GAP-Gen: Guided Automatic Python Code Generation

19 January 2022

Papers citing "GAP-Gen: Guided Automatic Python Code Generation"

3 / 3 papers shown

Title
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation Yue Wang Weishi Wang Shafiq R. Joty S. Hoi 235 1,489 0 02 Sep 2021
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation Shuai Lu Daya Guo Shuo Ren Junjie Huang Alexey Svyatkovskiy ... Nan Duan Neel Sundaresan Shao Kun Deng Shengyu Fu Shujie Liu ELM 198 1,105 0 09 Feb 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018