Intellicode compose: Code generation using transformer
Alexey Svyatkovskiy, Shao Kun Deng, Shengyu Fu, and Neel Sundaresan. 2020 · 2020
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Retrieve and refine: exemplar-based neural comment generation
Bolin Wei, Yongmin Li, Ge Li, Xin Xia, and Zhi Jin. 2020 · 2020
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Unified pre-training for program understanding and generation
Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang. 2021 · 2021
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Self-supervised contrastive learning for code retrieval and summarization via semantic-preserving transformations
Nghi DQ Bui, Yijun Yu, and Lingxiao Jiang. 2021 · 2021
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Evaluating large language models trained on code
Original
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021 · 2021
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Long-range modeling of source code files with ewash: Extended window access by syntax hierarchy
Original
Colin B Clement, Shuai Lu, Xiaoyu Liu, Michele Tufano, Dawn Drain, Nan Duan, Neel Sundaresan, and Alexey Svyatkovskiy. 2021 · 2021
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Generating bug-fixes using pretrained transformers
Dawn Drain, Chen Wu, Alexey Svyatkovskiy, and Neel Sundaresan. 2021 · 2021
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Simcse: Simple contrastive learning of sentence embeddings
Original
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Learning to complete code with sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, and Miltiadis Allamanis. 2021 · 2021
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Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Édouard Grave. 2021 · 2021
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Code prediction by feeding trees to transformers
Seohyun Kim, Jinman Zhao, Yuchi Tian, and Satish Chandra. 2021 · 2021
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Editsum: A retrieve-and-edit framework for source code summarization
Jia Li, Yongmin Li, Ge Li, Xing Hu, Xin Xia, and Zhi Jin. 2021 · 2021
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Codexglue: A machine learning benchmark dataset for code understanding and generation
Original
Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin Clement, Dawn Drain, Daxin Jiang, Duyu Tang, et al. 2021 · 2021
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A replication study of dense passage retriever
Original
Xueguang Ma, Kai Sun, Ronak Pradeep, and Jimmy Lin. 2021 · 2021
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Applying codebert for automated program repair of java simple bugs
Original
Ehsan Mashhadi and Hadi Hemmati. 2021 · 2021
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Retrieval augmented code generation and summarization
Original
Md Rizwan Parvez, Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang. 2021 · 2021
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Project codenet: A large-scale ai for code dataset for learning a diversity of coding tasks
Original
Ruchir Puri, David S Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladmir Zolotov, Julian Dolby, Jie Chen, Mihir Choudhury, Lindsey Decker, et al. 2021 · 2021
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On the generalizability of neural program models with respect to semantic-preserving program transformations
Md Rafiqul Islam Rabin, Nghi DQ Bui, Ke Wang, Yijun Yu, Lingxiao Jiang, and Mohammad Amin Alipour. 2021 · 2021
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Learning transferable visual models from natural language supervision
Original
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021 · 2021
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Fast and memory-efficient neural code completion
Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, and Miltiadis Allamanis. 2021 · 2021
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Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation
Original
Yue Wang, Weishi Wang, Shafiq Joty, and Steven CH Hoi. 2021 · 2021
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Unixcoder: Unified cross-modal pre-training for code representation
Original
Daya Guo, Shuai Lu, Nan Duan, Yanlin Wang, Ming Zhou, and Jian Yin. 2022 · 2022
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Syncobert: Syntax-guided multi-modal contrastive pre-training for code representation
Xin Wang, Fei Mi Yasheng Wang, Pingyi Zhou, Yao Wan, Xiao Liu, Li Li, Hao Wu, Jin Liu, and Xin Jiang. 2022 · 2022
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