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Nowadays, powerful large language models (LLMs) such as ChatGPT have demonstrated revolutionary power in a variety of tasks.
N-gram feature selection for authorship identification
John Houvardas and Efstathios Stamatatos · 2006
Earlier work this paper cites.
Identifying Real or Fake Articles: Towards better Language Modeling
Sameer Badaskar, Sachin Agarwal, and Shilpa Arora · 2008
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Improving Language Understanding by Generative Pre-Training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2016
Earlier work this paper cites.
Deep Reinforcement Learning from Human Preferences
Paul F. Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
Earlier work this paper cites.
Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Earlier work this paper cites.
GLTR: Statistical Detection and Visualization of Generated Text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M. Rush · 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
Earlier work this paper cites.
Language Models are Unsupervised Multitask Learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Earlier work this paper cites.
Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che · 2019
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
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Defending Against Neural Fake News
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi · 2019
Cited alongside, same era.
Language Models are Few-Shot Learners
Tom B. Brown, 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
Cited alongside, same era.
Automatic Detection of Generated Text is Easiest when Humans are Fooled
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck · 2020
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
Cited alongside, same era.
TruthfulQA: Measuring How Models Mimic Human Falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans · 2022
Later among the works it cites.
ChatGPT: The End of Online Exam Integrity?
Teo Susnjak · 2022
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Gpt4all: Training an assistant-style chatbot with large scale data distillation from gpt-3.5-turbo
Yuvanesh Anand, Zach Nussbaum, Brandon Duderstadt, Benjamin Schmidt, and Andriy Mulyar · 2023
Closest in time.
Conda: Contrastive domain adaptation for ai-generated text detection
Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah, and Huan Liu · 2023
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On the possibilities of ai-generated text detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, and Furong Huang · 2023
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Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F. Christiano · 2020
Cited alongside, same era.
Authorship Attribution for Neural Text Generation
Adaku Uchendu, Thai Le, Kai Shu, and Dongwon Lee · 2020
Cited alongside, same era.
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
Adaku Uchendu, Zeyu Ma, Thai Le, Rui Zhang, and Dongwon Lee · 2021
Cited alongside, same era.
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, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William S. Isaac, Sean Legassick, Geoffrey Irving, and Iason Gabriel · 2021
Cited alongside, same era.
Gpt-neox-20b: An open-source autoregressive language model
Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, Michael Pieler, USVSN Sai Prashanth, Shivanshu Purohit, Laria Reynolds, Jonathan Tow, Ben Wang, and Samuel Weinbach · 2022
Cited alongside, same era.
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang · 2022
Cited alongside, same era.
https://github.com/THUDM/ChatGLM-6B
ChatGLM
Cited in the paper.
https://github.com/databrickslabs/dolly
Dolly
Cited in the paper.
Biyang Guo, Xin Zhang, Ziyuan Wang, Minqi Jiang, Jinran Nie, Yuxuan Ding, Jianwei Yue, and Yupeng Wu · 2023
Closest in time.
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, and Chelsea Finn · 2023
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Deepfake Text Detection: Limitations and Opportunities
Jiameng Pu, Zain Sarwar, Sifat Muhammad Abdullah, Abdullah Rehman, Yoonjin Kim, Parantapa Bhattacharya, Mobin Javed, and Bimal Viswanath · 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
Closest in time.
Ghostbuster: Detecting text ghostwritten by large language models
Vivek Verma, Eve Fleisig, Nicholas Tomlin, and Dan Klein · 2023
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