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We study the feasibility of a Data Science assistant powered by a sequence-to-sequence transformer by training a new model JuPyT5 on all publicly available Jupyter Notebook GitHub repositories and developing a new metric: Data Science Problems (DSP).
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Husain, H.; Wu, H.-H.; Gazit, T.; Allamanis, M.; and Brockschmidt, M. 2019 · 1909
Earlier work this paper cites.
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Keskar, N.; McCann, B.; Varshney, L.; Xiong, C.; and Socher, R. 2019 · 1909
Earlier work this paper cites.
JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation
Agashe, R.; Iyer, S.; and Zettlemoyer, L. 2019 · 1910
Earlier work this paper cites.
Lewis, M.; Liu, Y.; Goyal, N.; Ghazvininejad, M.; Mohamed, A.; Levy, O.; Stoyanov, V.; and Zettlemoyer, L. 2019 · 1910
Earlier work this paper cites.
Scaling laws for neural language models
Kaplan, J.; McCandlish, S.; Henighan, T.; Brown, T. B.; Chess, B.; Child, R.; Gray, S.; Radford, A.; Wu, J.; and Amodei, D. 2020 · 2001
Earlier work this paper cites.
Language models are few-shot learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 2005
Earlier work this paper cites.
Learning from examples to improve code completion systems
Bruch, M.; Monperrus, M.; and Mezini, M. 2009 · 2009
Earlier work this paper cites.
Codebleu: a method for automatic evaluation of code synthesis
Ren, S.; Guo, D.; Lu, S.; Zhou, L.; Liu, S.; Tang, D.; Sundaresan, N.; Zhou, M.; Blanco, A.; and Ma, S. 2020 · 2009
Earlier work this paper cites.
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Cited alongside, same era.
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Raychev, V.; Vechev, M.; and Yahav, E. 2014 · 2014
Cited alongside, same era.
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Cited alongside, same era.
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Radford, A.; Narasimhan, K.; Salimans, T.; and Sutskever, I. 2018 · 2018
Cited alongside, same era.
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Chen, M. X.; Lee, B. N.; Bansal, G.; Cao, Y.; Zhang, S.; Lu, J.; Tsay, J.; Wang, Y.; Dai, A. M.; Chen, Z.; et al. 2019 · 2019
Cited alongside, same era.
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Feng, Z.; Guo, D.; Tang, D.; Duan, N.; Feng, X.; Gong, M.; Shou, L.; Qin, B.; Liu, T.; Jiang, D.; et al. 2020 · 2020
Later among the works it cites.
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Svyatkovskiy, A.; Deng, S. K.; Fu, S.; and Sundaresan, N. 2020 · 2020
Later among the works it cites.
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Zhai, J.; Xu, X.; Shi, Y.; Tao, G.; Pan, M.; Ma, S.; Xu, L.; Zhang, W.; Tan, L.; and Zhang, X. 2020 · 2020
Later among the works it cites.
Program Synthesis with Large Language Models
Austin, J.; Odena, A.; Nye, M.; Bosma, M.; Michalewski, H.; Dohan, D.; Jiang, E.; Cai, C.; Terry, M.; Le, Q.; et al. 2021 · 2021
Later among the works it cites.
Evaluating large language models trained on code
Chen, M.; Tworek, J.; Jun, H.; Yuan, Q.; Ponde, H.; Kaplan, J.; Edwards, H.; Burda, Y.; Joseph, N.; Brockman, G.; et al. 2021 · 2021
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Cited alongside, same era.
PyMT5: Multi-mode Translation of Natural Language and Python Code with Transformers
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Cited alongside, same era.
Later among the works it cites.
Generating Bug-Fixes Using Pretrained Transformers
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Later among the works it cites.
Measuring Coding Challenge Competence With APPS
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Later among the works it cites.