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In recent years, deep learning models have shown great potential in source code modeling and analysis.
Codegru: Context-aware deep learning with gated recurrent unit for source code modeling
Yasir Hussain, Zhiqiu Huang, Senzhang Wang, and Yu Zhou · 1903
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Deepvs: An efficient and generic approach for source code modeling usage
Yasir Hussain, Zhiqiu Huang, Yu Zhou, and Senzhang Wang · 1910
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Mapo: Mining api usages from open source repositories
Tao Xie and Jian Pei · 2006
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Transfer learning via dimensionality reduction
Sinno Jialin Pan, James T Kwok, Qiang Yang, et al · 2008
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Domain transfer svm for video concept detection
Lixin Duan, Ivor W Tsang, Dong Xu, and Stephen J Maybank · 2009
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol · 2010
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Searching connected api subgraph via text phrases
Wing-Kwan Chan, Hong Cheng, and David Lo · 2012
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On the naturalness of software
Abram Hindle, Earl T Barr, Zhendong Su, Mark Gabel, and Premkumar Devanbu · 2012
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Graph-based pattern-oriented, context-sensitive source code completion
Anh Tuan Nguyen, Tung Thanh Nguyen, Hoan Anh Nguyen, Ahmed Tamrawi, Hung Viet Nguyen, Jafar Al-Kofahi, and Tien N Nguyen · 2012
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Automatic recommendation of api methods from feature requests
Ferdian Thung, Shaowei Wang, David Lo, and Julia Lawall · 2013
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Mining succinct and high-coverage api usage patterns from source code
Jue Wang, Yingnong Dang, Hongyu Zhang, Kai Chen, Tao Xie, and Dongmei Zhang · 2013
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Mining idioms from source code
Miltiadis Allamanis and Charles Sutton · 2014
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Spotting working code examples
Iman Keivanloo, Juergen Rilling, and Ying Zou · 2014
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Structured generative models of natural source code
Chris Maddison and Daniel Tarlow · 2014
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Code completion with statistical language models
Veselin Raychev, Martin Vechev, and Eran Yahav · 2014
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On the localness of software
Zhaopeng Tu, Zhendong Su, and Premkumar Devanbu · 2014
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Mmrate: inferring multi-aspect diffusion networks with multi-pattern cascades
Senzhang Wang, Xia Hu, Philip S Yu, and Zhoujun Li · 2014
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Suggesting accurate method and class names
Miltiadis Allamanis, Earl T Barr, Christian Bird, and Charles Sutton · 2015
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Attention-based models for speech recognition
Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, and Yoshua Bengio · 2015
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Cacheca: A cache language model based code suggestion tool
Christine Franks, Zhaopeng Tu, Premkumar Devanbu, and Vincent Hellendoorn · 2015
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Leveraging informal documentation to summarize classes and methods in context
Latifa Guerrouj, David Bourque, and Peter C Rigby · 2015
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Deep transfer metric learning
Junlin Hu, Jiwen Lu, and Yap-Peng Tan · 2015
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Code clone detection and analysis using software metrics and neural network-a literature review
Balwinder Kumar and Satwinder Singh · 2015
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Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D Manning · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
Cited alongside, same era.
Toward deep learning software repositories
Autofolding for source code summarization
Jaroslav Fowkes, Pankajan Chanthirasegaran, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, and Charles Sutton · 2017
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Are deep neural networks the best choice for modeling source code?
Vincent J Hellendoorn and Premkumar Devanbu · 2017
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Transfer learning with deep convolutional neural network for sar target classification with limited labeled data
Zhongling Huang, Zongxu Pan, and Bin Lei · 2017
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Prst: A pagerank-based summarization technique for summarizing bug reports with duplicates
He Jiang, Najam Nazar, Jingxuan Zhang, Tao Zhang, and Zhilei Ren · 2017
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Decision support from financial disclosures with deep neural networks and transfer learning
Mathias Kraus and Stefan Feuerriegel · 2017
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Martin White, Christopher Vendome, Mario Linares-Vásquez, and Denys Poshyvanyk · 2015
Cited alongside, same era.
Event detection and popularity prediction in microblogging
Xiaoming Zhang, Xiaoming Chen, Yan Chen, Senzhang Wang, Zhoujun Li, and Jiali Xia · 2015
Cited alongside, same era.
A convolutional attention network for extreme summarization of source code
Miltiadis Allamanis, Hao Peng, and Charles Sutton · 2016
Cited alongside, same era.
End-to-end attention-based large vocabulary speech recognition
Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, and Yoshua Bengio · 2016
Cited alongside, same era.
Phog: probabilistic model for code
Pavol Bielik, Veselin Raychev, and Martin Vechev · 2016
Cited alongside, same era.
Similartech: automatically recommend analogical libraries across different programming languages
Chunyang Chen and Zhenchang Xing · 2016
Cited alongside, same era.
Collective intelligence for smarter api recommendations in python
Andrea Renika D’Souza, Di Yang, and Cristina V Lopes · 2016
Cited alongside, same era.
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, Łukasz Kaiser, and Illia Polosukhin · 2017
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Hyperspectral image superresolution by transfer learning
Yuan Yuan, Xiangtao Zheng, and Xiaoqiang Lu · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Deep reinforcement learning for programming language correction
Rahul Gupta, Aditya Kanade, and Shirish Shevade · 2018
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A deep neural network language model with contexts for source code
Anh Tuan Nguyen, Trong Duc Nguyen, Hung Dang Phan, and Tien N Nguyen · 2018
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Syntax and sensibility: Using language models to detect and correct syntax errors
Eddie Antonio Santos, Joshua Charles Campbell, Dhvani Patel, Abram Hindle, and José Nelson Amaral · 2018
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Dlpaper2code: Auto-generation of code from deep learning research papers
Akshay Sethi, Anush Sankaran, Naveen Panwar, Shreya Khare, and Senthil Mani · 2018
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Recent trends in deep learning based natural language processing
Tom Young, Devamanyu Hazarika, Soujanya Poria, and Erik Cambria · 2018
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code2vec: Learning distributed representations of code
Uri Alon, Meital Zilberstein, Omer Levy, and Eran Yahav · 2019
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Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, William W Cohen, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov · 2019
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A novel deep learning based framework for the detection and classification of breast cancer using transfer learning
SanaUllah Khan, Naveed Islam, Zahoor Jan, Ikram Ud Din, and Joel JP C Rodrigues · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Utilizing transfer learning and homomorphic encryption in a privacy preserving and secure biometric recognition system
Milad Salem, Shayan Taheri, and Jiann-Shiun Yuan · 2019
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Augmenting java method comments generation with context information based on neural networks
Yu Zhou, Xin Yan, Wenhua Yang, Taolue Chen, and Zhiqiu Huang · 2019
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