Fetching the paper…
Reading the bibliography…
ChatGPT, the first large language model (LLM) with mass adoption, has demonstrated remarkable performance in numerous natural language tasks.
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 · 1901
Earlier work this paper cites.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen. 1989 · 1989
Earlier work this paper cites.
Semeval-2016 task 6: Detecting stance in tweets
Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016 · 2016
Earlier work this paper cites.
Stance and sentiment in tweets
Saif M Mohammad, Parinaz Sobhani, and Svetlana Kiritchenko. 2017 · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Earlier work this paper cites.
Stance detection: A survey
Dilek Küçük and Fazli Can. 2020 · 2020
Earlier work this paper cites.
On the dangers of stochastic parrots: Can language models be too big?
Emily M Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
Earlier work this paper cites.
Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B Brown, Dawn Song, Ulfar Erlingsson, et al. 2021 · 2021
Earlier work this paper cites.
Documenting large webtext corpora: A case study on the colossal clean crawled corpus
Jesse Dodge, Maarten Sap, Ana Marasović, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Margaret Mitchell, and Matt Gardner. 2021 · 2021
Earlier work this paper cites.
P-stance: A large dataset for stance detection in political domain
Yingjie Li, Tiberiu Sosea, Aditya Sawant, Ajith Jayaraman Nair, Diana Inkpen, and Cornelia Caragea. 2021 · 2021
Cited alongside, same era.
What can transformers learn in-context? a case study of simple function classes
Shivam Garg, Dimitris Tsipras, Percy Liang, and Gregory Valiant. 2022 · 2022
Cited alongside, same era.
Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
Cited alongside, same era.
Chatgpt: Optimizing language models for dialogue
OpenAI. 2022 · 2022
Cited alongside, same era.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al. 2022 · 2022
Performance of chatgpt on usmle: Potential for ai-assisted medical education using large language models
Tiffany H Kung, Morgan Cheatham, Arielle Medenilla, Czarina Sillos, Lorie De Leon, Camille Elepaño, Maria Madriaga, Rimel Aggabao, Giezel Diaz-Candido, James Maningo, et al. 2023 · 2023
Closest in time.
OpenAI. 2023 · 2023
Closest in time.
Chatgpt: the future of discharge summaries?
Sajan B Patel and Kyle Lam. 2023 · 2023
Closest in time.
An analysis of the automatic bug fixing performance of chatgpt
Dominik Sobania, Martin Briesch, Carol Hanna, and Justyna Petke. 2023 · 2023
Closest in time.
What chatgpt and generative ai mean for science
Chris Stokel-Walker and Richard Van Noorden. 2023 · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
How would stance detection techniques evolve after the launch of chatgpt?
Bowen Zhang, Daijun Ding, and Liwen Jing. 2022 · 2022
Cited alongside, same era.
Artificial hallucinations in chatgpt: Implications in scientific writing
2023 · 2023
Cited alongside, same era.
Chatgpt for (finance) research: The bananarama conjecture
Michael Dowling and Brian Lucey. 2023 · 2023
Cited alongside, same era.
Mathematical capabilities of chatgpt
Simon Frieder, Luca Pinchetti, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Christian Petersen, Alexis Chevalier, and Julius Berner. 2023 · 2023
Cited alongside, same era.
Chatgpt: Jack of all trades, master of none
Jan Kocoń, Igor Cichecki, Oliwier Kaszyca, Mateusz Kochanek, Dominika Szydło, Joanna Baran, Julita Bielaniewicz, Marcin Gruza, Arkadiusz Janz, Kamil Kanclerz, et al. 2023 · 2023
Cited alongside, same era.
Chatgpt reaches 100 million users two months after launch
Dan Milmo. 2023a
Cited in the paper.
Reinventing search with a new ai-powered microsoft bing and edge, your copilot for the web
Dan Milmo. 2023b
Cited in the paper.
What can chatgpt do? analyzing early reactions to the innovative ai chatbot on twitter
Viriya Taecharungroj. 2023 · 2023
Closest in time.
Would chatgpt3 get a wharton mba. a prediction based on its performance in the operations management course
Christian Terwiesch. 2023 · 2023
Closest in time.
Chatgpt: five priorities for research
Eva AM van Dis, Johan Bollen, Willem Zuidema, Robert van Rooij, and Claudi L Bockting. 2023 · 2023
Closest in time.
Patrick Y Wu, Joshua A Tucker, Jonathan Nagler, and Solomon Messing. 2023 · 2023
Closest in time.