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Recently, there has been increasing activity in using deep learning for software engineering, including tasks like code generation and summarization.
Bleu: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., and Zhu, W.-J · 2002
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Lin, C.-Y · 2004
Earlier work this paper cites.
ORANGE: a method for evaluating automatic evaluation metrics for machine translation
Lin, C.-Y., and Och, F. J · 2004
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation, 2014
Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., and Bengio, Y · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Sutskever, I., Vinyals, O., and Le, Q. V · 2014
Earlier work this paper cites.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L. u., and Polosukhin, I · 2017
Earlier work this paper cites.
Spoc: Search-based pseudocode to code
Kulal, S., Pasupat, P., Chandra, K., Lee, M., Padon, O., Aiken, A., and Liang, P. S · 2019
Earlier work this paper cites.
Automatic source code summarization with extended tree-lstm
Shido, Y., Kobayashi, Y., Yamamoto, A., Miyamoto, A., and Matsumura, T · 2019
Earlier work this paper cites.
Codesearchnet challenge: Evaluating the state of semantic code search, 2020
Husain, H., Wu, H.-H., Gazit, T., Allamanis, M., and Brockschmidt, M · 2020
Earlier work this paper cites.
Program synthesis with large language models, 2021
Austin, J., Odena, A., Nye, M., Bosma, M., Michalewski, H., Dohan, D., Jiang, E., Cai, C., Terry, M., Le, Q., and Sutton, C · 2021
Earlier work this paper cites.
Evaluating large language models trained on code, 2021
Chen, M., Tworek, J., Jun, H., Yuan, Q., and de Oliveira Pinto et al., H. P · 2021
Earlier work this paper cites.
Measuring coding challenge competence with apps, 2021
Hendrycks, D., Basart, S., Kadavath, S., Mazeika, M., Arora, A., Guo, E., Burns, C., Puranik, S., He, H., Song, D., and Steinhardt, J · 2021
Cited alongside, same era.
Codexglue: A machine learning benchmark dataset for code understanding and generation, 2021
Lu, S., Guo, D., Ren, S., Huang, J., Svyatkovskiy, A., and et al., A. B · 2021
Cited alongside, same era.
Bi-lstm-based neural source code summarization
Aljumah, S., and Berriche, L · 2022
Cited alongside, same era.
Ds-1000: A natural and reliable benchmark for data science code generation, 2022
Lai, Y., Li, C., Wang, Y., Zhang, T., Zhong, R., Zettlemoyer, L., tau Yih, S. W., Fried, D., Wang, S., and Yu, T · 2022
Cited alongside, same era.
Santacoder: don’t reach for the stars!, 2023
Allal, L. B., Li, R., Kocetkov, D., Mou, C., and et al., C. A · 2023
Cited alongside, same era.
Incoder: A generative model for code infilling and synthesis, 2023
Gemini: A family of highly capable multimodal models, 2023
Team, G., Anil, R., Borgeaud, S., Wu, Y., and et al., J.-B. A · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models, 2023
Touvron, H., Martin, L., Stone, K., Albert, P., and et al., A. A · 2023
Later among the works it cites.
Magicoder: Source code is all you need, 2023
Wei, Y., Wang, Z., Liu, J., Ding, Y., and Zhang, L · 2023
Later among the works it cites.
Wizardlm: Empowering large language models to follow complex instructions, 2023
Xu, C., Sun, Q., Zheng, K., Geng, X., Zhao, P., Feng, J., Tao, C., and Jiang, D · 2023
Later among the works it cites.
Codegeex: A pre-trained model for code generation with multilingual evaluations on humaneval-x, 2023
Zheng, Q., Xia, X., Zou, X., Dong, Y., Wang, S., Xue, Y., Wang, Z., Shen, L., Wang, A., Li, Y., Su, T., Yang, Z., and Tang, J · 2023
Later among the works it cites.
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Fried, D., Aghajanyan, A., Lin, J., Wang, S., Wallace, E., Shi, F., Zhong, R., tau Yih, W., Zettlemoyer, L., and Lewis, M · 2023
Cited alongside, same era.
Starcoder: may the source be with you!, 2023
Li, R., Allal, L. B., Zi, Y., Muennighoff, N., and et al., D. K · 2023
Cited alongside, same era.
Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation, 2023
Liu, J., Xia, C. S., Wang, Y., and Zhang, L · 2023
Cited alongside, same era.
Wizardcoder: Empowering code large language models with evol-instruct
Luo, Z., Xu, C., Zhao, P., Sun, Q., Geng, X., Hu, W., Tao, C., Ma, J., Lin, Q., and Jiang, D · 2023
Cited alongside, same era.
Octopack: Instruction tuning code large language models
Muennighoff, N., Liu, Q., Zebaze, A., Zheng, Q., Hui, B., Zhuo, T. Y., Singh, S., Tang, X., von Werra, L., and Longpre, S · 2023
Cited alongside, same era.
Code llama: Open foundation models for code, 2023
Rozière, B., Gehring, J., Gloeckle, F., Sootla, S., Gat, I., Tan, X. E., Adi, Y., Liu, J., Remez, T., Rapin, J., Kozhevnikov, A., Evtimov, I., Bitton, J., Bhatt, M., Ferrer, C. C., Grattafiori, A., Xiong, W., Défossez, A., Copet, J., Azhar, F., Touvron, H., Martin, L., Usunier, N., Scialom, T., and Synnaeve, G · 2023
Cited alongside, same era.
Llama 3 model card
AI@Meta
Cited in the paper.
Guo, D., Zhu, Q., Yang, D., Xie, Z., Dong, K., Zhang, W., Chen, G., Bi, X., Wu, Y., Li, Y. K., Luo, F., Xiong, Y., and Liang, W · 2024
Closest in time.
Gpt-4 technical report, 2024
OpenAI, Achiam, J., Adler, S., Agarwal, S., and et al., L. A · 2024
Closest in time.
Humaneval-xl: A multilingual code generation benchmark for cross-lingual natural language generalization, 2024
Peng, Q., Chai, Y., and Li, X · 2024
Closest in time.
Wavecoder: Widespread and versatile enhanced instruction tuning with refined data generation, 2024
Yu, Z., Zhang, X., Shang, N., Huang, Y., Xu, C., Zhao, Y., Hu, W., and Yin, Q · 2024
Closest in time.
Summarizing source code using a neural attention model
Iyer, S., Konstas, I., Cheung, A., and Zettlemoyer, L · 2083
Closest in time.