CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding\n and Generation
Shuai Lu, Shujie Liu(Shijiazhuang University), Shuo Ren, Michele Tufano, Sheng‐Yu Fu(University of North Carolina at Charlotte), Ambrosio Blanco, Lidong Zhou(Microsoft (United States)), Junjie Huang(Wuhan Textile University), Nan Duan(Microsoft Research Asia (China)), Dawn Drain, Daxin Jiang(Jiangsu University), Shao Kun Deng, Linjun Shou(Microsoft Research Asia (China)), Neel Sundaresan, Long Zhou(BGI Group (China)), Ge Li(Monash Health), Ming Zhou(Langdon Hospital), Ming Gong(Microsoft Research Asia (China)), A. Svyatkovskiy(Google (United States)), Duyu Tang(Microsoft Research Asia (China)), Daya Guo(Sun Yat-sen University), Colin B. Clement(Microsoft Research (United Kingdom))
Cited by 29
Related Papers
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
|Unknown|2020|2.5k
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-Modal Pre-Training
|Proceedings of the AAAI Conference on Artificial Intelligence|2020|744
CLIP4Clip: An empirical study of CLIP for end to end video clip retrieval and captioning
|Neurocomputing|2022|676
UniXcoder: Unified Cross-Modal Pre-training for Code Representation
|Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)|2022|554