Improving code autocompletion with transfer learning

W Zhou, S Kim, V Murali, GA Aye - Proceedings of the 44th International …, 2022 - dl.acm.org
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integration. Recently …
Запазване Позоваване С позовавания в 14 Сродни статии

Improving Code Autocompletion with Transfer Learning

W Zhou, S Kim, V Murali, GA Aye - arXiv preprint arXiv:2105.05991, 2021 - arxiv.org
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integrations. Recently …
Позоваване

Improving Code Autocompletion with Transfer Learning

W Zhou, S Kim, V Murali, GA Aye - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integrations. Recently …
Позоваване

Improving Code Autocompletion with Transfer Learning

W Zhou, S Kim, V Murali, GA Aye - 2022 IEEE/ACM 44th …, 2022 - ieeexplore.ieee.org
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integration. Recently …
Позоваване

Improving Code Autocompletion with Transfer Learning

W Zhou, S Kim, V Murali, GA Aye - 2022 IEEE/ACM 44th International …, 2022 - computer.org
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integration. Recently …
Позоваване
[PDF] academia.edu

[PDF][PDF] Improving Code Autocompletion with Transfer Learning

W Zhou, S Kim, V Murali, GA Aye - academia.edu
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integrations. Recently …
Позоваване