex coding method
Ching-Yun Chang and Stephen Clark. 2014 · 2014
Cited alongside, same era.
Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Cited alongside, same era.
Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çağlar Gu̇lçehre, and Bing Xiang. 2016 · 2016
Cited alongside, same era.
Avoiding detection on twitter: embedding strategies for linguistic steganography
Alex Wilson and Andrew D. Ker. 2016 · 2016
Cited alongside, same era.
Generating steganographic text with LSTMs
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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RNN-Stega: Linguistic steganography based on recurrent neural networks
Zhong-Liang Yang, Xiao-Qing Guo, Zi-Ming Chen, Yong-Feng Huang, and Yu-Jin Zhang. 2019 · 2019
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Neural linguistic steganography
Zachary Ziegler, Yuntian Deng, and Alexander Rush. 2019 · 2019
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Automatic detection of generated text is easiest when humans are fooled
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck. 2020 · 2020
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Near-imperceptible neural linguistic steganography via self-adjusting arithmetic coding
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Tina Fang, Martin Jaggi, and Katerina Argyraki. 2017 · 2017
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Towards near-imperceptible steganographic text
Falcon Dai and Zheng Cai. 2019 · 2019
Cited alongside, same era.
Jiaming Shen, Heng Ji, and Jiawei Han. 2020 · 2020
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CCNet: Extracting high quality monolingual datasets from web crawl data
Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzmán, Armand Joulin, and Edouard Grave. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Later among the works it cites.