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The spread of fake news has emerged as a critical challenge, undermining trust and posing threats to society.
Language models are few-shot learners
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Roberta: A robustly optimized bert pretraining approach
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Comparing individual means in the analysis of variance
John W Tukey. 1949 · 1949
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Interrater reliability: the kappa statistic
Mary L McHugh. 2012 · 2012
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The current state of fake news: challenges and opportunities
Álvaro Figueira and Luciana Oliveira. 2017 · 2017
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This just in: Fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news
Benjamin Horne and Sibel Adali. 2017 · 2017
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Nela-gt-2018: A large multi-labelled news dataset for the study of misinformation in news articles
Jeppe Nørregaard, Benjamin D Horne, and Sibel Adalı. 2019 · 2018
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The brexit botnet and user-generated hyperpartisan news
Marco T Bastos and Dan Mercea. 2019 · 2019
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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. 2019 · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova. 2019 · 2019
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Fake news detection using machine learning approaches: A systematic review
Syed Ishfaq Manzoor, Jimmy Singla, et al. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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An exploratory study of “fake news” and media trust in kenya, nigeria and south africa
Herman Wasserman and Dani Madrid-Morales. 2019 · 2019
Cited alongside, same era.
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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Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2020 · 2020
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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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Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Cited alongside, same era.
The limitations of stylometry for detecting machine-generated fake news
Integrating pattern-and fact-based fake news detection via model preference learning
Qiang Sheng, Xueyao Zhang, Juan Cao, and Lei Zhong. 2021 · 2021
Later among the works it cites.
Fact-enhanced synthetic news generation
Kai Shu, Yichuan Li, Kaize Ding, and Huan Liu. 2021 · 2021
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Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, et al. 2021 · 2021
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Faking fake news for real fake news detection: Propaganda-loaded training data generation
Kung-Hsiang Huang, Kathleen McKeown, Preslav Nakov, Yejin Choi, and Heng Ji. 2022 · 2022
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Russian-ukraine 2022 war: A review of the economic impact of russian-ukraine crisis on the usa, uk, canada, and europe
Ruth Endam Mbah and Divine Forcha Wasum. 2022 · 2022
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Tal Schuster, Roei Schuster, Darsh J Shah, and Regina Barzilay. 2020 · 2020
Cited alongside, same era.
Fakenewsnet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media
Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, and Huan Liu. 2020 · 2020
Cited alongside, same era.
Inoculating against fake news about covid-19
Sander van Der Linden, Jon Roozenbeek, and Josh Compton. 2020 · 2020
Cited alongside, same era.
Recent advances in adversarial training for adversarial robustness
Tao Bai, Jinqi Luo, Jun Zhao, Bihan Wen, and Qian Wang. 2021 · 2021
Cited alongside, same era.
A survey of data augmentation approaches for nlp
Steven Y Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, and Eduard Hovy. 2021 · 2021
Cited alongside, same era.
Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
Cited alongside, same era.
A benchmark study of machine learning models for online fake news detection
Junaed Younus Khan, Md Tawkat Islam Khondaker, Sadia Afroz, Gias Uddin, and Anindya Iqbal. 2021 · 2021
Cited alongside, same era.
Later among the works it cites.
Domain adaptive fake news detection via reinforcement learning
Ahmadreza Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle V Mancenido, and Huan Liu. 2022 · 2022
Later among the works it cites.
Threat scenarios and best practices to detect neural fake news
Artidoro Pagnoni, Martin Graciarena, and Yulia Tsvetkov. 2022 · 2022
Later among the works it cites.
Hans WA Hanley and Zakir Durumeric. 2023 · 2023
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Faking fake news for real fake news detection: Propaganda-loaded training data generation
Kung-Hsiang Huang, Kathleen McKeown, Preslav Nakov, Yejin Choi, and Heng Ji. 2023 · 2023
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Starcoder: may the source be with you!
Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al. 2023 · 2023
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On the risk of misinformation pollution with large language models
Yikang Pan, Liangming Pan, Wenhu Chen, Preslav Nakov, Min-Yen Kan, and William Yang Wang. 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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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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