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Code search is an important and well-studied task, but it usually means searching for code by a text query.
Neural code search evaluation dataset
Hongyu Li, Seohyun Kim, and Satish Chandra. 2019 · 1908
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Okapi at trec-3
Stephen E. Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford. 1994 · 1994
Earlier work this paper cites.
GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, and Ming Zhou. 2021 · 2009
Earlier work this paper cites.
Distilling Knowledge from Reader to Retriever for Question Answering
Gautier Izacard and Edouard Grave. 2020 · 2012
Earlier work this paper cites.
Mining stackoverflow to turn the ide into a self-confident programming prompter
Luca Ponzanelli, Gabriele Bavota, Massimiliano Di Penta, Rocco Oliveto, and Michele Lanza. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2015
Earlier work this paper cites.
Deep code search
Xiaodong Gu, Hongyu Zhang, and Sunghun Kim. 2018 · 2018
Cited alongside, same era.
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt. 2019 · 2019
Cited alongside, same era.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
Cited alongside, same era.
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 · 2020
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Cited alongside, same era.
Cascaded fast and slow models for efficient semantic code search
Codesc: A large code–description parallel dataset
Masum Hasan, Tanveer Muttaqueen, Abdullah Al Ishtiaq, Kazi Sajeed Mehrab, Md Mahim Anjum Haque, Tahmid Hasan, Wasi Ahmad, Anindya Iqbal, and Rifat Shahriyar. 2021 · 2021
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Codexglue: A machine learning benchmark dataset for code understanding and generation
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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Codenet: A large-scale ai for code dataset for learning a diversity of coding tasks
Ruchir Puri, David S Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir Choudhury, Lindsey Decker, et al. 2021 · 2021
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RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering
Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2021 · 2021
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SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation
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Akhilesh Deepak Gotmare, Junnan Li, Shafiq Joty, and Steven CH Hoi. 2021 · 2021
Cited alongside, same era.
Xin Wang, Yasheng Wang, Fei Mi, Pingyi Zhou, Yao Wan, Xiao Liu, Li Li, Hao Wu, Jin Liu, and Xin Jiang. 2021 · 2021
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Ask me anything in your native language
Nikita Sorokin, Dmitry Abulkhanov, Irina Piontkovskaya, and Valentin Malykh. 2022 · 2022
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