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The powerful ability to understand, follow, and generate complex language emerging from large language models (LLMs) makes LLM-generated text flood many areas of our daily lives at an incredible speed and is widely accepted by humans.
Real or fake? learning to discriminate machine from human generated text
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Roberta: A robustly optimized BERT pretraining approach
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Release strategies and the social impacts of language models
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Attacking neural text detectors
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The hiding virtues of ambiguity: quantifiably resilient watermarking of natural language text through synonym substitutions
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Detecting fake content with relative entropy scoring
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Sequence transduction with recurrent neural networks
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Unispach: A text-based data hiding method using unicode space characters
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Machine translation detection from monolingual web-text
Arase, Yuki and Ming Zhou. 2013 · 2013
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Toefl11: A corpus of non-native english
Blanchard, Daniel, Joel Tetreault, Derrick Higgins, Aoife Cahill, and Martin Chodorow. 2013 · 2013
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Yelp dataset challenge: Review rating prediction
Asghar, Nabiha. 2016 · 2016
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Computer-generated text detection using machine learning: A systematic review
Beresneva, Daria. 2016 · 2016
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The goldilocks principle: Reading children’s books with explicit memory representations
Hill, Felix, Antoine Bordes, Sumit Chopra, and Jason Weston. 2016 · 2016
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A corpus and cloze evaluation for deeper understanding of commonsense stories
Mostafazadeh, Nasrin, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, and James Allen. 2016 · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Rajpurkar, Pranav, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Content-preserving text watermarking through unicode homoglyph substitution
Rizzo, Stefano Giovanni, Flavio Bertini, and Danilo Montesi. 2016 · 2016
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TURINGBENCH: A benchmark environment for Turing test in the age of neural text generation
Uchendu, Adaku, Zeyu Ma, Thai Le, Rui Zhang, and Dongwon Lee. 2021 · 2016
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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
Horne, Benjamin and Sibel Adali. 2017 · 2017
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Hierarchical neural story generation
Fan, Angela, Mike Lewis, and Yann Dauphin. 2018 · 2018
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Black-box generation of adversarial text sequences to evade deep learning classifiers
Gao, Ji, Jack Lanchantin, Mary Lou Soffa, and Yanjun Qi. 2018a · 2018
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Black-box generation of adversarial text sequences to evade deep learning classifiers
Gao, Ji, Jack Lanchantin, Mary Lou Soffa, and Yanjun Qi. 2018b · 2018
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A dataset of peer reviews (PeerRead): Collection, insights and NLP applications
Kang, Dongyeop, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, and Roy Schwartz. 2018 · 2018
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The NarrativeQA reading comprehension challenge
Kočiský, Tomáš, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, and Edward Grefenstette. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Narayan, Shashi, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019a · 2019
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BERT: pre-training of deep bidirectional transformers for language understanding
Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019b · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019c · 2019
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ELI5: Long form question answering
Fan, Angela, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 2019
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GLTR: Statistical detection and visualization of generated text
Gehrmann, Sebastian, Hendrik Strobelt, and Alexander Rush. 2019 · 2019
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PubMedQA: A dataset for biomedical research question answering
Jin, Qiao, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019
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Climate Change Tweets Ids
Littman, Justin and Laura Wrubel. 2019 · 2019
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Language models are unsupervised multitask learners
Radford, Alec, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Generating natural language adversarial examples through probability weighted word saliency
Ren, Shuhuai, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Wang, Alex, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Yang, Zhilin, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
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Defending against neural fake news
Zellers, Rowan, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi. 2019b · 2019
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How effectively can machines defend against machine-generated fake news? an empirical study
Bhat, Meghana Moorthy and Srinivasan Parthasarathy. 2020 · 2020
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Language models are few-shot learners
Brown, Tom B., Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Unsupervised cross-lingual representation learning at scale
Conneau, Alexis, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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RoFT: A tool for evaluating human detection of machine-generated text
Dugan, Liam, Daphne Ippolito, Arun Kirubarajan, and Chris Callison-Burch. 2020 · 2020
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Explainable ai in industry: Practical challenges and lessons learned
Gade, Krishna, Sahin Geyik, Krishnaram Kenthapadi, Varun Mithal, and Ankur Taly. 2020 · 2020
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Generative adversarial networks
Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
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Wiki-40B: Multilingual language model dataset
Guo, Mandy, Zihang Dai, Denny Vrandečić, and Rami Al-Rfou. 2020 · 2020
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The curious case of neural text degeneration
Holtzman, Ari, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Automatic detection of generated text is easiest when humans are fooled
Ippolito, Daphne, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck. 2020 · 2020
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Automatic detection of machine generated text: A critical survey
Jawahar, Ganesh, Muhammad Abdul-Mageed, and Laks Lakshmanan, V.S. 2020 · 2020
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Tinybert: Distilling BERT for natural language understanding
Jiao, Xiaoqi, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020 · 2020
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SLM: Learning a discourse language representation with sentence unshuffling
Lee, Haejun, Drew A. Hudson, Kangwook Lee, and Christopher D. Manning. 2020 · 2020
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Textattack: A framework for adversarial attacks, data augmentation, and adversarial training in NLP
Morris, John X., Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, and Yanjun Qi. 2020 · 2020
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Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Murtaza, Ghulam, Liyana Shuib, Ainuddin Wahid Abdul Wahab, Ghulam Mujtaba, Ghulam Mujtaba, Henry Friday Nweke, Mohammed Ali Al-garadi, Fariha Zulfiqar, Ghulam Raza, and Nor Aniza Azmi. 2020 · 2020
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Pre-trained models for natural language processing: A survey
Qiu, Xipeng, Tianxiang Sun, Yige Xu, Yunfan Shao, Ning Dai, and Xuanjing Huang. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, Colin, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Robustness to modification with shared words in paraphrase identification
Shi, Zhouxing and Minlie Huang. 2020 · 2020
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Authorship attribution for neural text generation
Uchendu, Adaku, Thai Le, Kai Shu, and Dongwon Lee. 2020 · 2020
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Fake news detection with generated comments for news articles
Yanagi, Yuta, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, and Akihiko Ohsuga. 2020 · 2020
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Neural deepfake detection with factual structure of text
Zhong, Wanjun, Duyu Tang, Zenan Xu, Ruize Wang, Nan Duan, Ming Zhou, Jiahai Wang, and Jian Yin. 2020 · 2020
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Adversarial watermarking transformer: Towards tracing text provenance with data hiding
Abdelnabi, Sahar and Mario Fritz. 2021 · 2021
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Epistemic defenses against scientific and empirical adversarial ai attacks
Aliman, Nadisha Marie and Leon Kester. 2021 · 2021
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All that’s ’human’ is not gold: Evaluating human evaluation of generated text
Clark, Elizabeth, Tal August, Sofia Serrano, Nikita Haduong, Suchin Gururangan, and Noah A. Smith. 2021b · 2021
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Parrot: Paraphrase generation for nlu
Damodaran, Prithiviraj. 2021 · 2021
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TweepFake: About detecting deepfake tweets
Fagni, Tiziano, Fabrizio Falchi, Margherita Gambini, Antonio Martella, and Maurizio Tesconi. 2021 · 2021
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Unsupervised and distributional detection of machine-generated text
Gallé, Matthias, Jos Rozen, Germán Kruszewski, and Hady Elsahar. 2021 · 2021
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SimCSE: Simple contrastive learning of sentence embeddings
Gao, Tianyu, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Characterizing social spambots by their human traits
Giorgi, Salvatore, Lyle Ungar, and H. Andrew Schwartz. 2021 · 2021
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Cogie: An information extraction toolkit for bridging texts and cognet
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Pushing on text readability assessment: A transformer meets handcrafted linguistic features
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Scigen: a dataset for reasoning-aware text generation from scientific tables
Moosavi, Nafise Sadat, Andreas Rücklé, Dan Roth, and Iryna Gurevych. 2021 · 2021
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Muric, G, Y Wu, and E Ferrara. 2021 · 2021
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Ethical and social risks of harm from language models (2021)
Weidinger, Laura, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, et al. 2021 · 2021
A watermark for large language models
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Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense
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Robust distortion-free watermarks for language models
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How reliable are ai-generated-text detectors? an assessment framework using evasive soft prompts
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Mutation-based adversarial attacks on neural text detectors
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Gpt detectors are biased against non-native english writers
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Large language models can be guided to evade ai-generated text detection
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