no code implementations • Findings (EMNLP) 2021 • Fuxiang Chen, Mijung Kim, Jaegul Choo
To tackle this problem, previous work on code summarization, the task of automatically generating code description given a piece of code reported that an auxiliary learning model trained to produce API (Application Programming Interface) embeddings showed promising results when applied to a downstream, code summarization model.
no code implementations • 5 Apr 2022 • Fuxiang Chen, Fatemeh Fard, David Lo, Timofey Bryksin
Furthermore, some programming languages are inherently different and code written in one language usually cannot be interchanged with the others, i. e., Ruby and Java code possess very different structure.
no code implementations • 5 Apr 2022 • Rishab Sharma, Fuxiang Chen, Fatemeh Fard
Although researchers have been studying multiple ways to generate code comments automatically, previous work mainly considers representing a code token in its entirety semantics form only (e. g., a language model is used to learn the semantics of a code token), and additional code properties such as the tree structure of a code are included as an auxiliary input to the model.
no code implementations • 5 Apr 2022 • Rishab Sharma, Fuxiang Chen, Fatemeh Fard, David Lo
When identifiers' embeddings are used in CodeBERT, a code-based PLM, the performance is improved by 21-24% in the F1-score of clone detection.
no code implementations • IJCNLP 2019 • Fuxiang Chen, Seung-won Hwang, Jaegul Choo, Jung-Woo Ha, Sunghun Kim
Here we describe a new NL2pSQL task to generate pSQL codes from natural language questions on under-specified database issues, NL2pSQL.