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Large Language Models (LLMs) have shown impressive proficiency in code generation.
Unsupervised translation of programming languages
Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, and Guillaume Lample. 2020 · 2006
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Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, et al. 2018 · 2018
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Python coding style compliance on stack overflow
Nikolaos Bafatakis, Niels Boecker, Wenjie Boon, Martin Cabello Salazar, Jens Krinke, Gazi Oznacar, and Robert White. 2019 · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam Girish Sastry, Amanda Askell, Sandhini Agarwa, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Clemens Winter Jeffrey Wu, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Earlier work this paper cites.
Unsupervised translation of programming languages
Baptiste Roziere, Marie-Anne Lachaux, Lowik Chanussot, and Guillaume Lample. 2020 · 2020
Earlier work this paper cites.
Graph-based, self-supervised program repair from diagnostic feedback
Michihiro Yasunaga and Percy Liang. 2020 · 2020
Earlier work this paper cites.
Self-supervised bug detection and repair
Miltiadis Allamanis, Henry Jackson-Flux, and Marc Brockschmidt. 2021 · 2021
Earlier work this paper cites.
Program synthesis with large language models
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al. 2021 · 2021
Earlier work this paper cites.
Deep learning based vulnerability detection: Are we there yet?
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, and Baishakhi Ray. 2021 · 2021
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NL-EDIT: Correcting semantic parse errors through natural language interaction
Ahmed Elgohary, Christopher Meek, Matthew Richardson, Adam Fourney, Gonzalo Ramos, and Ahmed Hassan Awadallah. 2021 · 2021
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Securityeval dataset: Mining vulnerability examples to evaluate machine learning-based code generation techniques
Mohammed Siddiq and Joanna Santos. 2022 · 2022
Earlier work this paper cites.
Re3: Generating longer stories with recursive reprompting and revision
Kevin Yang, Yuandong Tian, Nanyun Peng, and Dan Klein. 2022 · 2022
Cited alongside, same era.
Rl4f: Generating natural language feedback with reinforcement learning for repairing model outputs
Afra Feyza Akyürek, Ekin Akyürek, Ashwin Kalyan, Peter Clark, Derry Wijaya, and Niket Tandon. 2023 · 2023
Cited alongside, same era.
Learning defect prediction from unrealistic data
Kamel Alrashedy, Vincent J. Hellendoorn, and Alessandro Orso. 2023 · 2023
Cited alongside, same era.
Multi-lingual evaluation of code generation models
Ben Athiwaratkun, Sanjay Krishna Gouda, and Zijian Wang. 2023 · 2023
Cited alongside, same era.
Teaching large language models to self-debug
Xinyun Chen, Maxwell Lin, Nathanael Schärli, and Denny Zhou. 2023 · 2023
Cited alongside, same era.
Code llama: Open foundation models for code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, and Gabriel Synnaeve. 2023 · 2023
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Learning performance-improving code edits
Alexander Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob Gardner, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, and Amir Yazdanbakhsh. 2023 · 2023
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A lightweight framework for high-quality code generation
Mohammed Latif Siddiq, Beatrice Casey, and Joanna C. S. Santos. 2023 · 2023
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Llmseceval: A dataset of natural language prompts for security evaluations
Catherine Tony, Markus Mutas, Nicolas Díaz Ferreyra, and Riccardo Scandariato. 2023 · 2023
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Natural language generation and understanding of big code for ai-assisted programming: A review
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Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, and Graham Neubig. 2023 · 2023
Cited alongside, same era.
Critic: Large language models can self-correct with tool-interactive critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, and Weizhu Chen. 2023 · 2023
Cited alongside, same era.
Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark. 2023 · 2023
Cited alongside, same era.
Is self-repair a silver bullet for code generation?
Theo X Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, and Armando Solar-Lezama. 2023 · 2023
Cited alongside, same era.
Examining zero-shot vulnerability repair with large language models
Hammond Pearce, Benjamin Tan, Baleegh Ahmad, Ramesh Karri, and Brendan Dolan-Gavitt. 2023 · 2023
Cited alongside, same era.
Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, et al. 2023 · 2023
Cited alongside, same era.
Man-Fai Wong, Shangxin Guo, Ching-Nam Hang, Siu-Wai Ho, and Chee-Wei Tan. 2023 · 2023
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Kamal Ndousse Yuntao Bai, Andy Jones. 2023 · 2023
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Codegeex: A pre-trained model for code generation with multilingual evaluations on humaneval-x
Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Zihan Wang, Lei Shen, Andi Wang, Yang Li, et al. 2023 · 2023
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Docprompting: Generating code by retrieving the docs
Shuyan Zhou, Uri Alon, Frank F. Xu, Zhiruo Wang, Zhengbao Jiang, and Graham Neubig. 2023 · 2023
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Using an llm to help with code understanding
Daye Nam, Andrew Macvean, Vincent Hellendoorn, Bogdan Vasilescu, and Brad Myers. 2024 · 2024
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Software testing with large language models: Survey, landscape, and vision
Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, and Qing Wang. 2024 · 2024
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Bigcodebench: Benchmarking code generation with diverse function calls and complex instructions
Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, et al. 2024 · 2024
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