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Advances in Large Language Models (e.g., GPT-4, LLaMA) have improved the generation of coherent sentences resembling human writing on a large scale, resulting in the creation of so-called deepfake texts.
Language models are few-shot learners
Brown, T.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J. D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 1901
Earlier work this paper cites.
Real or fake? learning to discriminate machine from human generated text
Bakhtin, A.; Gross, S.; Ott, M.; Deng, Y.; Ranzato, M.; and Szlam, A. 2019 · 1906
Earlier work this paper cites.
Task and technology fit: a comparison of two technologies for synchronous and asynchronous group communication
Shirani, A. I.; Tafti, M. H.; and Affisco, J. F. 1999 · 1999
Earlier work this paper cites.
The wisdom of crowds
Surowiecki, J. 2005 · 2005
Earlier work this paper cites.
A study of synchronous versus asynchronous collaboration in an online business writing class
Mabrito, M. 2006 · 2006
Earlier work this paper cites.
Why do humans reason? Arguments for an argumentative theory
Mercier, H.; and Sperber, D. 2011 · 2011
Earlier work this paper cites.
Tracking changes in collaborative writing: edits, visibility and group maintenance
Birnholtz, J.; and Ibara, S. 2012 · 2012
Earlier work this paper cites.
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
Uchendu, A.; Ma, Z.; Le, T.; Zhang, R.; and Lee, D. 2021 · 2016
Earlier work this paper cites.
Truth inference in crowdsourcing: Is the problem solved?
Zheng, Y.; Li, G.; Li, Y.; Shan, C.; and Cheng, R. 2017 · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
Earlier work this paper cites.
A brief review of independent, dependent and one sample t-test
Gerald, B. 2018 · 2018
Earlier work this paper cites.
GLTR: Statistical Detection and Visualization of Generated Text
Gehrmann, S.; Strobelt, H.; and Rush, A. M. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
Earlier work this paper cites.
Trust it or not: Effects of machine-learning warnings in helping individuals mitigate misinformation
Seo, H.; Xiong, A.; and Lee, D. 2019 · 2019
Earlier work this paper cites.
Best practices for the human evaluation of automatically generated text
Van Der Lee, C.; Gatt, A.; Van Miltenburg, E.; Wubben, S.; and Krahmer, E. 2019 · 2019
Earlier work this paper cites.
Defending against neural fake news
Zellers, R.; Holtzman, A.; Rashkin, H.; Bisk, Y.; Farhadi, A.; Roesner, F.; and Choi, Y. 2019 · 2019
Earlier work this paper cites.
Enabling Language Models to Fill in the Blanks
Donahue, C.; Lee, M.; and Liang, P. 2020 · 2020
Earlier work this paper cites.
RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text
Dugan, L.; Ippolito, D.; Kirubarajan, A.; and Callison-Burch, C. 2020 · 2020
Cited alongside, same era.
Automatic Detection of Generated Text is Easiest when Humans are Fooled
Ippolito, D.; Duckworth, D.; Callison-Burch, C.; and Eck, D. 2020 · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
Cited alongside, same era.
Authorship attribution for neural text generation
Uchendu, A.; Le, T.; Shu, K.; and Lee, D. 2020 · 2020
Cited alongside, same era.
Neural Deepfake Detection with Factual Structure of Text
Zhong, W.; Tang, D.; Xu, Z.; Wang, R.; Duan, N.; Zhou, M.; Wang, J.; and Yin, J. 2020 · 2020
Cited alongside, same era.
Automatic Detection of Entity-Manipulated Text using Factual Knowledge
Jawahar, G.; Abdul-Mageed, M.; and Lakshmanan, L. 2022 · 2022
Later among the works it cites.
Human and Technological Infrastructures of Fact-Checking
Juneja, P.; and Mitra, T. 2022 · 2022
Later among the works it cites.
Liu, X.; Zhang, Z.; Wang, Y.; Lan, Y.; and Shen, C. 2022 · 2022
Later among the works it cites.
MAUVE Scores for Generative Models: Theory and Practice
Pillutla, K.; Liu, L.; Thickstun, J.; Welleck, S.; Swayamdipta, S.; Zellers, R.; Oh, S.; Choi, Y.; and Harchaoui, Z. 2022 · 2022
Later among the works it cites.
Deepfake generation and detection, a survey
Zhang, T. 2022 · 2022
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Chen, M.; Tworek, J.; Jun, H.; Yuan, Q.; Pinto, H. P. d. O.; Kaplan, J.; Edwards, H.; Burda, Y.; Joseph, N.; Brockman, G.; et al. 2021 · 2021
Cited alongside, same era.
All That’s ‘Human’ Is Not Gold: Evaluating Human Evaluation of Generated Text
Clark, E.; August, T.; Serrano, S.; Haduong, N.; Gururangan, S.; and Smith, N. A. 2021 · 2021
Cited alongside, same era.
TweepFake: About detecting deepfake tweets
Fagni, T.; Falchi, F.; Gambini, M.; Martella, A.; and Tesconi, M. 2021 · 2021
Cited alongside, same era.
Feature-based detection of automated language models: tackling GPT-2, GPT-3 and Grover
Fröhling, L.; and Zubiaga, A. 2021 · 2021
Cited alongside, same era.
Unsupervised and Distributional Detection of Machine-Generated Text
Gallé, M.; Rozen, J.; Kruszewski, G.; and Elsahar, H. 2021 · 2021
Cited alongside, same era.
Artificial Text Detection via Examining the Topology of Attention Maps
Kushnareva, L.; Cherniavskii, D.; Mikhailov, V.; Artemova, E.; Barannikov, S.; Bernstein, A.; Piontkovskaya, I.; Piontkovski, D.; and Burnaev, E. 2021 · 2021
Cited alongside, same era.
An information divergence measure between neural text and human text
Pillutla, K.; Swayamdipta, S.; Zellers, R.; Thickstun, J.; Welleck, S.; Choi, Y.; and Harchaoui, Z. 2021 · 2021
Cited alongside, same era.
GPT-2 Output Detector Demo
Huggingface. 2023 · 2023
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Do language models plagiarize?
Lee, J.; Le, T.; Chen, J.; and Lee, D. 2023 · 2023
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CekFakta: Collaborative Fact-Checking in Indonesias
Liu, I. J. 2018 · 2023
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Detectgpt: Zero-shot machine-generated text detection using probability curvature
Mitchell, E.; Lee, Y.; Khazatsky, A.; Manning, C. D.; and Finn, C. 2023 · 2023
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OpenAI. 2023 · 2023
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Deepfake Text Detection: Limitations and Opportunities
Pu, J.; Sarwar, Z.; Abdullah, S. M.; Rehman, A.; Kim, Y.; Bhattacharya, P.; Javed, M.; Viswanath, B.; Tech, V.; and Pakistan, L. 2023 · 2023
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Parachute: Evaluating interactive human-lm co-writing systems
Shen, H.; and Wu, T. 2023 · 2023
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Model evaluation for extreme risks
Shevlane, T.; Farquhar, S.; Garfinkel, B.; Phuong, M.; Whittlestone, J.; Leung, J.; Kokotajlo, D.; Marchal, N.; Anderljung, M.; Kolt, N.; et al. 2023 · 2023
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Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective
Uchendu, A.; Le, T.; and Lee, D. 2023 · 2023
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ScatterShot: Interactive In-context Example Curation for Text Transformation
Wu, S.; Shen, H.; Weld, D. S.; Heer, J.; and Ribeiro, M. T. 2023 · 2023
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Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News
Tan, R.; Plummer, B.; and Saenko, K. 2020 · 2081
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