AceCoder: Utilizing Existing Code to Enhance Code Generation

Language models are few-shot learners

Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901

Earlier work this paper cites.

Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics . 311–318

Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002

Earlier work this paper cites.

Test-driven development: by example

Kent Beck. 2003 · 2003

Earlier work this paper cites.

Rouge: A package for automatic evaluation of summaries. In Text Summarization Branches Out: Proceedings of the ACL-04 Workshop, Barcelona, Spain . 74–81

CY LIN. 2004 · 2004

Earlier work this paper cites.

Large-scale code reuse in open source software. In First International Workshop on Emerging Trends in FLOSS Research and Development (FLOSS’07: ICSE Workshops 2007) . IEEE, 7–7

Audris Mockus. 2007 · 2007

Earlier work this paper cites.

The probabilistic relevance framework: BM25 and beyond

Stephen Robertson, Hugo Zaragoza, et al · 2009

Earlier work this paper cites.

A retrieve-and-edit framework for predicting structured outputs

Tatsunori B Hashimoto, Kelvin Guu, Yonatan Oren, and Percy S Liang. 2018 · 2018

Earlier work this paper cites.

Improving language understanding by generative pre-training

Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018

Earlier work this paper cites.

Language models are unsupervised multitask learners

Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019

Earlier work this paper cites.

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019 , Kentaro Inui, Jing Jiang, Vincent Ng, and Xiaojun Wan (Eds.). Association for Computational Linguistics, 3980–3990

Nils Reimers and Iryna Gurevych. 2019 · 2019

Earlier work this paper cites.

The Curious Case of Neural Text Degeneration. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020 . OpenReview.net

Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020

Earlier work this paper cites.

Retrieve and refine: exemplar-based neural comment generation. In 2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 349–360

Bolin Wei, Yongmin Li, Ge Li, Xin Xia, and Zhi Jin. 2020 · 2020

Earlier work this paper cites.

Unified Pre-training for Program Understanding and Generation. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Online, 2655–2668

Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang. 2021 · 2021

Earlier work this paper cites.

Program synthesis with large language models

Original

Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al · 2021

Earlier work this paper cites.

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

Earlier work this paper cites.

In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)

Dan Hendrycks, Steven Basart, Saurav Kadavath, Mantas Mazeika, Akul Arora, Ethan Guo, Collin Burns, Samir Puranik, Horace He, Dawn Song, et al · 2021

Cited alongside, same era.

Editsum: A retrieve-and-edit framework for source code summarization. In 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 155–166

Jia Li, Yongmin Li, Ge Li, Xing Hu, Xin Xia, and Zhi Jin. 2021 · 2021

Cited alongside, same era.

Retrieval Augmented Code Generation and Summarization. In Findings of the Association for Computational Linguistics: EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 16-20 November, 2021 , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, 2719–2734

Md. Rizwan Parvez, Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang. 2021 · 2021

Cited alongside, same era.

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, Online and Punta Cana, Dominican Republic, 8696–8708

Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022

Later among the works it cites.

Code Alpaca: An Instruction-following LLaMA model for code generation

Sahil Chaudhary. 2023 · 2023

Closest in time.

Enabling Programming Thinking in Large Language Models Toward Code Generation

Original

Jia Li, Ge Li, Yongmin Li, and Zhi Jin. 2023b · 2023

Closest in time.

CodeEditor: Learning to Edit Source Code with Pre-Trained Models

Jia Li, Ge Li, Zhuo Li, Zhi Jin, Xing Hu, Kechi Zhang, and Zhiyi Fu. 2023d · 2023

Closest in time.

SkCoder: A Sketch-based Approach for Automatic Code Generation. In 45th IEEE/ACM International Conference on Software Engineering, ICSE 2023, Melbourne, Australia, May 14-20, 2023 . IEEE, 2124–2135

Jia Li, Yongmin Li, Ge Li, Zhi Jin, Yiyang Hao, and Xing Hu. 2023c · 2023