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The capabilities of large language models have grown significantly in recent years and so too have concerns about their misuse.
WordNet: A lexical database for english
George A. Miller · 1994
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Information transmission and steganography
Ingemar J. Cox, Ton Kalker, Georg Pakura, and Mathias Scheel · 2005
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An introduction to ROC analysis
Tom Fawcett · 2006
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Provably secure steganography
Nicholas Hopper, Luis von Ahn, and John Langford · 2009
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Teaching Machines to Read and Comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom · 2015
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An innovative technique for web text watermarking (aitw)
Milad Taleby Ahvanooey, Hassan Dana Mazraeh, and Seyed Tabasi · 2016
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OpenNMT: Open-source toolkit for neural machine translation
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander Rush · 2017
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Text watermarking in social media
Stefano Giovanni Rizzo, Flavio Bertini, Danilo Montesi, and Carlo Stomeo · 2017
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Get To The Point: Summarization with Pointer-Generator Networks
Abigail See, Peter J. Liu, and Christopher D. Manning · 2017
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A review of text watermarking: Theory, methods, and applications
Nurul Shamimi Kamaruddin, Amirrudin Kamsin, Lip Yee Por, and Hameedur Rahman · 2018
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Real or fake? Learning to discriminate machine from human generated text, November 2019
Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc’Aurelio Ranzato, and Arthur Szlam · 2019
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GLTR: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander Rush · 2019
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Defending against neural fake news
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi · 2019
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Neural linguistic steganography
Zachary Ziegler, Yuntian Deng, and Alexander Rush · 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 2020
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Automatic detection of generated text is easiest when humans are fooled, May 2020
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck · 2020
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Authorship attribution for neural text generation
Adaku Uchendu, Thai Le, Kai Shu, and Dongwon Lee · 2020
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Neural text generation with unlikelihood training
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf et al · 2020
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Program synthesis with large language models, 2021
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, and Charles Sutton · 2021
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Tweepfake: About detecting deepfake tweets
Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, and Maurizio Tesconi · 2021
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Argos translate, August 2021
P.J. Finlay and Contributors Argos Translate · 2021
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Hacking humans with ai as a service
Eugene Lim, Glenice Tan, Tan Kee Hock, and Timothy Lee · 2021
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A review on text steganography techniques
Mohammed A. Majeed, Rossilawati Sulaiman, Zarina Shukur, and Mohammad K. Hasan · 2021
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GPT-2 Output Dataset Detector, 2021
OpenAI · 2021
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Mauve: Measuring the gap between neural text and human text using divergence frontiers
Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, and Zaid Harchaoui · 2021
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Watermarking GPT outputs, December 2022
Scott Aaronson and Hendrik Kirchner · 2022
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G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment, 2023
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu · 2023
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DetectGPT: Zero-shot machine-generated text detection using probability curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, and Chelsea Finn · 2023
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Can AI-generated text be reliably detected?, March 2023
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi · 2023
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Necessary and sufficient watermark for large language models, 2023
Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, and Makoto Yamada · 2023
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The science of detecting llm-generated texts, 2023
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu · 2023
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Llama 2: Open foundation and fine-tuned chat models, July 2023
Hugo Touvron et al · 2023
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SSLGuard: A watermarking scheme for self-supervised learning pre-trained encoders
Tianshuo Cong, Xinlei He, and Yang Zhang · 2022
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Holistic evaluation of language models, November 2022
Percy Liang et al · 2022
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GPT-4 technical report
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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On the possibilities of AI-generated text detection, April 2023
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, and Furong Huang · 2023
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Can LLM-generated misinformation be detected?
Canyu Chen and Kai Shu · 2023
Cited alongside, same era.
Can large language models be an alternative to human evaluations?
Cheng-Han Chiang and Hung-yi Lee · 2023
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Waterbench: Towards holistic evaluation of watermarks for large language models, 2023
Shangqing Tu, Yuliang Sun, Yushi Bai, Jifan Yu, Lei Hou, and Juanzi Li · 2023
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Christoforos Vasilatos, Manaar Alam, Talal Rahwan, Yasir Zaki, and Michail Maniatakos · 2023
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Toward quantifying trust dynamics: How people adjust their trust after moment-to-moment interaction with automation
X Jessie Yang, Christopher Schemanske, and Christine Searle · 2023
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Watermarks in the sand: Impossibility of strong watermarking for generative models, 2023
Hanlin Zhang, Benjamin L. Edelman, Danilo Francati, Daniele Venturi, Giuseppe Ateniese, and Boaz Barak · 2023
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Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena, 2023
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica · 2023
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On the learnability of watermarks for language models, 2024
Chenchen Gu, Xiang Lisa Li, Percy Liang, and Tatsunori Hashimoto · 2024
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Zhiwei He, Binglin Zhou, Hongkun Hao, Aiwei Liu, Xing Wang, Zhaopeng Tu, Zhuosheng Zhang, and Rui Wang · 2024
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Unbiased watermark for large language models
Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, and Heng Huang · 2024
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Watermark stealing in large language models
Nikola Jovanović, Robin Staab, and Martin Vechev · 2024
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An entropy-based text watermarking detection method, 2024
Yijian Lu, Aiwei Liu, Dianzhi Yu, Jingjing Li, and Irwin King · 2024
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Meta Llama 3, 2024
Meta · 2024
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MarkLLM: An open-source toolkit for LLM watermarking
Leyi Pan, Aiwei Liu, Zhiwei He, Zitian Gao, Xuandong Zhao, Yijian Lu, Binglin Zhou, Shuliang Liu, Xuming Hu, Lijie Wen, et al · 2024
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Artificial Intelligence Act
European Parliament · 2024
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In-context impersonation reveals large language models’ strengths and biases
Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto, Eric Schulz, and Zeynep Akata · 2024
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