region:us
CodeXGLUE is a benchmark dataset to foster machine learning research for program understanding and generation. 
CodeXGLUE includes a collection of 10 tasks across 14 datasets and a platform for model evaluation and comparison.
@article{Lu2021,
author = {Lu, Shuai and Guo, Daya and Ren, Shuo and Huang, Junjie and Svyatkovskiy, Alexey and Blanco, Ambrosio and Clement, Colin B. and Drain, Dawn and Jiang, Daxin and Tang, Duyu and Li, Ge and Zhou, Lidong and Shou, Linjun and Zhou, Long and Tufano, Michele and Gong, Ming and Zhou, Ming and Duan, Nan and Sundaresan, Neel and Deng, Shao Kun and Fu, Shengyu and Liu, Shujie},
year = {2021},
booktitle = {arXiv},
title = {CodeXGLUE - A Machine Learning Benchmark Dataset for Code Understanding and Generation}
}
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