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There is a lack of research into capabilities of recent LLMs to generate convincing text in languages other than English and into performance of detectors of machine-generated text in multilingual settings.
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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Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, et al. 2019 · 1908
Earlier work this paper cites.
Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1911
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Attacking neural text detectors
Max Wolff and Stuart Wolff. 2020 · 2002
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TuringBench: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
Adaku Uchendu, Zeyu Ma, Thai Le, Rui Zhang, and Dongwon Lee. 2021 · 2016
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Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Gltr: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M Rush. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 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
Earlier work this paper cites.
Generating sentiment-preserving fake online reviews using neural language models and their human-and machine-based detection
David Ifeoluwa Adelani, Haotian Mai, Fuming Fang, Huy H Nguyen, Junichi Yamagishi, and Isao Echizen. 2020 · 2020
Earlier work this paper cites.
Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al. 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
Earlier work this paper cites.
Authorship attribution for neural text generation
Adaku Uchendu, Thai Le, Kai Shu, and Dongwon Lee. 2020 · 2020
Earlier work this paper cites.
Neural deepfake detection with factual structure of text
Wanjun Zhong, Duyu Tang, Zenan Xu, Ruize Wang, Nan Duan, Ming Zhou, Jiahai Wang, and Jian Yin. 2020 · 2020
Earlier work this paper cites.
Truth, Lies, and Automation: How Language Models Could Change Disinformation
Ben Buchanan, Andrew Lohn, Micah Musser, and Katerina Sedova. 2021 · 2021
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Lamda: our breakthrough conversation technology
Eli Collins and Zoubin Ghahramani. 2021 · 2021
Earlier work this paper cites.
Automatic detection of hybrid human-machine text boundaries
Joseph Cutler, Liam Dugan, Shreya Havaldar, and Adam Stein. 2021 · 2021
Earlier work this paper cites.
Tweepfake: About detecting deepfake tweets
Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, and Maurizio Tesconi. 2021 · 2021
Cited alongside, same era.
Feature-based detection of automated language models: tackling gpt-2, gpt-3 and grover
Leon Fröhling and Arkaitz Zubiaga. 2021 · 2021
Cited alongside, same era.
Robustness analysis of grover for machine-generated news detection
Rinaldo Gagiano, Maria Myung-Hee Kim, Xiuzhen Jenny Zhang, and Jennifer Biggs. 2021 · 2021
Cited alongside, same era.
Unsupervised and distributional detection of machine-generated text
Matthias Gallé, Jos Rozen, Germán Kruszewski, and Hady Elsahar. 2021 · 2021
Cited alongside, same era.
Artificial text detection via examining the topology of attention maps
Laida Kushnareva, Daniil Cherniavskii, Vladislav Mikhailov, Ekaterina Artemova, Serguei Barannikov, Alexander Bernstein, Irina Piontkovskaya, Dmitri Piontkovski, and Evgeny Burnaev. 2021 · 2021
Cited alongside, same era.
Detecting computer-generated disinformation
Harald Stiff and Fredrik Johansson. 2022 · 2022
Later among the works it cites.
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
Later among the works it cites.
Gpt4all: Training an assistant-style chatbot with large scale data distillation from gpt-3.5-turbo
Yuvanesh Anand, Zach Nussbaum, Brandon Duderstadt, Benjamin Schmidt, and Andriy Mulyar. 2023 · 2023
Closest in time.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
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MassiveSumm: a very large-scale, very multilingual, news summarisation dataset
Daniel Varab and Natalie Schluter. 2021 · 2021
Cited alongside, same era.
GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
Cited alongside, same era.
Gpt-neox-20b: An open-source autoregressive language model
Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, et al. 2022 · 2022
Cited alongside, same era.
MTG: A benchmark suite for multilingual text generation
Yiran Chen, Zhenqiao Song, Xianze Wu, Danqing Wang, Jingjing Xu, Jiaze Chen, Hao Zhou, and Lei Li. 2022 · 2022
Cited alongside, same era.
Adversarial robustness of neural-statistical features in detection of generative transformers
Evan Crothers, Nathalie Japkowicz, Herna Viktor, and Paula Branco. 2022b · 2022
Cited alongside, same era.
Liam Dugan, Daphne Ippolito, Arun Kirubarajan, Sherry Shi, and Chris Callison-Burch. 2022 · 2022
Cited alongside, same era.
Xiaoming Liu, Zhaohan Zhang, Yichen Wang, Yu Lan, and Chao Shen. 2022 · 2022
Cited alongside, same era.
Josh A. Goldstein, Girish Sastry, Micah Musser, Renee DiResta, Matthew Gentzel, and Katerina Sedova. 2023 · 2023
Closest in time.
Mgtbench: Benchmarking machine-generated text detection
Xinlei He, Xinyue Shen, Zeyuan Chen, Michael Backes, and Yang Zhang. 2023 · 2023
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Stylometric detection of ai-generated text in twitter timelines
Tharindu Kumarage, Joshua Garland, Amrita Bhattacharjee, Kirill Trapeznikov, Scott Ruston, and Huan Liu. 2023 · 2023
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Deepfake text detection in the wild
Yafu Li, Qintong Li, Leyang Cui, Wei Bi, Longyue Wang, Linyi Yang, Shuming Shi, and Yue Zhang. 2023 · 2023
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Argugpt: evaluating, understanding and identifying argumentative essays generated by gpt models
Yikang Liu, Ziyin Zhang, Wanyang Zhang, Shisen Yue, Xiaojing Zhao, Xinyuan Cheng, Yiwen Zhang, and Hai Hu. 2023 · 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 · 2023
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OpenAI. 2023 · 2023
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Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao. 2023 · 2023
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Deepfake text detection: Limitations and opportunities
Jiameng Pu, Zain Sarwar, Sifat Muhammad Abdullah, Abdullah Rehman, Yoonjin Kim, Parantapa Bhattacharya, Mobin Javed, and Bimal Viswanath. 2022a · 2023
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Autextification dataset (full data)
Areg Sarvazyan, José Ángel González, Marc Franco, Francisco Manuel Rangel, María Alberta Chulvi, and Paolo Rosso. 2023 · 2023
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Model evaluation for extreme risks
Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, Mary Phuong, Jess Whittlestone, Jade Leung, Daniel Kokotajlo, Nahema Marchal, Markus Anderljung, Noam Kolt, et al. 2023 · 2023
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Detectllm: Leveraging log rank information for zero-shot detection of machine-generated text
Jinyan Su, Terry Yue Zhuo, Di Wang, and Preslav Nakov. 2023 · 2023
Closest in time.
Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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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, Alham Fikri Aji, et al. 2023 · 2023
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Detecting cross-modal inconsistency to defend against neural fake news
Reuben Tan, Bryan Plummer, and Kate Saenko. 2020 · 2081
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