Fetching the paper…
Reading the bibliography…
Recently, Large Language Models (LLMs) have shown impressive abilities in code generation.
Mean, median, mode
Runnenburg, J. T. 1978 · 1978
Earlier work this paper cites.
A learning algorithm for Boltzmann machines
Ackley, D. H.; Hinton, G. E.; and Sejnowski, T. J. 1985 · 1985
Earlier work this paper cites.
An estimate of an upper bound for the entropy of English
Brown, P. F.; Della Pietra, S. A.; Della Pietra, V. J.; Lai, J. C.; and Mercer, R. L. 1992 · 1992
Earlier work this paper cites.
Measurement error
Bland, J. M.; and Altman, D. G. 1996 · 1996
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.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2005
Earlier work this paper cites.
Measures of shape: Skewness and kurtosis
Brown, S. 2011 · 2011
Earlier work this paper cites.
greedy algorithm, Dictionary of Algorithms and Data Structures
Black; and E, P. 2012 · 2012
Earlier work this paper cites.
On End-to-End Program Generation from User Intention by Deep Neural Networks
Mou, L.; Men, R.; Li, G.; Zhang, L.; and Jin, Z. 2015 · 2015
Earlier work this paper cites.
Beam Search Strategies for Neural Machine Translation
Freitag, M.; and Al-Onaizan, Y. 2017 · 2017
Cited alongside, same era.
Hierarchical Neural Story Generation
Fan, A.; Lewis, M.; and Dauphin, Y. 2018 · 2018
Cited alongside, same era.
Probability for machine learning: Discover how to harness uncertainty with Python
Brownlee, J. 2019 · 2019
Cited alongside, same era.
The Curious Case of Neural Text Degeneration
Holtzman, A.; Buys, J.; Du, L.; Forbes, M.; and Choi, Y. 2019 · 2019
Cited alongside, same era.
Do Massively Pretrained Language Models Make Better Storytellers?
See, A.; Pappu, A.; Saxena, R.; Yerukola, A.; and Manning, C. D. 2019 · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Measuring Coding Challenge Competence With APPS
Hendrycks, D.; Basart, S.; Kadavath, S.; Mazeika, M.; Arora, A.; Guo, E.; Burns, C.; Puranik, S.; He, H.; Song, D.; and Steinhardt, J. 2021 · 2021
Later among the works it cites.
Improving Diversity of Neural Text Generation via Inverse Probability Weighting
Zhang, X.; Sun, M.; Liu, J.; and Li, X. 2021 · 2021
Later among the works it cites.
InCoder: A Generative Model for Code Infilling and Synthesis
Fried, D.; Aghajanyan, A.; Lin, J.; Wang, S.; Wallace, E.; Shi, F.; Zhong, R.; Yih, S.; Zettlemoyer, L.; and Lewis, M. 2022 · 2022
Later among the works it cites.
Competition-level code generation with alphacode
Li, Y.; Choi, D.; Chung, J.; Kushman, N.; Schrittwieser, J.; Leblond, R.; Eccles, T.; Keeling, J.; Gimeno, F.; Dal Lago, A.; et al. 2022 · 2022
Later among the works it cites.
InCoder: A Generative Model for Code Infilling and Synthesis
Fried, D.; Aghajanyan, A.; Lin, J.; Wang, S.; Wallace, E.; Shi, F.; Zhong, R.; Yih, S.; Zettlemoyer, L.; and Lewis, M. 2023 · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Evaluating Large Language Models Trained on Code
Chen, M.; Tworek, J.; Jun, H.; Yuan, Q.; de Oliveira Pinto, H. P.; Kaplan, J.; Edwards, H.; Burda, Y.; Joseph, N.; Brockman, G.; Ray, A.; Puri, R.; Krueger, G.; Petrov, M.; Khlaaf, H.; Sastry, G.; Mishkin, P.; Chan, B.; Gray, S.; Ryder, N.; Pavlov, M.; Power, A.; Kaiser, L.; Bavarian, M.; Winter, C.; Tillet, P.; Such, F. P.; Cummings, D.; Plappert, M.; Chantzis, F.; Barnes, E.; Herbert-Voss, A.; Guss, W. H.; Nichol, A.; Paino, A.; Tezak, N.; Tang, J.; Babuschkin, I.; Balaji, S.; Jain, S.; Saunders, W.; Hesse, C.; Carr, A. N.; Leike, J.; Achiam, J.; Misra, V.; Morikawa, E.; Radford, A.; Knight, M.; Brundage, M.; Murati, M.; Mayer, K.; Welinder, P.; McGrew, B.; Amodei, D.; McCandlish, S.; Sutskever, I.; and Zaremba, W. 2021 · 2021
Cited alongside, same era.
CodeEditor: Learning to Edit Source Code with Pre-Trained Models
Li, J.; Li, G.; Li, Z.; Jin, Z.; Hu, X.; Zhang, K.; and Fu, Z. 2023a
Cited in the paper.
Large Language Model-Aware In-Context Learning for Code Generation
Li, J.; Li, G.; Tao, C.; Zhang, H.; Liu, F.; and Jin, Z. 2023b
Cited in the paper.
Structured Chain-of-Thought Prompting for Code Generation
Li, J.; Li, Y.; Li, G.; and Jin, Z. 2023c
Cited in the paper.
AceCoder: Utilizing Existing Code to Enhance Code Generation
Li, J.; Zhao, Y.; Li, Y.; Li, G.; and Jin, Z. 2023e
Cited in the paper.
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Nijkamp, E.; Pang, B.; Hayashi, H.; Tu, L.; Wang, H.; Zhou, Y.; Savarese, S.; and Xiong, C. 2022a
Cited in the paper.
SkCoder: A Sketch-based Approach for Automatic Code Generation
Li, J.; Li, Y.; Li, G.; Jin, Z.; Hao, Y.; and Hu, X. 2023d · 2023
Closest in time.
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X
Zheng, Q.; Xia, X.; Zou, X.; Dong, Y.; Wang, S.; Xue, Y.; Wang, Z.; Shen, L.; Wang, A.; Li, Y.; Su, T.; Yang, Z.; and Tang, J. 2023 · 2023
Closest in time.