Fetching the paper…
Reading the bibliography…
Accurate attribution of authorship is crucial for maintaining the integrity of digital content, improving forensic investigations, and mitigating the risks of misinformation and plagiarism.
Inference in an authorship problem: A comparative study of discrimination methods applied to the authorship of the disputed Federalist Papers
Frederick Mosteller and David L Wallace. 1963 · 1963
Earlier work this paper cites.
Authorship attribution
David I Holmes. 1994 · 1994
Earlier work this paper cites.
The state of authorship attribution studies: Some problems and solutions
Joseph Rudman. 1997 · 1997
Earlier work this paper cites.
Natural language watermarking: Design, analysis, and a proof-of-concept implementation. In Information Hiding: 4th International Workshop, IH 2001 Pittsburgh, PA, USA, April 25–27, 2001 Proceedings 4 . Springer, 185–200
Mikhail J Atallah, Victor Raskin, Michael Crogan, Christian Hempelmann, Florian Kerschbaum, Dina Mohamed, and Sanket Naik. 2001 · 2001
Earlier work this paper cites.
Gender, genre, and writing style in formal written texts
Shlomo Argamon, Moshe Koppel, Jonathan Fine, and Anat Rachel Shimoni. 2003 · 2003
Earlier work this paper cites.
The enron corpus: A new dataset for email classification research. In Machine Learning: ECML 2004: 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004. Proceedings 15 . Springer, 217–226
Bryan Klimt and Yiming Yang. 2004 · 2004
Earlier work this paper cites.
Who’s at the keyboard? Authorship attribution in digital evidence investigations
Carole E Chaski. 2005 · 2005
Earlier work this paper cites.
Determining an author’s native language by mining a text for errors. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining . 624–628
Moshe Koppel, Jonathan Schler, and Kfir Zigdon. 2005 · 2005
Earlier work this paper cites.
Author identification on the large scale. In Proceedings of the 2005 Meeting of the Classification Society of North America (CSNA)
David Madigan, Alexander Genkin, David D Lewis, Shlomo Argamon, Dmitriy Fradkin, and Li Ye. 2005b · 2005
Earlier work this paper cites.
On compression-based text classification. In Advances in Information Retrieval: 27th European Conference on IR Research, ECIR 2005, Santiago de Compostela, Spain, March 21-23, 2005. Proceedings 27 . Springer, 300–314
Yuval Marton, Ning Wu, and Lisa Hellerstein. 2005 · 2005
Earlier work this paper cites.
Natural language watermarking. In Security, Steganography, and Watermarking of Multimedia Contents VII , Vol. 5681. SPIE, 441–452
Mercan Topkara, Cuneyt M Taskiran, and Edward J Delp III. 2005 · 2005
Earlier work this paper cites.
Authorship attribution with thousands of candidate authors. In Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval . 659–660
Moshe Koppel, Jonathan Schler, Shlomo Argamon, and Eran Messeri. 2006 · 2006
Earlier work this paper cites.
Plagiarism detection without reference collections. In Advances in Data Analysis: Proceedings of the 30 th Annual Conference of the Gesellschaft für Klassifikation eV, Freie Universität Berlin, March 8–10, 2006 . Springer, 359–366
Sven Meyer zu Eissen, Benno Stein, and Marion Kulig. 2007 · 2006
Earlier work this paper cites.
Effects of age and gender on blogging.. In AAAI spring symposium: Computational approaches to analyzing weblogs , Vol. 6. 199–205
Jonathan Schler, Moshe Koppel, Shlomo Argamon, and James W Pennebaker. 2006 · 2006
Earlier work this paper cites.
Authorship attribution. In 2007 22nd international symposium on computer and information sciences . IEEE, 1–5
Ilker Nadi Bozkurt, Ozgur Baghoglu, and Erkan Uyar. 2007 · 2007
Earlier work this paper cites.
Bigrams of syntactic labels for authorship discrimination of short texts
Graeme Hirst and Ol’ga Feiguina. 2007 · 2007
Earlier work this paper cites.
Opinion spam and analysis. In Proceedings of the International Conference on Web Search and Web Data Mining, WSDM 2008, Palo Alto, California, USA, February 11-12, 2008 , Marc Najork, Andrei Z. Broder, and Soumen Chakrabarti (Eds.). ACM, 219–230
Nitin Jindal and Bing Liu. 2008 · 2008
Earlier work this paper cites.
Authorship attribution in law enforcement scenarios
Moshe Koppel, Jonathan Schler, and Eran Messeri. 2008 · 2008
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.
Author identification: Using text sampling to handle the class imbalance problem
Efstathios Stamatatos. 2008 · 2008
Earlier work this paper cites.
Automatically profiling the author of an anonymous text
Shlomo Argamon, Moshe Koppel, James W Pennebaker, and Jonathan Schler. 2009 · 2009
Earlier work this paper cites.
Person Identification from Text and Speech Genre Samples. In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009) . Association for Computational Linguistics, Athens, Greece, 336–344
Jade Goldstein-Stewart, Ransom Winder, and Roberta Sabin. 2009 · 2009
Earlier work this paper cites.
A review of digital watermarking techniques for text documents. In 2009 International Conference on Information and Multimedia Technology . IEEE, 230–234
Zunera Jalil and Anwar M Mirza. 2009 · 2009
Earlier work this paper cites.
Natural language watermarking via morphosyntactic alterations
Hasan Mesut Meral, Bülent Sankur, A Sumru Özsoy, Tunga Güngör, and Emre Sevinç. 2009 · 2009
Earlier work this paper cites.
A survey of modern authorship attribution methods
Efstathios Stamatatos. 2009 · 2009
Earlier work this paper cites.
A theory of learning from different domains
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan. 2010 · 2010
Earlier work this paper cites.
Domain Independent Authorship Attribution without Domain Adaptation. In Proceedings of the International Conference Recent Advances in Natural Language Processing 2011 . Association for Computational Linguistics, Hissar, Bulgaria, 309–315
Rohith Menon and Yejin Choi. 2011 · 2011
Earlier work this paper cites.
Finding Deceptive Opinion Spam by Any Stretch of the Imagination. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Portland, Oregon, USA, 309–319
Myle Ott, Yejin Choi, Claire Cardie, and Jeffrey T. Hancock. 2011 · 2011
Earlier work this paper cites.
Ghosts from the high court’s past: Evidence from computational linguistics for Dixon ghosting for Mctiernan and rich
Yanir Seroussi, Russell Smyth, and Ingrid Zukerman. 2011 · 2011
Earlier work this paper cites.
Plagiarism and authorship analysis: introduction to the special issue
Efstathios Stamatatos and Moshe Koppel. 2011 · 2011
Earlier work this paper cites.
Detecting hoaxes, frauds, and deception in writing style online. In 2012 IEEE Symposium on Security and Privacy . IEEE, 461–475
Sadia Afroz, Michael Brennan, and Rachel Greenstadt. 2012 · 2012
Earlier work this paper cites.
The handbook of language variation and change
Jack K Chambers, Peter Trudgill, and Natalie Schilling-Estes. 2013 · 2013
Earlier work this paper cites.
The secret life of pronouns. what our words say about us
John Nerbonne. 2014 · 2014
Earlier work this paper cites.
Zipf’s word frequency law in natural language: A critical review and future directions
Steven T Piantadosi. 2014 · 2014
Earlier work this paper cites.
Authorship Attribution with Topic Models
Yanir Seroussi, Ingrid Zukerman, and Fabian Bohnert. 2014 · 2014
Earlier work this paper cites.
Breaking the closed-world assumption in stylometric authorship attribution. In Advances in Digital Forensics X: 10th IFIP WG 11.9 International Conference, Vienna, Austria, January 8-10, 2014, Revised Selected Papers 10 . Springer, 185–205
Ariel Stolerman, Rebekah Overdorf, Sadia Afroz, and Rachel Greenstadt. 2014 · 2014
Earlier work this paper cites.
Author identification using multi-headed recurrent neural networks
Douglas Bagnall. 2015 · 2015
Earlier work this paper cites.
Does size matter? Authorship attribution, small samples, big problem
Maciej Eder. 2015 · 2015
Earlier work this paper cites.
Explaining and Harnessing Adversarial Examples. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings , Yoshua Bengio and Yann LeCun (Eds.)
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy. 2015 · 2015
Earlier work this paper cites.
The development and psychometric properties of LIWC2015
James W Pennebaker, Ryan L Boyd, Kayla Jordan, and Kate Blackburn. 2015 · 2015
Earlier work this paper cites.
Computer-generated text detection using machine learning: A systematic review. In Natural Language Processing and Information Systems: 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings 21 . Springer, 421–426
Daria Beresneva. 2016 · 2016
Earlier work this paper cites.
Authorship attribution for social media forensics
Anderson Rocha, Walter J Scheirer, Christopher W Forstall, Thiago Cavalcante, Antonio Theophilo, Bingyu Shen, Ariadne RB Carvalho, and Efstathios Stamatatos. 2016 · 2016
Earlier work this paper cites.
Sebastian Ruder, Parsa Ghaffari, and John G Breslin. 2016 · 2016
Earlier work this paper cites.
Authorship verification: a review of recent advances
Efstathios Stamatatos. 2016 · 2016
Earlier work this paper cites.
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation. In Findings of the Association for Computational Linguistics: EMNLP 2021 . Association for Computational Linguistics, Punta Cana, Dominican Republic, 2001–2016
Adaku Uchendu, Zeyu Ma, Thai Le, Rui Zhang, and Dongwon Lee. 2021 · 2016
Earlier work this paper cites.
Human behavior and the principle of least effort: An introduction to human ecology
George Kingsley Zipf. 2016 · 2016
Earlier work this paper cites.
Authorship verification applied to detection of compromised accounts on online social networks: A continuous approach
Sylvio Barbon, Rodrigo Augusto Igawa, and Bruno Bogaz Zarpelão. 2017 · 2017
Earlier work this paper cites.
Stylometric authorship attribution of collaborative documents. In Cyber Security Cryptography and Machine Learning: First International Conference, CSCML 2017, Beer-Sheva, Israel, June 29-30, 2017, Proceedings 1 . Springer, 115–135
Edwin Dauber, Rebekah Overdorf, and Rachel Greenstadt. 2017 · 2017
Earlier work this paper cites.
Bag of Tricks for Efficient Text Classification. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers . Association for Computational Linguistics, Valencia, Spain, 427–431
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
Earlier work this paper cites.
End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017 , Carles Sierra (Ed.). ijcai.org, 2237–2243
Zheng Li, Yu Zhang, Ying Wei, Yuxiang Wu, and Qiang Yang. 2017 · 2017
Earlier work this paper cites.
A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA , Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 4765–4774
Scott M. Lundberg and Su-In Lee. 2017 · 2017
Earlier work this paper cites.
Surveying stylometry techniques and applications
Tempestt Neal, Kalaivani Sundararajan, Aneez Fatima, Yiming Yan, Yingfei Xiang, and Damon Woodard. 2017 · 2017
Earlier work this paper cites.
Identifying computer-generated text using statistical analysis. In 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) . IEEE, 1504–1511
Hoang-Quoc Nguyen-Son, Ngoc-Dung T Tieu, Huy H Nguyen, Junichi Yamagishi, and Isao Echi Zen. 2017 · 2017
Earlier work this paper cites.
Deep learning based authorship identification
Chen Qian, Tianchang He, and Rao Zhang. 2017 · 2017
Earlier work this paper cites.
Convolutional Neural Networks for Authorship Attribution of Short Texts. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers . Association for Computational Linguistics, Valencia, Spain, 669–674
Prasha Shrestha, Sebastian Sierra, Fabio González, Manuel Montes, Paolo Rosso, and Thamar Solorio. 2017 · 2017
Earlier work this paper cites.
User identity linkage across online social networks: A review
Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, and Huan Liu. 2017 · 2017
Earlier work this paper cites.
Classification for authorship of tweets by comparing logistic regression and naive bayes classifiers. In 2018 IEEE International Conference on Information Reuse and Integration (IRI) . IEEE, 269–276
Opeyemi Aborisade and Mohd Anwar. 2018 · 2018
Earlier work this paper cites.
Computational forensic authorship analysis: Promises and pitfalls
Shlomo Argamon. 2018 · 2018
Earlier work this paper cites.
Universal Language Model Fine-tuning for Text Classification. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Melbourne, Australia, 328–339
Jeremy Howard and Sebastian Ruder. 2018 · 2018
Earlier work this paper cites.
Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, Brussels, Belgium, 1797–1807
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
Earlier work this paper cites.
Abhay Sharma, Ananya Nandan, and Reetika Ralhan. 2018 · 2018
Earlier work this paper cites.
What represents “style” in authorship attribution?. In Proceedings of the 27th International Conference on Computational Linguistics . Association for Computational Linguistics, Santa Fe, New Mexico, USA, 2814–2822
Kalaivani Sundararajan and Damon Woodard. 2018 · 2018
Earlier work this paper cites.
Syntax Encoding with Application in Authorship Attribution. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, Brussels, Belgium, 2742–2753
Richong Zhang, Zhiyuan Hu, Hongyu Guo, and Yongyi Mao. 2018 · 2018
Earlier work this paper cites.
Learning Invariant Representations of Social Media Users. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . Association for Computational Linguistics, Hong Kong, China, 1684–1695
Nicholas Andrews and Marcus Bishop. 2019 · 2019
Earlier work this paper cites.
Cross-Domain Authorship Attribution Combining Instance Based and Profile-Based Features.. In CLEF (Working Notes)
Andrea Bacciu, Massimo La Morgia, Alessandro Mei, Eugenio Nerio Nemmi, Valerio Neri, and Julinda Stefa. 2019 · 2019
Earlier work this paper cites.
Explainable Authorship Verification in Social Media via Attention-based Similarity Learning. In 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, December 9-12, 2019 . IEEE, 36–45
Benedikt T. Boenninghoff, Steffen Hessler, Dorothea Kolossa, and Robert M. Nickel. 2019a · 2019
Earlier work this paper cites.
Similarity Learning for Authorship Verification in Social Media. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019 . IEEE, 2457–2461
Benedikt T. Boenninghoff, Robert M. Nickel, Steffen Zeiler, and Dorothea Kolossa. 2019b · 2019
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . Association for Computational Linguistics, Minneapolis, Minnesota, 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
GLTR: Statistical Detection and Visualization of Generated Text. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations . Association for Computational Linguistics, Florence, Italy, 111–116
Sebastian Gehrmann, Hendrik Strobelt, and Alexander Rush. 2019 · 2019
Earlier work this paper cites.
OpenWebText Corpus
Aaron Gokaslan and Vanya Cohen. 2019 · 2019
Earlier work this paper cites.
A survey on stylometric text features. In 2019 25th Conference of Open Innovations Association (FRUCT) . IEEE, 184–195
Ksenia Lagutina, Nadezhda Lagutina, Elena Boychuk, Inna Vorontsova, Elena Shliakhtina, Olga Belyaeva, Ilya Paramonov, and PG Demidov. 2019 · 2019
Earlier work this paper cites.
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 · 2019
Cited alongside, same era.
Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . Association for Computational Linguistics, Hong Kong, China, 188–197
Jianmo Ni, Jiacheng Li, and Julian McAuley. 2019 · 2019
Cited alongside, same era.
Improving author verification based on topic modeling
Nektaria Potha and Efstathios Stamatatos. 2019 · 2019
Cited alongside, same era.
Explain Yourself! Leveraging Language Models for Commonsense Reasoning. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics . Association for Computational Linguistics, Florence, Italy, 4932–4942
Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
Megha Chakraborty, SM Tonmoy, SM Zaman, Krish Sharma, Niyar R Barman, Chandan Gupta, Shreya Gautam, Tanay Kumar, Vinija Jain, Aman Chadha, et al · 2023
Later among the works it cites.
On the possibilities of ai-generated text detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, and Furong Huang. 2023a · 2023
Later among the works it cites.
Gpt-sentinel: Distinguishing human and chatgpt generated content
Yutian Chen, Hao Kang, Vivian Zhai, Liangze Li, Rita Singh, and Bhiksha Raj. 2023a · 2023
Later among the works it cites.
Token prediction as implicit classification to identify LLM-generated text
Yutian Chen, Hao Kang, Vivian Zhai, Liangze Li, Rita Singh, and Bhiksha Raj. 2023b · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin. 2019 · 2019
Cited alongside, same era.
Do Massively Pretrained Language Models Make Better Storytellers?. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) . Association for Computational Linguistics, Hong Kong, China, 843–861
Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola, and Christopher D. Manning. 2019 · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Best practices for the human evaluation of automatically generated text. In Proceedings of the 12th International Conference on Natural Language Generation . Association for Computational Linguistics, Tokyo, Japan, 355–368
Chris van der Lee, Albert Gatt, Emiel van Miltenburg, Sander Wubben, and Emiel Krahmer. 2019 · 2019
Cited alongside, same era.
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations . Association for Computational Linguistics, Hong Kong, China, 7–12
Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, and Sameer Singh. 2019 · 2019
Cited alongside, same era.
Exclusive: FBI document warns conspiracy theories are a new domestic terrorism threat
Jana Winter. 2019 · 2019
Cited alongside, same era.
Defending Against Neural Fake News. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada , Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d’Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 9051–9062
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi. 2019 · 2019
Cited alongside, same era.
Cross-domain authorship attribution using pre-trained language models. In Artificial Intelligence Applications and Innovations: 16th IFIP WG 12.5 International Conference, AIAI 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, Part I 16 . Springer, 255–266
Georgios Barlas and Efstathios Stamatatos. 2020 · 2020
Cited alongside, same era.
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
Later among the works it cites.
Machine-generated text: A comprehensive survey of threat models and detection methods
Evan Crothers, Nathalie Japkowicz, and Herna L Viktor. 2023 · 2023
Later among the works it cites.
Real or fake text?: Investigating human ability to detect boundaries between human-written and machine-generated text. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 37. 12763–12771
Liam Dugan, Daphne Ippolito, Arun Kirubarajan, Sherry Shi, and Chris Callison-Burch. 2023 · 2023
Later among the works it cites.
Efficient Black-Box Adversarial Attacks on Neural Text Detectors
Vitalii Fishchuk and Daniel Braun. 2023 · 2023
Later among the works it cites.
Josh A. Goldstein, Girish Sastry, Micah Musser, Renee DiResta, Matthew Gentzel, and Katerina Sedova. 2023 · 2023
Later among the works it cites.
How close is chatgpt to human experts? comparison corpus, evaluation, and detection
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.
Large language models can be used to effectively scale spear phishing campaigns
Julian Hazell. 2023 · 2023
Later among the works it cites.
Mgtbench: Benchmarking machine-generated text detection
Xinlei He, Xinyue Shen, Zeyuan Chen, Michael Backes, and Yang Zhang. 2023 · 2023
Later among the works it cites.
Semstamp: A semantic watermark with paraphrastic robustness for text generation
Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, and Yulia Tsvetkov. 2023 · 2023
Later among the works it cites.
Radar: Robust ai-text detection via adversarial learning
Xiaomeng Hu, Pin-Yu Chen, and Tsung-Yi Ho. 2023 · 2023
Later among the works it cites.
A watermark for large language models. In International Conference on Machine Learning . PMLR, 17061–17084
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023 · 2023
Later among the works it cites.
Exploring Semantic Perturbations on Grover
Pranav Kulkarni, Ziqing Ji, Yan Xu, Marko Neskovic, and Kevin Nolan. 2023 · 2023
Later among the works it cites.
Neural Authorship Attribution: Stylometric Analysis on Large Language Models
Tharindu Kumarage and Huan Liu. 2023 · 2023
Later among the works it cites.
How reliable are ai-generated-text detectors? an assessment framework using evasive soft prompts
Tharindu Kumarage, Paras Sheth, Raha Moraffah, Joshua Garland, and Huan Liu. 2023 · 2023
Later among the works it cites.
Origin tracing and detecting of llms
Linyang Li, Pengyu Wang, Ke Ren, Tianxiang Sun, and Xipeng Qiu. 2023b · 2023
Later among the works it cites.
MAGE: Machine-generated Text Detection in the Wild
Yafu Li, Qintong Li, Leyang Cui, Wei Bi, Zhilin Wang, Longyue Wang, Linyi Yang, Shuming Shi, and Yue Zhang. 2023a · 2023
Later among the works it cites.
GPT detectors are biased against non-native English writers
Weixin Liang, Mert Yuksekgonul, Yining Mao, Eric Wu, and James Zou. 2023 · 2023
Later among the works it cites.
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. 2023b · 2023
Later among the works it cites.
Zeyan Liu, Zijun Yao, Fengjun Li, and Bo Luo. 2023a · 2023
Later among the works it cites.
Large language models can be guided to evade ai-generated text detection
Ning Lu, Shengcai Liu, Rui He, Qi Wang, Yew-Soon Ong, and Ke Tang. 2023 · 2023
Later among the works it cites.
ChatGPT and a new academic reality: Artificial Intelligence-written research papers and the ethics of the large language models in scholarly publishing
Brady D Lund, Ting Wang, Nishith Reddy Mannuru, Bing Nie, Somipam Shimray, and Ziang Wang. 2023 · 2023
Later among the works it cites.
MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark
Dominik Macko, Robert Moro, Adaku Uchendu, Jason Samuel Lucas, Michiharu Yamashita, Matúš Pikuliak, Ivan Srba, Thai Le, Dongwon Lee, Jakub Simko, et al · 2023
Later among the works it cites.
Smaller language models are better black-box machine-generated text detectors
Niloofar Mireshghallah, Justus Mattern, Sicun Gao, Reza Shokri, and Taylor Berg-Kirkpatrick. 2023 · 2023
Later among the works it cites.
Detectgpt: Zero-shot machine-generated text detection using probability curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D Manning, and Chelsea Finn. 2023 · 2023
Later among the works it cites.
Distinguishing Fact from Fiction: A Benchmark Dataset for Identifying Machine-Generated Scientific Papers in the LLM Era.. In Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023) . 190–207
Edoardo Mosca, Mohamed Hesham Ibrahim Abdalla, Paolo Basso, Margherita Musumeci, and Georg Groh. 2023 · 2023
Later among the works it cites.
Learning Interpretable Style Embeddings via Prompting LLMs
Ajay Patel, Delip Rao, and Chris Callison-Burch. 2023 · 2023
Later among the works it cites.
Deepfake text detection: Limitations and opportunities. In 2023 IEEE Symposium on Security and Privacy (SP) . IEEE, 1613–1630
Jiameng Pu, Zain Sarwar, Sifat Muhammad Abdullah, Abdullah Rehman, Yoonjin Kim, Parantapa Bhattacharya, Mobin Javed, and Bimal Viswanath. 2023a · 2023
Later among the works it cites.
On the zero-shot generalization of machine-generated text detectors
Xiao Pu, Jingyu Zhang, Xiaochuang Han, Yulia Tsvetkov, and Tianxing He. 2023b · 2023
Later among the works it cites.
Can ai-generated text be reliably detected?
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi. 2023 · 2023
Later among the works it cites.
Areg Mikael Sarvazyan, José Ángel González, Marc Franco-Salvador, Francisco Rangel, Berta Chulvi, and Paolo Rosso. 2023 · 2023
Later among the works it cites.
Long-form analogies generated by chatGPT lack human-like psycholinguistic properties
SM Seals and Valerie L Shalin. 2023 · 2023
Later among the works it cites.
ChatGPT: more than a “weapon of mass deception” ethical challenges and responses from the human-centered artificial intelligence (HCAI) perspective
Alejo Jose G Sison, Marco Tulio Daza, Roberto Gozalo-Brizuela, and Eduardo C Garrido-Merchán. 2023 · 2023
Later among the works it cites.
Evaluating the social impact of generative ai systems in systems and society
Irene Solaiman, Zeerak Talat, William Agnew, Lama Ahmad, Dylan Baker, Su Lin Blodgett, Canyu Chen, Hal Daumé III, Jesse Dodge, Isabella Duan, et al · 2023
Later among the works it cites.
AI model GPT-3 (dis) informs us better than humans
Giovanni Spitale, Nikola Biller-Andorno, and Federico Germani. 2023 · 2023
Later among the works it cites.
Detectllm: Leveraging log rank information for zero-shot detection of machine-generated text
Jinyan Su, Terry Yue Zhuo, Di Wang, and Preslav Nakov. 2023b · 2023
Later among the works it cites.
Hc3 plus: A semantic-invariant human chatgpt comparison corpus
Zhenpeng Su, Xing Wu, Wei Zhou, Guangyuan Ma, and Songlin Hu. 2023a · 2023
Later among the works it cites.
The science of detecting llm-generated texts
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu. 2023 · 2023
Later among the works it cites.
GPTZero: Towards detection of AI-generated text using zero-shot and supervised methods
Edward Tian and Alexander Cui. 2023 · 2023
Later among the works it cites.
HANSEN: human and AI spoken text benchmark for authorship analysis
Nafis Irtiza Tripto, Adaku Uchendu, Thai Le, Mattia Setzu, Fosca Giannotti, and Dongwon Lee. 2023 · 2023
Later among the works it cites.
Gpt-who: An information density-based machine-generated text detector
Saranya Venkatraman, Adaku Uchendu, and Dongwon Lee. 2023 · 2023
Later among the works it cites.
Ghostbuster: Detecting text ghostwritten by large language models
Vivek Verma, Eve Fleisig, Nicholas Tomlin, and Dan Klein. 2023 · 2023
Later among the works it cites.
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, Toru Sasaki, et al · 2023
Later among the works it cites.
A survey on llm-gernerated text detection: Necessity, methods, and future directions
Junchao Wu, Shu Yang, Runzhe Zhan, Yulin Yuan, Derek F Wong, and Lidia S Chao. 2023b · 2023
Later among the works it cites.
Dipmark: A stealthy, efficient and resilient watermark for large language models
Yihan Wu, Zhengmian Hu, Hongyang Zhang, and Heng Huang. 2023a · 2023
Later among the works it cites.
On the Generalization of Training-based ChatGPT Detection Methods
Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, and Jiliang Tang. 2023 · 2023
Later among the works it cites.
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
Xianjun Yang, Wei Cheng, Linda Petzold, William Yang Wang, and Haifeng Chen. 2023a · 2023
Later among the works it cites.
A survey on detection of llms-generated content
Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda Petzold, William Yang Wang, and Wei Cheng. 2023b · 2023
Later among the works it cites.
Cheat: A large-scale dataset for detecting chatgpt-written abstracts
Peipeng Yu, Jiahan Chen, Xuan Feng, and Zhihua Xia. 2023 · 2023
Later among the works it cites.
G3Detector: General GPT-generated text detector
Haolan Zhan, Xuanli He, Qiongkai Xu, Yuxiang Wu, and Pontus Stenetorp. 2023 · 2023
Later among the works it cites.
Provable robust watermarking for ai-generated text
Xuandong Zhao, Prabhanjan Ananth, Lei Li, and Yu-Xiang Wang. 2023 · 2023
Later among the works it cites.
A survey on data selection for language models
Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, et al · 2024
Closest in time.
Alimohammad Beigi, Zhen Tan, Nivedh Mudiam, Canyu Chen, Kai Shu, and Huan Liu. 2024 · 2024
Closest in time.
Combating misinformation in the age of LLMs: Opportunities and challenges
Canyu Chen and Kai Shu. 2024b · 2024
Closest in time.
RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors
Liam Dugan, Alyssa Hwang, Filip Trhlik, Josh Magnus Ludan, Andrew Zhu, Hainiu Xu, Daphne Ippolito, and Chris Callison-Burch. 2024 · 2024
Closest in time.
Machine-made media: Monitoring the mobilization of machine-generated articles on misinformation and mainstream news websites. In Proceedings of the International AAAI Conference on Web and Social Media , Vol. 18. 542–556
Hans WA Hanley and Zakir Durumeric. 2024 · 2024
Closest in time.
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, and Tom Goldstein. 2024 · 2024
Closest in time.
Can Large Language Models Identify Authorship?. In Findings of the Association for Computational Linguistics: EMNLP 2024 , Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen (Eds.). Association for Computational Linguistics, Miami, Florida, USA, 445–460
Baixiang Huang, Canyu Chen, and Kai Shu. 2024 · 2024
Closest in time.
Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense
Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, and Mohit Iyyer. 2024 · 2024
Closest in time.
Authorship obfuscation in multilingual machine-generated text detection
Dominik Macko, Robert Moro, Adaku Uchendu, Ivan Srba, Jason Samuel Lucas, Michiharu Yamashita, Nafis Irtiza Tripto, Dongwon Lee, Jakub Simko, and Maria Bielikova. 2024 · 2024
Closest in time.
Automatic Authorship Analysis in Human-AI Collaborative Writing. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) . 1845–1855
Aquia Richburg, Calvin Bao, and Marine Carpuat. 2024 · 2024
Closest in time.
Red teaming language model detectors with language models
Zhouxing Shi, Yihan Wang, Fan Yin, Xiangning Chen, Kai-Wei Chang, and Cho-Jui Hsieh. 2024 · 2024
Closest in time.
Few-Shot Detection of Machine-Generated Text using Style Representations
Rafael Rivera Soto, Kailin Koch, Aleem Khan, Barry Chen, Marcus Bishop, and Nicholas Andrews. 2024 · 2024
Closest in time.
Introducing v0. 5 of the ai safety benchmark from mlcommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, et al · 2024
Closest in time.
M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Osama Mohanned Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, et al · 2024
Closest in time.
LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?. In Findings of the Association for Computational Linguistics: NAACL 2024 . 409–436
Qihui Zhang, Chujie Gao, Dongping Chen, Yue Huang, Yixin Huang, Zhenyang Sun, Shilin Zhang, Weiye Li, Zhengyan Fu, Yao Wan, et al · 2024
Closest in time.
Who’s Your Judge? On the Detectability of LLM-Generated Judgments
Dawei Li, Zhen Tan, Chengshuai Zhao, Bohan Jiang, Baixiang Huang, Pingchuan Ma, Abdullah Alnaibari, Kai Shu, and Huan Liu. 2025 · 2025
Closest in time.
Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky. 2016 · 2030
Closest in time.