HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks
Published in In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP 2021), to appear, 2021
Recommended citation: Xuye Liu*, Dakuo Wang*, April Yi Wang, Yufang Hou, and Lingfei Wu. . HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP 2021), to appear https://arxiv.org/abs/2104.01002
BibTex citation:
@article{DBLP:journals/corr/abs-2104-01002, author = {Xuye Liu and Dakuo Wang and April Yi Wang and Lingfei Wu}, title = {HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks}, journal = {CoRR}, volume = {abs/2104.01002}, year = {2021}, url = {https://arxiv.org/abs/2104.01002}, eprinttype = {arXiv}, eprint = {2104.01002}, timestamp = {Mon, 12 Apr 2021 16:14:56 +0200}, biburl = {https://dblp.org/rec/journals/corr/abs-2104-01002.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }