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The efficacy of detectors for texts generated by large language models (LLMs) substantially depends on the availability of large-scale training data.
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
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.
Facilitation in recognizing pairs of words: evidence of a dependence between retrieval operations
David E Meyer and Roger W Schvaneveldt. 1971 · 1971
Earlier work this paper cites.
Semantic priming and retrieval from lexical memory: Roles of inhibitionless spreading activation and limited-capacity attention
James H Neely. 1977 · 1977
Earlier work this paper cites.
Writing performance: Effects of cognitive strategies
Ronald T Kellogg. 1987 · 1987
Earlier work this paper cites.
Cognitive load during problem solving: Effects on learning
John Sweller. 1988 · 1988
Earlier work this paper cites.
Working memory
Alan Baddeley. 1992 · 1992
Earlier work this paper cites.
Foundations of statistical natural language processing
Christopher Manning and Hinrich Schutze. 1999 · 1999
Earlier work this paper cites.
A machine learning approach to the automatic evaluation of machine translation
Simon Corston-Oliver, Michael Gamon, and Chris Brockett. 2001 · 2001
Earlier work this paper cites.
A guided tour to approximate string matching
Gonzalo Navarro. 2001 · 2001
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Cross-linguistic influence
Terence Odlin. 2003 · 2003
Earlier work this paper cites.
Pre-trained models for natural language processing: A survey
Xipeng Qiu, Tianxiang Sun, Yige Xu, Yunfan Shao, Ning Dai, and Xuanjing Huang. 2020 · 2003
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Working memory in writing: Empirical evidence from the dual-task technique
Thierry Olive. 2004 · 2004
Earlier work this paper cites.
METEOR: an automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
Earlier work this paper cites.
The organization of behavior: A neuropsychological theory
Donald Olding Hebb. 2005 · 2005
Earlier work this paper cites.
A study of translation edit rate with targeted human annotation
Matthew G. Snover, Bonnie J. Dorr, Richard M. Schwartz, Linnea Micciulla, and John Makhoul. 2006 · 2006
Earlier work this paper cites.
Detecting fake content with relative entropy scoring
Thomas Lavergne, Tanguy Urvoy, and François Yvon. 2008 · 2008
Earlier work this paper cites.
Machine translation detection from monolingual web-text
Yuki Arase and Ming Zhou. 2013 · 2013
Earlier work this paper cites.
chrf: character n-gram f-score for automatic MT evaluation
Maja Popovic. 2015 · 2015
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Computer-generated text detection using machine learning: A systematic review
Daria Beresneva. 2016 · 2016
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Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Examining the transcription-writing link: Effects of handwriting fluency and spelling accuracy on writing performance via planning and translating in middle grades
Teresa Limpo, Rui A Alves, and Vincent Connelly. 2017 · 2017
Cited alongside, same era.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann N. Dauphin. 2018 · 2018
Cited alongside, same era.
Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Gpt-sentinel: Distinguishing human and chatgpt generated content
Yutian Chen, Hao Kang, Vivian Zhai, Liangze Li, Rita Singh, and Bhiksha Raj. 2023 · 2023
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Is chatgpt a highly fluent grammatical error correction system? A comprehensive evaluation
Tao Fang, Shu Yang, Kaixin Lan, Derek F. Wong, Jinpeng Hu, Lidia S. Chao, and Yue Zhang. 2023 · 2023
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Introducing palm 2
Zoubin Ghahramani. 2023 · 2023
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Towards possibilities & impossibilities of ai-generated text detection: A survey
Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, and Amrit Singh Bedi. 2023 · 2023
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How close is chatgpt to human experts? comparison corpus, evaluation, and detection
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Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
Cited alongside, same era.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2018 · 2018
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
The effect of noise on attention and performance in reading and writing tasks
Renata Adams Fernandes, Deisi Cristina Gollo Marques Vidor, and Alcyr Alves de Oliveira. 2019 · 2019
Cited alongside, same era.
GLTR: statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M. Rush. 2019 · 2019
Cited alongside, same era.
Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Biyang Guo, Xin Zhang, Ziyuan Wang, Minqi Jiang, Jinran Nie, Yuxuan Ding, Jianwei Yue, and Yupeng Wu. 2023 · 2023
Later among the works it cites.
A watermark for large language models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023 · 2023
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Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense
Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, and Mohit Iyyer. 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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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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Language model detectors are easily optimized against
Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher Manning, Chelsea Finn, and Stefano Ermon. 2023 · 2023
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Coedit: Text editing by task-specific instruction tuning
Vipul Raheja, Dhruv Kumar, Ryan Koo, and Dongyeop Kang. 2023 · 2023
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Can ai-generated text be reliably detected?
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi. 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
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Christoforos Vasilatos, Manaar Alam, Talal Rahwan, Yasir Zaki, and Michail Maniatakos. 2023 · 2023
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A survey on llm-generated text detection: Necessity, methods, and future directions
Junchao Wu, Shu Yang, Runzhe Zhan, Yulin Yuan, Derek F. Wong, and Lidia S. Chao. 2023 · 2023
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Beat llms at their own game: Zero-shot llm-generated text detection via querying chatgpt
Biru Zhu, Lifan Yuan, Ganqu Cui, Yangyi Chen, Chong Fu, Bingxiang He, Yangdong Deng, Zhiyuan Liu, Maosong Sun, and Ming Gu. 2023 · 2023
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Claude 3.5 sonnet
Anthropic. 2024 · 2024
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Introducing meta llama 3: The most capable openly available llm to date
MetaAI. 2024 · 2024
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Hello gpt-4o
OpenAI. 2024 · 2024
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Detectrl: Benchmarking llm-generated text detection in real-world scenarios
Junchao Wu, Runzhe Zhan, Derek F. Wong, Shu Yang, Xinyi Yang, Yulin Yuan, and Lidia S. Chao. 2024 · 2024
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