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The release of ChatGPT, a language model capable of generating text that appears human-like and authentic, has gained significant attention beyond the research community.
“Language models are few-shot learners”
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry and Amanda Askell · 1901
Earlier work this paper cites.
“Professional language in swedish radiology reports–characterization for patient-adapted text simplification”
Maria Kvist and Sumithra Velupillai · 2013
Earlier work this paper cites.
“A survey of automated text simplification”
Matthew Shardlow · 2014
Earlier work this paper cites.
“Medical text simplification using synonym replacement: Adapting assessment of word difficulty to a compounding language”
Emil Abrahamsson, Timothy Forni, Maria Skeppstedt and Maria Kvist · 2014
Earlier work this paper cites.
“PORTER: a prototype system for patient-oriented radiology reporting”
Seong Oh, Tessa Cook and Charles Kahn · 2016
Earlier work this paper cites.
“Attention is all you need”
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan Gomez, ukasz Kaiser and Illia Polosukhin · 2017
Earlier work this paper cites.
“Deep reinforcement learning from human preferences”
Paul Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg and Dario Amodei · 2017
Earlier work this paper cites.
“Proximal policy optimization algorithms”
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford and Oleg Klimov · 2017
Earlier work this paper cites.
“Radiological Text Simplification Using a General Knowledge Base”
Lionel Ramadier and Mathieu Lafourcade · 2017
Earlier work this paper cites.
“Text simplification using consumer health vocabulary to generate patient-centered radiology reporting: translation and evaluation”
Basel Qenam, Tae Kim, Mark Carroll and Michael Hogarth · 2017
Earlier work this paper cites.
“Readability of radiology reports: implications for patient-centered care”
Teresa Martin-Carreras, Tessa. Cook and Charles. Kahn · 2018
Earlier work this paper cites.
“Improving language understanding by generative pre-training”
Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever · 2018
Earlier work this paper cites.
“Learning to Summarize Radiology Findings”
Yuhao Zhang, Daisy Ding, Tianpei Qian, Christopher. Manning and Curtis. Langlotz · 2018
Earlier work this paper cites.
“Domain-aware abstractive text summarization for medical documents”
Paul Gigioli, Nikhita Sagar, Anand Rao and Joseph Voyles · 2018
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.
“Megatron-lm: Training multi-billion parameter language models using model parallelism”
Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper and Bryan Catanzaro · 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
Cited alongside, same era.
“Ontology-aware clinical abstractive summarization”
Sean MacAvaney, Sajad Sotudeh, Arman Cohan, Nazli Goharian, Ish Talati and Ross Filice · 2019
Cited alongside, same era.
“Readability of Lumbar Spine MRI Reports: Will Patients Understand?” Publisher: American Roentgen Ray Society
Paul Yi, Sean Golden, John. Harringa and Mark. Kliewer · 2019
Cited alongside, same era.
“Principles of biomedical ethics”
Tom. Beauchamp and James. Childress · 2019
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 Liu · 2020
Cited alongside, same era.
“The pile: An 800gb dataset of diverse text for language modeling”
“Extracting training data from large language models”
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song and Ulfar Erlingsson · 2021
Later among the works it cites.
“Detecting Hallucinated Content in Conditional Neural Sequence Generation”
Chunting Zhou, Graham Neubig, Jiatao Gu, Mona. Diab, Francisco Guzm\’an, Luke Zettlemoyer and Marjan Ghazvininejad · 2021
Later among the works it cites.
“ChatGPT: Optimizing Language Models for Dialogue”, 2022
OpenAI · 2022
Closest in time.
“The Brilliance and Weirdness of ChatGPT”, 2022
The New Times · 2022
Closest in time.
“Stumbling with their words, some people let AI do the talking”, 2022
The Post · 2022
Closest in time.
“ChatGPT: New AI chatbot has everyone talking to it”, 2022
BBC · 2022
Closest in time.
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Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite and Noa Nabeshima · 2020
Cited alongside, same era.
“Biomedical-domain pre-trained language model for extractive summarization”
Yongping Du, Qingxiao Li, Lulin Wang and Yanqing He · 2020
Cited alongside, same era.
“CERC: an interactive content extraction, recognition, and construction tool for clinical and biomedical text”
Eva Lee and Karan Uppal · 2020
Cited alongside, same era.
“The Ethics of AI Ethics: An Evaluation of Guidelines”
Thilo Hagendorff · 2020
Cited alongside, same era.
“On the opportunities and risks of foundation models”
Rishi Bommasani, Drew Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael Bernstein, Jeannette Bohg, Antoine Bosselut and Emma Brunskill · 2021
Cited alongside, same era.
“ChestXRayBERT: A Pretrained Language Model for Chest Radiology Report Summarization”
Xiaoyan Cai, Sen Liu, Junwei Han, Libin Yang, Zhenguo Liu and Tianming Liu · 2021
Cited alongside, same era.
“Automated text simplification: a survey”
Suha Al-Thanyyan and Aqil Azmi · 2021
Cited alongside, same era.
“What is AI chatbot phenomenon ChatGPT and could it replace humans?”, 2022
The Guardian · 2022
Closest in time.
“Explain to me like I am five–Sentence Simplification Using Transformers”
Aman Agarwal · 2022
Closest in time.
“Palm: Scaling language modeling with pathways”
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Chung, Charles Sutton and Sebastian Gehrmann · 2022
Closest in time.
“Bloom: A 176b-parameter open-access multilingual language model”
Teven Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ili\’c, Daniel Hesslow, Roman Castagn\’e, Alexandra Luccioni, Francois Yvon and Matthias Gall\’e · 2022
Closest in time.
“Training language models to follow instructions with human feedback”
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama and Alex Ray · 2022
Closest in time.
“Fine-tuning BERT Models for Summarizing German Radiology Findings”
Siting Liang, Klaus Kades, Matthias Fink, Peter Full, Tim Weber, Jens Kleesiek, Michael Strube and Klaus Maier-Hein · 2022
Closest in time.
“Automatic Text Summarization of Biomedical Text Data: A Systematic Review”
Andrea Chaves, Cyrille Kesiku and Begonya Garcia-Zapirain · 2022
Closest in time.
“TruthfulQA: Measuring How Models Mimic Human Falsehoods”
Stephanie Lin, Jacob Hilton and Owain Evans · 2022
Closest in time.
“Galactica: A Large Language Model for Science”
Ross Taylor, Marcin Kardas, Guillem Cucurull, Thomas Scialom, Anthony Hartshorn, Elvis Saravia, Andrew Poulton, Viktor Kerkez and Robert Stojnic · 2022
Closest in time.