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Source code can be parsed into the abstract syntax tree (AST) based on defined syntax rules.
Pre-trained contextual embedding of source code
Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, and Kensen Shi · 2001
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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A convolutional attention network for extreme summarization of source code
Miltiadis Allamanis, Hao Peng, and Charles Sutton · 2016
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Summarizing source code using a neural attention model
Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, and Luke Zettlemoyer · 2016
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Convolutional neural networks over tree structures for programming language processing
Lili Mou, Ge Li, Lu Zhang, Tao Wang, and Zhi Jin · 2016
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Probabilistic model for code with decision trees
Veselin Raychev, Pavol Bielik, and Martin T. Vechev · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch · 2016
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N. Dauphin · 2017
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Abstract syntax networks for code generation and semantic parsing
Maxim Rabinovich, Mitchell Stern, and Dan Klein · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Deep code comment generation
Xing Hu, Ge Li, Xin Xia, David Lo, and Zhi Jin · 2018
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Unsupervised machine translation using monolingual corpora only
Guillaume Lample, Alexis Conneau, Ludovic Denoyer, and Marc’Aurelio Ranzato · 2018
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Graph2seq: Graph to sequence learning with attention-based neural networks
Kun Xu, Lingfei Wu, Zhiguo Wang, Yansong Feng, and Vadim Sheinin · 2018
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code2seq: Generating sequences from structured representations of code
Uri Alon, Shaked Brody, Omer Levy, and Eran Yahav · 2019
Cited alongside, same era.
Cross-lingual language model pretraining
MASS: masked sequence to sequence pre-training for language generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le · 2019
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ELECTRA: pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning · 2020
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Codebert: A pre-trained model for programming and natural languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou · 2020
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ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut · 2020
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Alexis Conneau and Guillaume Lample · 2019
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon · 2019
Cited alongside, same era.
A neural model for generating natural language summaries of program subroutines
Alexander LeClair, Siyuan Jiang, and Collin McMillan · 2019
Cited alongside, same era.
Annual meeting of the association for computational linguistics, ACL
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao · 2019
Cited alongside, same era.
Improved code summarization via a graph neural network
Alexander LeClair, Sakib Haque, Lingfei Wu, and Collin McMillan · 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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Unsupervised translation of programming languages
Baptiste Rozière, Marie-Anne Lachaux, Lowik Chanussot, and Guillaume Lample · 2020
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Treegen: A tree-based transformer architecture for code generation
Zeyu Sun, Qihao Zhu, Yingfei Xiong, Yican Sun, Lili Mou, and Lu Zhang · 2020
Later among the works it cites.