GrammarT5: Grammar-Integrated Pretrained Encoder-Decoder Neural Model for Code
Abstract
Pretrained models for code have exhibited promising performance across various code-related tasks, such as code summarization, code completion, code translation, and bug detection. However, despite their success, the majority of current models still represent code as a token sequence, which may not adequately capture the essence of the underlying code structure.
BibTeX
@inproceedings{Zhu-al:ICSE24,
author = {Qihao Zhu and
Qingyuan Liang and
Zeyu Sun and
Yingfei Xiong and
Lu Zhang and
Shengyu Cheng},
title = {{GrammarT5:} {Grammar-Integrated} Pretrained {Encoder-Decoder} Neural Model for Code},
booktitle = {ICSE},
pages = {76:1--76:13},
publisher = {{ACM}},
year = {2024},
}