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Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design.
Gltr: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M Rush. 2019 · 1906
Earlier work this paper cites.
Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, and Jasmine Wang. 2019 · 1908
Earlier work this paper cites.
CTRL - A Conditional Transformer Language Model for Controllable Generation
Nitish Shirish Keskar, Bryan McCann, Lav Varshney, Caiming Xiong, and Richard Socher. 2019 · 1909
Earlier work this paper cites.
Approximate nearest neighbors: Towards removing the curse of dimensionality
Piotr Indyk and Rajeev Motwani. 1998 · 1998
Earlier work this paper cites.
Provable robust watermarking for ai-generated text
Xuandong Zhao, Prabhanjan Ananth, Lei Li, and Yu-Xiang Wang. 2023 · 1998
Earlier work this paper cites.
Natural language watermarking: Design, analysis, and a proof-of-concept implementation
Mikhail J. Atallah, Victor Raskin, Michael Crogan, Christian Hempelmann, Florian Kerschbaum, Dina Mohamed, and Sanket Naik. 2001 · 2001
Earlier work this paper cites.
Natural language watermarking and tamperproofing
Mikhail J. Atallah, Victor Raskin, Christian F. Hempelmann, Mercan Karahan, Radu Sion, Umut Topkara, and Katrina E. Triezenberg. 2002 · 2002
Earlier work this paper cites.
Similarity estimation techniques from rounding algorithms
Moses S Charikar. 2002 · 2002
Earlier work this paper cites.
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Hongchao Fang, Sicheng Wang, Meng Zhou, Jiayuan Ding, and Pengtao Xie. 2020 · 2005
Earlier work this paper cites.
Contrastive self-supervised learning for commonsense reasoning
Tassilo Klein and Moin Nabi. 2020 · 2005
Earlier work this paper cites.
Randomized algorithms and NLP: Using locality sensitive hash functions for high speed noun clustering
Deepak Ravichandran, Patrick Pantel, and Eduard Hovy. 2005 · 2005
Earlier work this paper cites.
Dimensionality reduction by learning an invariant mapping
R. Hadsell, S. Chopra, and Y. LeCun. 2006 · 2006
Earlier work this paper cites.
Online generation of locality sensitive hash signatures
Benjamin Van Durme and Ashwin Lall. 2010 · 2010
Earlier work this paper cites.
Watermarking the outputs of structured prediction with an application in statistical machine translation
Ashish Venugopal, Jakob Uszkoreit, David Talbot, Franz Och, and Juri Ganitkevitch. 2011 · 2011
Earlier work this paper cites.
SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
Earlier work this paper cites.
Generating sentences by editing prototypes
Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, and Percy Liang. 2018 · 2018
Earlier work this paper cites.
An efficient framework for learning sentence representations
Lajanugen Logeswaran and Honglak Lee. 2018 · 2018
Earlier work this paper cites.
Generating informative and diverse conversational responses via adversarial information maximization
Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, and William B. Dolan. 2018 · 2018
Earlier work this paper cites.
Abstractive Summarization of Reddit Posts with Multi-level Memory Networks
Byeongchang Kim, Hyunwoo Kim, and Gunhee Kim. 2019 · 2019
Earlier work this paper cites.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Defending against neural fake news
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi. 2019 · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 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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Automatic detection of machine generated text: A critical survey
Ganesh Jawahar, Muhammad Abdul-Mageed, and Laks Lakshmanan, V.S. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Threat scenarios and best practices to detect neural fake news
Artidoro Pagnoni, Martin Graciarena, and Yulia Tsvetkov. 2022 · 2022
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Paraphrastic representations at scale
John Wieting, Kevin Gimpel, Graham Neubig, and Taylor Berg-kirkpatrick. 2022 · 2022
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OPT: Open Pre-trained Transformer Language Models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
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On the possibilities of ai-generated text detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, and Furong Huang. 2023 · 2023
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Undetectable watermarks for language models
Miranda Christ, Sam Gunn, and Or Zamir. 2023 · 2023
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Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense
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Promptcare: Prompt copyright protection by watermark injection and verification
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Robust multi-bit natural language watermarking through invariant features
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