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With the emergence of widely available powerful LLMs, disinformation generated by large Language Models (LLMs) has become a major concern.
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 1902
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Real or fake? learning to discriminate machine from human generated text
Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc’Aurelio Ranzato, and Arthur Szlam. 2019 · 1906
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Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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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
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ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2003
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Host-pathongen co-evolution inspired algorithm enables robust GAN training
Andrei Kucharavy, El Mahdi El Mhamdi, and Rachid Guerraoui. 2020 · 2006
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The radicalization risks of gpt-3 and advanced neural language models
Kris McGuffie and Alex Newhouse. 2020 · 2009
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Exposure to the russian internet research agency foreign influence campaign on twitter in the 2016 us election and its relationship to attitudes and voting behavior
Gregory Eady, Tom Paskhalis, Jan Zilinsky, Richard Bonneau, Jonathan Nagler, and Joshua A. Tucker. 2023 · 2016
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Computational propaganda: If you make it trend, you make it true
Renee DiRESTA. 2018 · 2018
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The spread of true and false news online
Soroush Vosoughi, Deb K. Roy, and Sinan Aral. 2018 · 2018
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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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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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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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On the dangers of stochastic parrots: Can language models be too big?
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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Uncovering coordinated networks on social media: Methods and case studies
Diogo Pacheco, Pik-Mai Hui, Christopher Torres-Lugo, Bao Tran Truong, Alessandro Flammini, and Filippo Menczer. 2021 · 2021
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Dos and don’ts of machine learning in computer security
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, and Konrad Rieck. 2022 · 2022
Cited alongside, same era.
Russian propaganda on social media during the 2022 invasion of ukraine
Dominique Geissler, Dominik Bär, Nicolas Pröllochs, and Stefan Feuerriegel. 2022 · 2022
Cited alongside, same era.
Human heuristics for ai-generated language are flawed
Maurice Jakesch, Jeffrey T. Hancock, and Mor Naaman. 2022 · 2022
Cited alongside, same era.
A new and better quiet option? strategies of subversion and cyber conflict
Lennart Maschmeyer. 2022 · 2022
Cited alongside, same era.
Can llm-generated misinformation be detected?
Canyu Chen and Kai Shu. 2023 · 2023
Cited alongside, same era.
On the zero-shot generalization of machine-generated text detectors
Xiao Pu, Jingyu Zhang, Xiaochuang Han, Yulia Tsvetkov, and Tianxing He. 2023 · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
Later among the works it cites.
Zephyr: Direct distillation of LM alignment
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, and Thomas Wolf. 2023 · 2023
Later among the works it cites.
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Vitalii Fishchuk and Daniel Braun. 2023 · 2023
Cited alongside, same era.
Josh A. Goldstein, Girish Sastry, Micah Musser, Renee DiResta, Matthew Gentzel, and Katerina Sedova. 2023 · 2023
Cited alongside, same era.
Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, and Yuanzhi Li. 2023 · 2023
Cited alongside, same era.
Mgtbench: Benchmarking machine-generated text detection
Xinlei He, Xinyue Shen, Zeyuan Johnson Chen, Michael Backes, and Yang Zhang. 2023 · 2023
Cited alongside, same era.
Multitude: Large-scale multilingual machine-generated text detection benchmark
Dominik Macko, Róbert Móro, Adaku Uchendu, Jason Samuel Lucas, Michiharu Yamashita, Matús Pikuliak, Ivan Srba, Thai Le, Dongwon Lee, Jakub Simko, and Mária Bieliková. 2023 · 2023
Cited alongside, same era.
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, and Chelsea Finn. 2023 · 2023
Cited alongside, same era.
Sandra Mitrović, Davide Andreoletti, and Omran Ayoub. 2023 · 2023
Cited alongside, same era.
Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, and Jiliang Tang. 2023 · 2023
Later among the works it cites.
Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, Linyi Yang, and Yue Zhang. 2024 · 2024
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Supersharers of fake news on twitter
Sahar Baribi-Bartov, Briony Swire-Thompson, and Nir Grinberg. 2024 · 2024
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LLM Detectors , pages 197–204. Springer Nature Switzerland, Cham
Henrique Da Silva Gameiro. 2024 · 2024
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Raid: A shared benchmark for robust evaluation of machine-generated text detectors
Liam Dugan, Alyssa Hwang, Filip Trhlik, Josh Magnus Ludan, Andrew Zhu, Hainiu Xu, Daphne Ippolito, and Christopher Callison-Burch. 2024 · 2024
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Token-Ensemble Text Generation: On Attacking the Automatic AI-Generated Text Detection
Fan Huang, Haewoon Kwak, and Jisun An. 2024 · 2024
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Mage: Machine-generated text detection in the wild
Yafu Li, Qintong Li, Leyang Cui, Wei Bi, Zhilin Wang, Longyue Wang, Linyi Yang, Shuming Shi, and Yue Zhang. 2024 · 2024
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The potential of generative ai for personalized persuasion at scale
S C Matz, J D Teeny, Sumer S. Vaid, H Peters, Gabriella M. Harari, and M Cerf. 2024 · 2024
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Can AI-Generated Text be Reliably Detected?
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi. 2024 · 2024
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Gptzero: Towards detection of ai-generated text using zero-shot and supervised methods
Edward Tian and Alexander Cui. 2024 · 2024
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M4: multi-generator, multi-domain, and multi-lingual black-box machine-generated text detection
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Chenxi Whitehouse, Osama Mohammed Afzal, Tarek Mahmoud, Toru Sasaki, Thomas Arnold, Alham Fikri Aji, Nizar Habash, Iryna Gurevych, and Preslav Nakov. 2024b · 2024
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