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ChatGPT is a recent chatbot service released by OpenAI and is receiving increasing attention over the past few months.
A theory of the learnable
Leslie G Valiant · 1984
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A theory of learning from different domains
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan · 2010
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Learning with noisy labels
Nagarajan Natarajan, Inderjit S Dhillon, Pradeep K Ravikumar, and Ambuj Tewari · 2013
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Recognition in terra incognita
Sara Beery, Grant Van Horn, and Pietro Perona · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R Bowman · 2018
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 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
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen · 2020
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2020
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer · 2020
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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
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OPUS-MT — Building open translation services for the World
Jörg Tiedemann and Santhosh Thottingal · 2020
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Deep learning for ai
Yoshua Bengio, Yann Lecun, and Geoffrey Hinton · 2021
Cited alongside, same era.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Renofeation: A simple transfer learning method for improved adversarial robustness
Ting-Wu Chin, Cha Zhang, and Diana Marculescu · 2021
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Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization
John P Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, and Ludwig Schmidt · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Ddxplus: A new dataset for automatic medical diagnosis
Arsene Fansi Tchango, Rishab Goel, Zhi Wen, Julien Martel, and Joumana Ghosn · 2022
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Id and ood performance are sometimes inversely correlated on real-world datasets
Damien Teney, Yong Lin, Seong Joon Oh, and Ehsan Abbasnejad · 2022
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Generalizing to unseen domains: A survey on domain generalization
Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, and Philip Yu · 2022
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Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
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Towards out-of-distribution generalization: A survey
Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, and Peng Cui · 2021
Cited alongside, same era.
Mesh-Transformer-JAX: Model-Parallel Implementation of Transformer Language Model with JAX
Ben Wang · 2021
Cited alongside, same era.
GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki · 2021
Cited alongside, same era.
Adversarial glue: A multi-task benchmark for robustness evaluation of language models
Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, and Bo Li · 2021
Cited alongside, same era.
Deep long-tailed learning: A survey
Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, and Jiashi Feng · 2021
Cited alongside, same era.
Exploring ai ethics of chatgpt: A diagnostic analysis
Terry Yue Zhuo, Yujin Huang, Chunyang Chen, and Zhenchang Xing · 2021
Cited alongside, same era.
Chatgpt usage and limitations
Amos Azaria · 2022
Cited alongside, same era.
Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, Jindong Wang, Xing Xie, and Yue Zhang · 2022
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Scaling vision transformers
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer · 2022
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Musiclm: Generating music from text
Andrea Agostinelli, Timo I Denk, Zalán Borsos, Jesse Engel, Mauro Verzetti, Antoine Caillon, Qingqing Huang, Aren Jansen, Adam Roberts, Marco Tagliasacchi, et al · 2023
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Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al · 2023
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Chatgpt and the future of medical writing, 2023
Som Biswas · 2023
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Chatgpt goes to law school
Jonathan H Choi, Kristin E Hickman, Amy Monahan, and Daniel Schwarcz · 2023
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Scaling vision transformers to 22 billion parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, et al · 2023
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Chatgpt is not all you need. a state of the art review of large generative ai models
Roberto Gozalo-Brizuela and Eduardo C Garrido-Merchan · 2023
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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
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Regulating chatgpt and other large generative ai models
Philipp Hacker, Andreas Engel, and Marco Mauer · 2023
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Will chatgpt get you caught? rethinking of plagiarism detection
Mohammad Khalil and Erkan Er · 2023
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Adversarial prompting for black box foundation models
Natalie Maus, Patrick Chao, Eric Wong, and Jacob Gardner · 2023
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https://chat.openai.com.chat , 2023
OpenAI · 2023
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Is chatgpt a general-purpose natural language processing task solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang · 2023
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Chatgpt and other large language models are double-edged swords, 2023
Yiqiu Shen, Laura Heacock, Jonathan Elias, Keith D Hentel, Beatriu Reig, George Shih, and Linda Moy · 2023
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Using chatgpt for human–computer interaction research: A primer
Wilbert Tabone and Joost de Winter · 2023
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Flipkart product reviews with sentiment dataset, 2023
Nirali Vaghani and Mansi Thummar · 2023
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Chatgpt: five priorities for research
Eva AM van Dis, Johan Bollen, Willem Zuidema, Robert van Rooij, and Claudi L Bockting · 2023
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Translating natural language to planning goals with large-language models
Yaqi Xie, Chen Yu, Tongyao Zhu, Jinbin Bai, Ze Gong, and Harold Soh · 2023
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